U.S. patent application number 13/741491 was filed with the patent office on 2014-07-17 for method and apparatus for controlling multi-dimensional peak-to-average-power-ratio (papr) with constraints.
The applicant listed for this patent is John David Terry. Invention is credited to John David Terry.
Application Number | 20140198863 13/741491 |
Document ID | / |
Family ID | 51165124 |
Filed Date | 2014-07-17 |
United States Patent
Application |
20140198863 |
Kind Code |
A1 |
Terry; John David |
July 17, 2014 |
METHOD AND APPARATUS FOR CONTROLLING MULTI-DIMENSIONAL
PEAK-TO-AVERAGE-POWER-RATIO (PAPR) WITH CONSTRAINTS
Abstract
A method and system uses a constrained set of indexed samples to
identify a next generation population of samples that exhibits a
more desirable signal characteristic. The invention generates an
intermediate set of indexed samples which are subjected to a
fitness function and next generation calculations to produce next
generation indexes for the next population of samples. The next
generation indexes population of samples is further constrained
over initial indexes for generating a more desirable signal
characteristic. In an example, the PAPR for all samples of the
population are reduced.
Inventors: |
Terry; John David;
(Annandale, VA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Terry; John David |
Annandale |
VA |
US |
|
|
Family ID: |
51165124 |
Appl. No.: |
13/741491 |
Filed: |
January 15, 2013 |
Current U.S.
Class: |
375/260 ;
375/340 |
Current CPC
Class: |
H04L 27/2623
20130101 |
Class at
Publication: |
375/260 ;
375/340 |
International
Class: |
H04L 27/26 20060101
H04L027/26 |
Claims
1. A method for controlling the peak-to-average-power ratio (PAPR)
for a collection of data samples having OFDM signal components,
comprising: receiving a data sample signal; indexing said data
sample signal; evaluating the PAPR of said indexed data sample
signal; preparing a fitness result based on said evaluation;
subjecting said fitness result to algorithmic process to generate a
next generation index; preparing a next generation data sample
based on said next generation indexes, the PAPR of said next
generation data sample being less than said PAPR of said indexed
data sample, wherein said next generation sample conforms to at
least one independent international standard, wherein said next
generation sample is receivable by a receiver for demodulating and
decoding separately each constituent protocol stream of said next
generation sample without requiring additional information to be
transmitted outside of said protocols, and wherein said calculation
of said PAPR of each constituent protocol stream results in a lower
PAPR for every constituent stream of the collection.
2. (canceled)
3. (canceled)
4. The method according to claim 1, wherein said next generation
sample contains an alternate representation of a constituent
protocol stream component, said alternate representation of said
constituent protocol stream differing from said constituent
protocol stream in a cyclic time shift, wherein said alternate
representation of said constituent protocol stream is generated
based on a characteristic of said constituent protocol stream.
5. The method according to claim 1, further comprising performing
the algorithmic process in iterative steps, wherein each iterative
step results in the lowering PAPR or equal PAPR of the previous
iteration for every constituent protocol stream, and terminating
the algorithmic process for PAPR calculations below a targeted
threshold.
6. The method according to claim 4, wherein said alternate
representation of said constituent protocol stream meets a
regulatory emission criterion of the governing regulatory body of
the country in which a transmitter transmitting said alternate
representation operates.
7. The method according to claim 1, wherein the algorithmic process
outputs a set of parameters to a transmitter subsystem for
producing equivalent radio frequency representations of the next
generation sample.
8. A method of reducing multi-dimensional Peak-to-Average-Ratio
Power Ratio (PAPR) in a collection of aggregate waveforms, wherein
each aggregate waveform contains at least a first individual stream
constructed using orthogonal frequency multiplexed stream
components, the method comprising: receiving a first signal;
sampling said first signal into a plurality of first signal
samples; sequentially indexing said plurality of first signal
samples; combining n number of said indexed first signal samples
into a set of indexed first signal samples; forming a first subset
of n.sub.s number of said set of indexed first signal samples,
wherein n.sub.s<n, and wherein said first subset of indexed
first signal samples includes a first indexed sample of said set of
indexed first signal samples; forming a second subset of n.sub.s
number of set of indexed first signal samples, wherein said second
subset of indexed first signal samples includes a last indexed
sample of said set of indexed first signal samples; forming an
augmented set of indexed first signal samples, including appending
said first subset of said set of indexed first signal samples to
said set of indexed first signal samples, and prepending said
second subset of said set of indexed first signal samples to said
set of indexed first signal samples; generating an augmented set of
indexed first signal samples PAPR; receiving a second signal;
sampling said second signal into a plurality of second signal
samples; sequentially indexing said plurality of second signal
samples; combining x number of said indexed second signal samples
into a set of indexed second signal samples; forming a first subset
of x.sub.s number of said set of indexed second signal samples,
wherein x.sub.s<x, and wherein said first subset of said set of
indexed second signal samples includes a first indexed sample of
said set of indexed second signal samples; forming a second subset
of x.sub.s number of said set of indexed second signal samples,
wherein said second subset of indexed second signal samples
includes a last indexed second signal sample of said set of indexed
second signal samples; forming an augmented set of indexed second
signal samples, including appending said first subset of indexed
second signal samples to said set of indexed second signal samples,
and prepending said second subset of indexed second signal samples
to said set of indexed second signal samples; generating an
augmented set of indexed second signal samples PAPR; generating a
first aggregated waveform PAPR based on said augmented set of
indexed first signal samples PAPR and said augmented set of indexed
second signal samples PAPR; receiving a third signal; sampling said
third signal into a plurality of third signal samples; sequentially
indexing said plurality of third signal samples; combining p number
of said indexed third signal samples into a set of indexed third
signal samples; forming a first subset of p.sub.s number of said
set of indexed third signal samples, wherein p.sub.s<p, and
wherein said first subset of set of indexed third signal samples
includes a first indexed third signal sample of said set of indexed
third signal samples; forming a second subset of p.sub.s number of
said set of indexed third signal samples, wherein said second
subset of indexed third signal samples includes a last indexed
third signal sample of said set of indexed third signal samples;
forming an augmented set of indexed third signal samples, including
appending said first subset of said set of indexed third signal
samples to said set of indexed third signal samples, and prepending
said second subset of said set of indexed third signal samples to
said set of indexed third signal samples; generating an augmented
set of indexed third signal samples PAPR; receiving a fourth
signal; sampling said fourth signal into a plurality of fourth
signal samples; sequentially indexing said plurality of fourth
signal samples; combining r number of said indexed fourth signal
samples into a set of indexed fourth signal samples; forming a
first subset of r.sub.s number of said set of indexed fourth signal
samples, wherein r.sub.s<r, and wherein said first subset of
said set of indexed fourth signal samples includes a first indexed
sample of said set of indexed fourth signal samples; forming a
second subset of r.sub.s number of said set of indexed fourth
signal samples, wherein said second subset of said set of indexed
fourth signal samples includes a last indexed sample of said set of
indexed fourth signal samples; forming an augmented set of indexed
fourth signal samples, including appending said first subset of
said set of indexed fourth signal samples to said set of indexed
fourth signal samples, and prepending said second subset of said
set of indexed fourth signal samples to said set of indexed fourth
signal samples; generating an augmented set of indexed fourth
signal samples PAPR; generating a second aggregate waveform PAPR
based on said augmented set of indexed third signal samples PAR and
said augmented set of indexed fourth signal samples PAPR; comparing
said first aggregate waveform PAPR and said second aggregate
waveform PAPR to determine a next generation PAPR; and evaluating
said next generation PAPR against an initial constraint to produce
a fitness result.
9. A method claim according to claim 1, further comprising:
generating multiple sets of next generation indexes based on said
fitness result, said multiple sets of next generation indexes
including a first set of next generation indexes comprising a set
of n.sub.m number of indexed first signal samples corresponding to
a subset of said set of indexed first signal samples, wherein
n.sub.m<n.sub.s, a second set of next generation indexes
comprising a set of x.sub.m number of next generation indexes
corresponding to a subset of said set of indexed second signal
samples, wherein x.sub.m<x.sub.s, a third set of next generation
indexes comprising a set of p.sub.m next generation indexes
corresponding to a subset of said set of indexed third signal
samples, wherein p.sub.m<p.sub.s, and a fourth set of next
generation indexes comprising a set of r.sub.m next generation
indexes corresponding to a subset said set of indexed fourth signal
samples, wherein r.sub.m<r.sub.s.
10. A method of claim 1, further comprising: generating a first
next generation segment based on said first set of next generation
indexes, wherein said first next generation segment includes
n.sub.m number of samples corresponding to said first set of next
generation indexes; forming a first subset of n.sub.c number of
said first next generation segment samples, wherein
n.sub.c<n.sub.m and wherein said first subset of first next
generation segment samples includes a first indexed sample of said
set first next generation segment; forming a second subset of
n.sub.c number of said first next generation segment samples,
wherein said second subset of said first next generation segment
samples includes a last indexed sample of said first next
generation segment; forming a first augmented next generation
segment, wherein said forming said first augmented next generation
segment includes appending said first subset of first next
generation segment samples to said first next generation segment,
and prepending said second subset of said first next generation
segment samples to said first next generation segment; generating a
first augmented next generation segment PAPR; generating a second
mutated sample segment based on said second set of next generation
indexes, wherein said second mutated sample segment includes
x.sub.m number of samples corresponding to said second set of next
generation indexes; forming a first subset of x.sub.c number of
said second next generation segment samples, wherein
x.sub.c<x.sub.m and wherein said first subset of said second
next generation segment samples includes a first indexed sample of
said second next generation segment; forming a second subset of
x.sub.c number of said first next generation segment samples,
wherein said second subset of said second next generation segment
samples includes a last indexed sample of said second next
generation segment; forming a second augmented next generation
segment, wherein said forming said second augmented next generation
segment includes appending said first subset of second next
generation segment samples to said first next generation segment,
and prepending said second subset of said second next generation
segment samples to said second next generation segment; generating
a second augmented next generation segment PAPR; generating a first
mutated aggregated waveform PAPR based on said first augmented next
generation segment PAPR and said second augmented mutated segment
PAPR; generating a third mutated sample segment based on said third
set of next generation indexes, wherein said third mutated sample
segment includes p.sub.m number of samples corresponding to said
third set of next generation indexes; forming a first subset of
p.sub.c number of said third next generation segment samples,
wherein p.sub.c<p.sub.m and wherein said first subset of third
next generation segment samples includes a first indexed sample of
said third next generation segment; forming a second subset of
p.sub.c number of said third next generation segment samples,
wherein said second subset of said third next generation segment
samples includes a last indexed sample of said third next
generation segment; forming a third augmented next generation
segment, wherein said forming said third augmented next generation
segment includes appending said first subset of third next
generation segment samples to said third next generation segment,
and prepending said second subset of said third next generation
segment samples to said third next generation segment; generating a
third augmented next generation segment PAPR; generating a fourth
next generation segment based on said fourth set of next generation
indexes, wherein said fourth next generation segment includes
r.sub.m number of samples corresponding to said fourth set of next
generation indexes; forming a first subset of r.sub.c number of
said fourth next generation segment samples, wherein
r.sub.c<r.sub.m and wherein said first subset of fourth next
generation segment samples includes a first indexed sample of said
set fourth next generation segment; forming a second subset of
r.sub.c number of said fourth next generation segment samples,
wherein said second subset of said fourth next generation segment
samples includes a last indexed sample of said fourth next
generation segment; forming a fourth augmented next generation
segment, wherein said forming said fourth augmented next generation
segment includes appending said first subset of fourth next
generation segment samples to said fourth next generation segment,
and prepending said second subset of said fourth next generation
segment samples to said fourth next generation segment; generating
a fourth augmented next generation segment PAPR; generating a
fourth mutated aggregate waveform PAPR based on said third
augmented next generation segment PAPR and said fourth augmented
next generation segment PAPR; comparing said third mutated
aggregate waveform PAPR and said fourth mutated aggregate waveform
PAPR to determine a second maximum PAPR; and evaluating said second
maximum PAPR against said initial constraint to produce a second
fitness result.
11. An apparatus for minimizing the peak-to-average-power ratio
(PAPR) for a collection of data samples having OFDM signal
components, comprising: an input for receiving said collection of
data samples signals, wherein at least one of said data sample
signals includes OFDM signal components; a processor configured to
evaluate the PAPR of said data sample signals, analyze the data
samples according to said PAPR and at least one criteria based
using an iterative algorithmic process, preparing a next generation
data sample based on the results of said analysis, and calculating
the PAPR of said next generation data sample; an output port
configured to output information representing combined waveform of
next generation samples, said PAPR of said next generation data
sample being less than said PAPR of said indexed data sample,
wherein said next generation sample comprises multiple constituent
protocol streams, wherein said next generation sample conforms to
at least one independent international standard, wherein said next
generation sample is receivable by a receiver for demodulating and
decoding separately each constituent protocol stream of said next
generation sample without requiring additional information to be
transmitted outside of said protocols, and wherein said calculation
of said PAPR of each constituent protocol stream results in a lower
PAPR for every constituent stream.
12. (canceled)
13. (canceled)
14. An apparatus according to claim 11, wherein said next
generation sample contains an alternate representation of a
constituent protocol stream component, said alternate
representation of said constituent protocol stream differing from
said constituent protocol stream in a cyclic time shift, wherein
said alternate representation of said constituent protocol stream
is generated based on a characteristic of said constituent protocol
stream.
15. An apparatus according to claim 11, wherein said processor is
further configured to perform the algorithmic process in iterative
steps, wherein each iterative step results in the lowering PAPR or
equal PAPR of the previous iteration for every constituent protocol
stream, and terminating the algorithmic process for PAPR
calculations below a targeted threshold.
16. An apparatus according to claim 14, wherein said alternate
representation of said constituent protocol stream meets a
regulatory emission criterion of the governing regulatory body of
the country in which the device operations.
17. An apparatus according to claim 11, wherein said algorithmic
process outputs a set of parameters to a transmitter subsystem for
producing equivalent radio frequency representations of the next
generation sample.
Description
FIELD OF INVENTION
[0001] This invention relates generally to wireless communication
systems. In particular, this invention relates to a method for
controlling the peak-to-average-power-ratio (PAPR) of a collection
of aggregate waveforms.
BACKGROUND OF INVENTION
[0002] A wireless communication device in a communication system
communicates directly or indirectly with other wireless
communication devices. For direct/point-to-point communications,
the participating wireless communication devices tune their
receivers and transmitters to the same channel(s) and communicate
over those channels. For indirect wireless communications, each
wireless communication device communicates directly with an
associated base station and/or access point via an assigned
channel.
[0003] Each wireless communication device participating in wireless
communications includes a built-in radio transceiver (i.e.,
transmitter and receiver) or is coupled to an associated radio
transceiver. Typically, the transmitter includes one antenna for
transmitting radiofrequency (RF) signals, which are received by one
or more antennas of the receiver. When the receiver includes two or
more antennas, the receiver selects one of antennas to receive the
incoming RF signals. This type of wireless communication between
the transmitter and receiver is known as a
single-output-single-input (SISO) communication.
[0004] Generally speaking, transmission systems compliant with the
IEEE 802.11a and 802.11g or "802.11a/g" as well as the 802.11n
standards achieve their high data transmission rates using
Orthogonal Frequency Division Modulation (OFDM) encoded symbols
mapped up to a 64 quadrature amplitude modulation (QAM)
multi-carrier constellation. In a general sense, the use of OFDM
divides the overall system bandwidth into a number of frequency
sub-bands or channels, with each frequency sub-band being
associated with a respective sub-carrier upon which data may be
modulated. Thus, each frequency sub-band of the OFDM system may be
viewed as an independent transmission channel within which to send
data, thereby increasing the overall throughput or transmission
rate of the communication system. Similarly, multi-code spread
spectrum system comprised of perfectly orthogonal high-speed chaos
spreading codes transporting independent modulated data can be used
to increase its overall throughput or transmission rate of the SISO
system. The high-speed "spreading signals" belong to the class of
signals referred to as Pseudo Noise (PN) or pseudo-random signal.
This class of signals possesses good autocorrelation and
cross-correlation properties such that different PN sequences are
nearly orthogonal to one other. The autocorrelation and
cross-correlation properties of these PN sequences allow the
original information bearing signal to be spread at the
transmitter.
[0005] Transmitters used in the wireless communication systems that
are compliant with the aforementioned 802.11a/802.11g/802.11n
standards as well as other standards such as the 802.16a IEEE
Standard, typically perform multi-carrier OFDM symbol encoding
(which may include error correction encoding and interleaving),
convert the encoded symbols into the time domain using Inverse Fast
Fourier Transform (IFFT) techniques, and perform digital to analog
conversion and conventional radio frequency (RF) upconversion on
the signals. These transmitters then transmit the modulated and
upconverted signals after appropriate power amplification to one or
more receivers, resulting in a relatively high-speed time domain
signal with a high peak-to-average ratio (PAPR).
[0006] Likewise, the receivers used in the wireless communication
systems that are compliant with the aforementioned
802.11a/802.11g/802.11n and 802.16a IEEE standards typically
include an RF receiving unit that performs RF downconversion and
filtering of the received signals (which may be performed in one or
more stages), and a baseband processor unit that processes the OFDM
encoded symbols bearing the data of interest. The digital form of
each OFDM symbol presented in the frequency domain is recovered
after baseband downconverting, conventional analog to digital
conversion and Fast Fourier Transformation of the received time
domain signal.
[0007] To further increase the number of signals which may be
propagated in the communication system and/or to compensate for
deleterious effects associated with the various propagation paths,
and to thereby improve transmission performance, it is known in the
art to use multiple transmission and receive antennas within a
wireless transmission system. Such a system is commonly referred to
as a multiple-input, multiple-output (MIMO) wireless transmission
system and is specifically provided for within the 802.11n IEEE
Standard now adopted and being adopted in IEEE 802.16m and 3GPP-LTE
Advance. As is known, the use of MIMO technology produces
significant increases in spectral efficiency, throughput and link
reliability, and these benefits generally increase as the number of
transmission and receive antennas within the MIMO system
increases.
[0008] In particular, in addition to the frequency channels created
by the use of OFDM, a MIMO channel formed by the various
transmissions and receive antennas between a particular transmitter
and a particular receiver includes a number of independent spatial
channels. As is known, a wireless MIMO communication system can
provide improved performance (e.g., increased transmission
capacity) by utilizing the additional dimensionalities created by
these spatial channels for the transmission of additional data. Of
course, the spatial channels of a wideband MIMO system may
experience different channel conditions (e.g., different fading and
multi-path effects) across the overall system bandwidth and may
therefore achieve different signal-to-noise ratio (SNRs) at
different frequencies (i.e., at the different OFDM frequency
sub-bands) of the overall system bandwidth. Consequently, the
number of information bits per modulation symbol (i.e., the data
rate) that may be transmitted using the different frequency
sub-bands of each spatial channel for a particular level of
performance may differ from frequency sub-band to frequency
sub-band.
[0009] In the MIMO-OFDM communication system, a high
Peak-to-Average Power Ratio (PAPR) may be caused by the multiple
carrier modulation. That is, because data are transmitted using
multiple carriers in the MIMO-OFDM scheme, the final OFDM signals
have amplitude obtained by summing up amplitudes of each carrier.
The high PAPR results when the carrier signal phases are added
constructively (zero phase difference) or destructively (.+-.180
phase difference). Notably, OFDM signals have a higher
peak-to-average power ratio (PAPR) than single-carrier signals do.
The reason is that in the time domain, a multicarrier signal is the
sum of many narrowband signals. At some time instances, this sum is
large and at other times is small, which means that the peak value
of the signal is substantially larger than the average value.
Similarly, MIMO schemes can have high PAPR for periodic sequence or
binary-valued sequence.
[0010] High PAPR also results in MIMO schemes when multiple
aggregate waveforms are transmitted in the same channel. In this
instance, an aggregate waveform consists of a multiple combined
individual waveforms/streams. The PAPR of an aggregate waveform is
computed after combining the individual streams. Consequently, the
highest PAPR amongst multiple aggregate waveforms is computed from
the PAPRs of the combined individual waveforms. The continually
increasing reliance on SISO and new focus on MISO/MIMO wireless
forms of communication create an increasing need to decrease PAPR
in these schemes.
[0011] Consider two similar channels, each with average power
P.sub.0 and maximum instantaneous power P.sub.1. This corresponds
to a peak-to-average power ratio PAPR=P.sub.1/P.sub.0, usually
expressed in dB as PAPR[dB]=10 log(P.sub.1/P.sub.0). For the
combined signal, the average power is 2 P.sub.0 (an increase of 3
dB), but the maximum instantaneous power can be as high as 4
P.sub.1, an increase of 6 dB. Thus, PAPR for the combined signal
can increase by as much as 3 dB and, in general, the PAPR increases
by 10 log(n) for n signal. This maximum power will occur if the
signals from the two channels happen to have peaks which are in
phase. This may be a rare transient occurrence, but in general the
linear dynamic range of all transmitter components must be designed
for this possibility. Nonlinearities will create intermodulation
products, which will degrade the signal and cause it to spread into
undesirable regions of the spectrum. This, in turn, may require
filtering, and in any case will likely reduce the power efficiency
of the system.
[0012] This problem of the peak-to-average power ratio (PAPR) is a
well-known general problem in OFDM and related waveforms, since
they are constructed of multiple closely-spaced sub-channels. There
are a number of classic strategies to reducing the PAPR, which are
addressed in such review articles as "Directions and Recent
Advances in PAPR Reduction Methods", Hanna Bogucka, Proc. 2006 IEEE
International Symposium on Signal Processing and Information
Technology, pp. 821-827, incorporated herein by reference. These
PAPR reduction strategies include amplitude clipping and filtering,
coding, tone reservation, tone injection, active constellation
extension, and multiple signal representation techniques such as
partial transmit sequence (PTS), selective mapping (SLM), and
interleaving. These techniques can achieve significant PAPR
reduction, but at the expense of transmit signal power increase,
bit error rate (BER) increase, data rate loss, increase in
computational complexity, and so on. Further, many of these
techniques require the transmission of additional side-information
(about the signal transformation) together with the signal itself,
in order that the received signal to be properly decoded. Such
side-information reduces the generality of the technique,
particularly for a technology where one would like simple mobile
receivers to receive signals from a variety of base-station
transmitters. To the extent compatible, the techniques disclosed in
Bogucka, and otherwise known in the art, can be used in conjunction
with the techniques discussed herein-below.
[0013] Various efforts to solve the PAPR (Peak to Average Power
Ratio) issue in an OFDM transmission scheme, include a frequency
domain interleaving method, a clipping filtering method (See, for
example, X. Li and L. J. Cimini, "Effects of Clipping and Filtering
on the Performance of OFDM", IEEE Commun. Lett., Vol. 2, No. 5, pp.
131-133, May, 1998), a partial transmit sequence (PTS) method (See,
for example, L. J Cimini and N. R. Sollenberger, "Peak-to-Average
Power Ratio Reduction of an OFDM Signal Using Partial Transmit
Sequences", IEEE Commun. Lett., Vol. 4, No. 3, pp. 86-88, March,
2000), and a cyclic shift sequence (CSS) method (See, for example,
G. Hill and M. Faulkner, "Cyclic Shifting and Time Inversion of
Partial Transmit Sequences to Reduce the Peak-to-Average Ratio in
OFDM", PIMRC 2000, Vol. 2, pp. 1256-1259, September 2000). In
addition, to improve the receiving characteristic in OFDM
transmission when a non-linear transmission amplifier is used, a
PTS method using a minimum clipping power loss scheme (MCPLS) is
proposed to minimize the power loss clipped by a transmission
amplifier (See, for example, Xia Lei, Youxi Tang, Shaoqian Li, "A
Minimum Clipping Power Loss Scheme for Mitigating the Clipping
Noise in OFDM", GLOBECOM 2003, IEEE, Vol. 1, pp. 6-9, December
2003). The MCPLS is also applicable to a cyclic shifting sequence
(CSS) method.
[0014] In base station towers today, most 3G operators combine
several narrow band signals and transmit them through a common
power amplifier signal. However, the signal characteristics for 3G
networks (such as WCDMA) differ greatly from current 4G
technologies such as OFDM and OFDMA technologies, which tend to
have extreme maxima and minima in their signal envelope, compared
to nearly constant signal envelope. Spectrum combination for wide
bandwidths is inherently more challenging for amplifier designers
in terms of maintaining linearity across the total band. In
addition, very high PAPR exacerbate the poor operational efficiency
for the wideband power amplifier (PA). These PAs with lower
efficiencies result in greater heat dissipation requiring better
heat transfer mechanisms which lead to larger base stations,
increasing operator's capital and operating expenditure.
[0015] Traditionally, PAPR reduction techniques lead to distortion
the transmit signal characteristics, which is quantifiable by
Error-Vector-Magnitude (EVM). The goal is to minimize the effect on
EVM while reducing PAPR, which allows use of higher order
modulation scheme to result in higher spectral efficiencies. In
contrast, arbitrarily combining signals can lead to poor
operational efficiency for the wideband PA, higher costs for the
base station, and lower spectral efficiency for the network.
[0016] The continually increasing reliance on especially MISO
wireless forms of communication creates a need for means to reduce
the PAPR, especially in multi-carrier, multi-dimensional systems.
Such a method or system
[0017] Then according to the prior art, what is needed is a system
and method that reduces the PAPR of a data transmission by
eliminating the guesswork involved in randomly generating indexed
samples for PAPR optimization.
SUMMARY OF INVENTION
[0018] The present invention teaches improvements not found in the
prior art. The invention teaches a system, device and method for
controlling the peak-to-average-ratio (PAPR) of multiple aggregated
waveforms.
[0019] In one aspect, the invention teaches a generating a next
generation population of data points based on a common constraint.
The invention uses a fitness value to generate a set of identifying
indexes corresponding to data points nearer to a desired state
value.
[0020] In yet another aspect, the invention teaches generating
multiple sets of next generation/mutation indexes based on said
fitness result. The multiple sets of mutation indexes include a
first set of mutation indexes comprising a set of n.sub.m number of
indexed first signal samples corresponding to a subset of said set
of indexed first signal samples n.sub.s, wherein
n.sub.m<n.sub.s, a second set of mutation indexes comprising a
set of x.sub.m number of mutation indexes corresponding to a subset
of said set of indexed second signal samples x.sub.s, wherein
x.sub.m<x.sub.s, a third set of mutation indexes comprising a
set of p.sub.m mutation indexes corresponding to a subset of said
set of indexed third signal samples p.sub.s, wherein
p.sub.m<p.sub.s, and a fourth set of mutation indexes comprising
a set of r.sub.m mutation indexes corresponding to a subset said
set of indexed fourth signal samples r.sub.s, wherein
r.sub.m<r.sub.s.
[0021] In yet another aspect of the invention, a data signal is
received and sampled. The samples are indexed and organized in an
initial population of aggregate waveforms. The aggregate waveforms
are evaluated against a characteristic common to all aggregate
waveforms in the population. The indexes corresponding to aggregate
waveform with the desired fitness value are then subjected to
further processing to produce a set of indexes used to construct a
next generation population of aggregate waveforms which may produce
a more desired common characteristic result.
BRIEF DESCRIPTION OF DRAWINGS
[0022] A more complete understanding of the present invention may
be derived by referring to the various embodiments of the invention
described in the detailed descriptions and drawings and figures in
which like numerals denote like elements, and in which:
[0023] FIG. 1 is an exemplary MIMO wireless transmission system
that may be used with the various embodiments of the invention;
[0024] FIG. 2 is an exemplary method for generating an augmented
segmented signal, in accordance with various embodiments of the
invention;
[0025] FIG. 3 is an exemplary method for reducing PAPR for an
initial population in accordance with various embodiments of the
invention;
[0026] FIG. 4 is an exemplary schematic of a method for generating
next generation population with reduced PAPR in accordance with
various embodiments of the invention;
[0027] FIG. 5 is an exemplary flowchart of a method for reducing
PAPR in accordance with various embodiments of the invention;
[0028] FIG. 6 is an exemplary embodiment of second generation
aggregated waveform with reduced PAPR; and
[0029] FIG. 7 is an graphical example of the results of the
operation of the invention showing a reduced PAPR when the next
generation of indexes is constrained in accordance with the present
invention.
DETAILED DESCRIPTION
[0030] The brief description of exemplary embodiments of the
invention herein makes reference to the accompanying drawing and
flowchart, which show the exemplary embodiment by way of
illustration and its best mode. While these exemplary embodiments
are described in sufficient detail to enable those skilled in the
art to practice the invention, it should be understood that other
embodiments may be realized and that logical and mechanical changes
may be made without departing from the spirit and scope of the
invention. Thus, the description herein is presented for purposes
of illustration only and not of limitation. For example, the steps
recited in any of the method or process descriptions may be
executed in any order and are not limited to the order
presented.
[0031] The present invention may be described herein in terms of
functional block components and various processing steps. It should
be appreciated that such functional blocks may be realized by any
number of hardware and/or software components configured to perform
the specified functions. For example, the present invention may
employ various integrated circuit (IC) components (e.g., memory
elements, processing elements, logic elements, look-up tables, and
the like), which may carry out a variety of functions under the
control of one or more microprocessors or other control devices.
Similarly, the software elements of the present invention may be
implemented with any programming or scripting language such as C,
C++, Java, COBOL, assembler, PERL, or the like, with the various
algorithms being implemented with any combination of data
structures, objects, processes, routines or other programming
elements. Further, it should be noted that the present invention
may employ any number of conventional techniques for data
transmission, signaling, data processing, network control, and the
like. Still further, the invention could be used to detect or
prevent security issues with a scripting language, such as
JavaScript, VBScript or the like.
[0032] It should be appreciated that the particular implementations
shown and described herein are illustrative of the invention and
its best mode and are not intended to otherwise limit the scope of
the present invention in any way. Indeed, for the sake of brevity;
conventional wireless data transmission, transmitter, receivers,
modulators, base station, data transmission concepts and other
functional aspects of the systems (and components of the individual
operating components of the systems) may not be described in detail
herein. Furthermore, the connecting lines shown in the various
figures contained herein are intended to represent exemplary
functional relationships and/or physical couplings between the
various elements. It also should be noted that many alternative or
additional functional relationships or physical connections may be
present in a practical electronic transaction or file transmission
system.
[0033] As will be appreciated by one of ordinary skill in the art,
the present invention may be embodied as a method, a data
processing system, a device for data processing, and/or a computer
program product. Accordingly, the present invention may take the
form of an entirely software embodiment, an entirely hardware
embodiment, or an embodiment combining aspects of both software and
hardware. Furthermore, the present invention may take the form of a
computer program product on a computer-readable storage medium
having computer-readable program code means embodied in the storage
medium. Any suitable computer-readable storage medium may be
utilized, including hard disks, CD-ROM, optical storage devices,
magnetic storage devices, and/or the like.
[0034] In various embodiments, the invention may comprise, or be
implemented as, a computer system, a computer sub-system, a
computer, an appliance, a workstation, a terminal, a server, a
personal computer (PC), a laptop, an ultra-laptop, a handheld
computer, a personal digital assistant (PDA), a set top box (STB),
a telephone, a mobile telephone, a cellular telephone, a handset, a
wireless access point, a base station, a radio network controller
(RNC), a mobile subscriber center (MSC), a microprocessor, an
integrated circuit such as an application specific integrated
circuit (ASIC), a programmable logic device (PLD), a processor such
as general purpose processor, a digital signal processor (DSP)
and/or a network processor, an interface, an input/output (I/O)
device (e.g., keyboard, mouse, display, printer), a router, a hub,
a gateway, a bridge, a switch, a circuit, a logic gate, a register,
a semiconductor device, a chip, a transistor, or any other device,
machine, tool, equipment, component, or combination thereof.
[0035] To simplify the description of the exemplary embodiment, the
invention is described as pertaining to a MIMO system. However, the
invention is applicable to SISO and DSSS systems and any
multi-dimensional transmission protocol. It will be appreciated
that many applications of the present invention could be
formulated. For example, the system could be used to facilitate any
conventional wireless communication medium, and the like. Further,
it should be appreciated that the network described herein may
include any system for exchanging data or transacting business,
such as the Internet, an intranet, an extranet, WAN, WLAN, WPAN, Ad
hoc Networks, mobile ad hoc networks (MANET), satellite
communications (SATCOM), and/or the like.
[0036] FIG. 1 is an exemplary block diagram of a MIMO system 100
useful with the invention. The exemplary MIMO communication system
100 and its sub-components will be described below when required to
facilitate the description of the present invention. The exemplary
MIMO communication system 100 may be implemented as a wireless
system for the transmission and reception of data across a wireless
channel 111. For example, the MIMO communication system 100 may be
implemented as part of a wireless local area network (LAN) or
metropolitan area network (MAN) system, a cellular telephone
system, or another type of radio or microwave frequency system
incorporating one-way or two-way communications over a range of
distances.
[0037] MIMO communication system 100 may employ various signal
modulation and demodulation techniques, such as single-carrier
frequency domain equalization (SCFDE) or orthogonal frequency
division multiplexing (OFDM), for example. However, throughout this
description, references will be made with respect to a MIMO
communication system or a system including a transmitter and
receiver merely to facilitate the description of the invention.
[0038] MIMO communication system 100 includes a transmitter 102 and
a receiver 104. The transmitter 102 transmits signals across the
channel 111 to the receiver 104. The transmitter 102 may include a
signal splitter for spitting data source 202, and an encoder (not
shown) for encoding the signals. The peak-to-average-power-ratio
(PAPR) of each signal may then be calculated at, for example,
multi-dimensional PAR calculator 204. Multi-dimensional PAPR
calculator may take the randomly produced indexed samples in the
initial population and evaluate the initial population them under a
predetermined criterion. If the initial population of indexed
samples meets the criteria, multi-dimensional PAPR calculator 204
may generate a next generation population of indexes for further
processing. If the initial population of sampled indexes does not
meet the criteria, then the next generation indexes are used to
generate a next population of sampled indexes which are constrained
by the mapping of the PAPR vector of the selected indexed samples
onto the fitness function. The next generation of indexes is
therefore constrained by the fitness function to ensure that the
next generation samples are reduced over the initial population.
Each signal may then be modulated 103, then spatially mapped at
spatial mapper 207 prior to being transmitted to the receiver 104
by antenna 218a. 218b, and 218n. Such signals may alternatively be
referred to collectively as a "data source," "data," "signals,"
"information sequence," and/or "data signals."
[0039] The signal is received at the receiver antenna 326a, 326b,
and/or 326n and MIMO equalizer 211 receives the signal. MIMO
equalizer 211 equalizes any inter-channel interference and the
mixed signals, typically received from more than one transmit
antenna. The receiver 104 may include a demodulator 105a, 105b,
105c, which receives the received signals from MIMO equalizer 211.
Demodulator 105a, 105b, 105c may demodulate the signals and provide
the signals to decoder 320a, 320b, 320c. Decoder 320a, 320b, 320c
typically combines and decodes the demodulated signals from the
demodulator 105a, 105b, 105c. In this regard, the decoder 320
typically recovers the original signals that were provided by the
data source 202. As depicted in FIG. 1, the original signals
recovered by the decoder 320a, 320b, 320c may be merged and
transmitted to a connected data sink 107, Data sink 107 may include
one or more devices configured to utilize or process the recovered
signals.
[0040] FIG. 2 depicts an example of the signal processing performed
for preparing a data signal (e.g., data source 202) for PAPR
optimization. During signal processing, a data signal 202 (data
source 202) is sampled. The samples may also be sequentially
indexed. Periods of samples may be organized into groups,
collections, segments or the like. By repeating the process of FIG.
2, a population of indexed samples may be generated. The first
instance of sampling may serve as an initial population for
evaluation and optimization of a signal characteristic, such as the
peak-to-average-power-ratio, as will be described more fully. In
the exemplary embodiments discussed herein, to facilitate
understanding, the group of samples is described as "segment,"
"indexed segment," "indexed samples" interchangeably.
[0041] Step 260 teaches that data signal 202 may be sampled into a
signal segment 265, of length m samples, which may be indexed
{1:m}. At step 270, a first segment portion 275 of length k samples
may be determined from indexed samples 1 through k where the
samples are taken from signal segment 265. Similarly, at step 280,
a second portion of segment 265 (second segment portion 285) of
length m-k may be generated from indexed samples m-k+1:m samples.
Finally, at step 290, an augmented segment 295 may be generated.
Augmented segment 295 may be generated by pre-pending second
segment portion 285 to signal segment 265 (cyclic-prefix), and
further appending section 285 to signal segment 265
(cyclic-suffix). As such, each augmented segment may include (m+2k)
total indexed samples.
[0042] In a particular example, multiple augmented segments may be
generated from data signal 202. Additionally, multiple "augmented
segment streams" may be generated from each "augmented segment."
The augmented segment streams may be generated using the method of
FIG. 2 described above. In this context, an augmented segment
stream may be samples taken from data signal 202. Segment 265 may
be used for forming the augmented segment. Signal segment 265 may
be comprised of indexed samples that may be ordinally shifted from
a first indexed sample (e.g., sample 1) to a different indexed
sample x.noteq.1. As is understood by one skilled in the art, an
augmented segment stream may be an alternate representation of the
augmented segment from which it is generated using a cyclic time
shift, for example. For example, a first augmented segment stream
generated using the processing of FIG. 2 may be an alternate
representation of augmented segment 295. Further still, it should
be noted that where an augmented segment is used to generate
multiple augmented segment streams, each of the augmented segment
streams may be an alternate representation of the augmented
segmented from which it is generated. Additionally, each aggregate
waveform is constructed of indexed samples mutually exclusive from
the indexed samples used for constructing other aggregated
waveforms in the collection. More particularly, the indexed samples
used to construct an augmented segment are unique.
[0043] To facilitate description of augmented segments and
augmented segment streams, an augmented segment may be described as
augmented segment 1, and a first augmented segment stream of
augmented segment 1 is denoted augmented segmented stream 1-1. A
second augmented segment stream of augmented segment 1 is denoted
augmented segment stream 1-2, and the nth augmented segment stream
of augmented segmented 1 is augmented segment stream 1-nth. Similar
naming convention is used with respect to augmented segment 2,
which may have a first augmented segment stream 2-1, a second
augmented segment stream 2-2, and an nth augmented segment stream
2-nth.
[0044] As used herein, an "aggregate waveform" may be a combination
of augmented segment streams. The augmented segment streams forming
the aggregate waveform may be generated from the same augmented
segment, or from multiple augmented segments. FIG. 3 shows the
generation of multiple aggregate waveforms, 1.sup.st AW, 2.sup.nd
AW and nth AW. As is shown, aggregate waveform 1.sup.st AW may
comprised of multiple augmented segment streams. More particularly,
aggregate waveform 1.sup.st AW may be comprised of multiple like
numbered augmented segment streams from the multiple augmented
segments. By "like numbered" what is meant is that all like
numbered augmented segment streams of different augmented segments
are combined to form an aggregate waveform. In some instances,
where an augmented segment does not have a like numbered stream the
aggregated waveform formed may not include the missing like
numbered augmented segment stream.
[0045] The example shown in FIG. 3 is a schematic of a method for
generating an initial population 310 of signal samples In the
instance shown, the initial population consists of aggregate
waveforms, for which the PAPR must be optimized. Initial population
310 may include multiple aggregate waveforms, which may be
considered a collection of aggregate waveforms 310.
[0046] As illustrated in FIG. 3, 1.sup.st AW is constructed by
combining the first streams from each augmented segment generated,
for example, using the method of FIG. 2. Aggregated waveform
1.sup.st AW comprises stream 1 of a first augmented segment (i.e.,
augmented segment stream 1-1) and a stream 1 of a second augmented
segment (i.e., augmented segment stream 2-1). Aggregated waveform
1.sup.st AW may include additional augmented segment streams, such
as, a stream 1 of an n.sup.th augmented segment (i.e., augmented
segmented stream n.sup.th-1).
[0047] The aggregate waveforms 2.sup.nd AW and n.sup.th AW in the
collection of aggregate waveforms 310 are generated similarly to as
what is described with respect to aggregated waveform 1.sup.st AW.
Namely, aggregated waveform 2.sup.nd AW comprises stream 2 of a
first augmented segment (i.e., augmented segment stream 1-2) and a
stream 2 of a second augmented segment (i.e., augmented segment
stream 2-2). Aggregated waveform 2.sup.nd AW may include additional
augmented segment streams, such as, a stream 2 of an n.sup.th
augmented segment (i.e., augmented segmented stream
n.sup.th-2).
[0048] Further, an aggregated waveform n.sup.th AW comprises stream
n.sup.th of a first augmented segment (i.e., augmented segment
stream 1-n.sup.th) and a stream n.sup.th of a second augmented
segment (i.e., augmented segment stream 2-n.sup.th). Aggregated
waveform n.sup.th AW may include additional augmented segment
streams, such as, a like numbered stream of an augmented segment
(i.e., augmented segmented stream n.sup.th-1) in the collection of
aggregate waveforms.
[0049] As noted above, collection of aggregated waveforms 310 may
be viewed an initial population 310 of sampled data signals for
which a population characteristic, such as PAPR, is evaluated. The
initial population may be processed or manipulated to prepare it
for later processing, such as, PAPR optimization. Referring again
to FIG. 3, the PAPR of the initial population 310 may be calculated
by evaluating the PAPR of the aggregate waveforms in the collection
of aggregate waveforms 310. For example, the aggregate waveform
1.sup.st AW PAPR may be calculated from the combined PAPRs of each
augmented segment stream comprising the aggregated waveform
1.sup.st AW. Specifically, the PAPR of aggregated waveform 1.sup.st
AW may be calculated from the PAPRs of augmented segment stream
1-1, augmented segment 2-1, and augmented segment stream
n.sup.th-1, etc. The PAPR of each aggregated waveform (e.g., 2 AW
PAPR, nth AW PAPR) in the collection is likewise calculated.
[0050] The PAPRs for the different aggregated waveforms may be
calculated using separate dedicated PAPR calculators 320. FIG. 3
depicts a PAPR #1 calculator for calculating PAPR of 1.sup.st AW.
PAPR #1 provides the PAPR for 1.sup.st AW to be further processed
at, for example a PAPR comparator and optimizing process 330.
Similarly, PAPR #2 calculator provides the PAPR for 2.sup.nd AW to
be further processed, and PAPR #n.sup.th calculator provides the
PAPR for n.sup.th AW to be further processed. During processing,
the PAPRs of each aggregate waveform are evaluated. The PAPRs is
optimized prior to transmitting the aggregate waveform to a
receiver.
[0051] In one aspect, the present invention teaches a system and
method for controlling multi-dimensional
peak-to-average-power-ratio resulting from combining multiple
augmented segments streams. The methods found in the prior art are
deficient in that prior PAPR methods are not guided by constraints.
For example, prior methods only evaluate new populations in without
guidance, such that the next random indexing is not assured to have
a reduced PAPR.
[0052] In another aspect, the present invention makes use of the
indexes for samples in the initial population 310 to select the
indexes for a next generation of aggregated waveforms with a
reduced PAPR. What "next generation" may refer to are the
collections, groups, segments of samples generated based on any
prior "parent" or "initial" population. For example, a next
generation of aggregate waveforms may be generated based on
information related to the parent aggregated waveforms from the
initial population. In an exemplary embodiment of the invention,
the samples that create the initial population and the next
generation population may be identified by their corresponding
indexes. The samples form in the next generation may be less in
number or in value than the samples forming the initial or parent
population. What this may mean is the next generation indexes are a
subset of the indexes for the initial population samples. Thus, the
samples corresponding to the next generation indexes are a subset
of the samples in the initial population. In one exemplary
embodiment, the next generation indexes are used to identify the
samples in the next generation aggregated waveforms with reduced
PAPR over the aggregated waveforms generated from the initial
population.
[0053] FIG. 4 is a block diagram of an exemplary method for
generating the next generation indexes in accordance with the
present invention. In one particular embodiment, only the indexes
related to a single aggregate waveform are considered when
generating the next generation indexes. For example, when the PAPRs
related to multiple aggregate waveforms are evaluated, the indexed
samples related to the aggregate waveform having the highest PAPR
value are the basis for forming the next generation indexes. For
ease in understanding, we will refer to the indexes related to the
aggregated waveform with the suitable PAPR as the set of
"intermediate indexes."
[0054] The initial population of indexes 400 consists of all
indexes related to each aggregated waveform in the population. The
initial population of indexes 400 may be organized according to the
aggregated waveforms included in the population. The PAPR of each
aggregate waveform is evaluated to determine which aggregate
waveform has the highest PAPR (step 410). The indexes forming the
selected aggregated waveform make up the intermediate indexes at
step 420.
[0055] The intermediate indexes may then be subjected to further
processing (step 430). The additional processing may mean the
intermediate indexes are subjected to a genetic algorithm and/or
fitness function for producing a fitness value. In this context, a
fitness value serve considered a constraint upon the processing at
step 430. For example, typical constraints that may be placed on
the processing include timing offset errors, frequency offset
errors, amplitude distortions or channel estimation errors as are
found in the prior art. In another example, the processing may mean
that the intermediate indexes undergo integer programming, updated
state vectors such as with control systems described by a Kalman
Filter process. In still another embodiment, the processing at step
430 results in next generation indexes for forming a next
generation population. In yet another embodiment, the processing at
step 430 results in next generation indexes used to identify the
samples for next generation aggregated waveforms having a reduced
PAPR.
[0056] FIG. 5 illustrates an exemplary method for how the next
generation indexes may be used to construct a next generation
population of indexed samples 510. Next generation population 510
is shown comprising next generation aggregate waveforms 1.sup.st NG
AW, 2.sup.nd NG AW, n.sup.th NG AW. Each next generation aggregate
waveform is constructed using the next generation indexes 440. For
example, the next generation indexes are organized such that
samples are identified for each next generation segment. The
identified next generation segments are used to construct augmented
next generation segments using for example the method in FIG. 2.
Alternate representations of the next generation augmented segment
are formed as augmented next generation segment streams. For
example, 1.sup.st NG AW is comprised of next generation segment
stream 1-1, a using similar convention as is discussed above with
respect to initial population 310.
[0057] As is noted, the next generation indexed samples may be a
subset of the indexed samples used to construct the initial
population. In similar manner as was discussed above, each next
generation stream is an indexed shifted representation of next
generation segment. Namely, next generation segment stream 1-2 is a
shifted representation of next generation segment stream 1-1.
Further still, each aggregate waveform is comprised of like
numbered streams from each next generation segment, where the next
generation segment is generated based on intermediate indexes. With
continued reference to FIG. 5, the next generation population
includes multiple next generation segments, the individual streams
of which comprise the next generation aggregate waveforms. At step
520, the target characteristic of each next generation aggregate
waveform is evaluated. For example, the PAPR of each next
generation aggregate waveform is determined. The PAPR of each next
generation aggregate waveform is calculated from the combination of
the PAPRs of each next generation segment stream. Each individual
PAPR is then evaluated against the target value at step 530. The
optimization of the PAPR may be any traditional PAPR optimization
method. As shown in step 530, in one example shown as a fitness
evaluation function computing the PAPR max. The PAPR vectors are
mapped onto the fitness value function. Where the PAPR does not
meet the target value, a further next generation of indexes is
generated with respect to FIG. 4. Particularly, a further next
generation of indexes is generated, where the further generated
indexes correspond to samples that provide an even further reduced
value relative to the target value. In one embodiment, the further
generation indexes correspond to samples with an even further
reduced PAPR.
[0058] Additionally, next generation samples generated based on
said next generation indexes meet at least one regulatory emission
criterion of the governing regulatory body of the country in which
the device operations. Further still, the next generation samples
generated in according to this invention are receivable by a
receiver for demodulating and decoding separately each constituent
protocol stream of said next generation sample without requiring
additional information to be transmitted outside of said protocols.
The next generation sample contains an alternate representation of
a constituent protocol stream component that differs from the
constituent protocol stream in a cyclic time shift, wherein the
alternate representation of the constituent protocol stream is
generated based on a characteristic of the constituent protocol
stream. Further still, the alternate representation of the
constituent protocol stream meets a regulatory emission criterion
of the governing regulatory body (e.g., IEEE, ETSI, etc) of the
country in which a transmitter transmitting said alternate
representation operates.
[0059] FIG. 6 is yet another embodiment of an exemplary method for
generating a next generation population according to the present
invention. At step 610, a signal is received from a data source.
The data source is sampled to generate an initial population of
data points (e.g., step 620). A characteristic of the data signal
is evaluated against a targeted or desired value. In the example
shown, the initial population PAPR is calculated (step 630) and
evaluated against a target PAPR. If the initial population PAPR of
the initial population does not meet the targeted PAPR (step 640),
a fitness value is determined (step 650) that is used to generate
next generation indexes (step 660). The next generation indexes are
computed using the fitness value and an added constraint. The next
generation indexes identify the data source samples forming a
mutation or iteration of the initial population space (step 680).
The next generation population is formed using data source samples
which are nearer to the targeted value. In the example shown, the
next generation PAPR is evaluated against the targeted or desired
PAPR (step 640). The process of generating a next generation
population may be repeated until the generated next generation PAPR
meets the targeted value (step 640). In this context, by meeting
the targeted value, what is meant is that the measured value is
within a predetermined range or tolerance. Once the measured value
is within the predetermined tolerance, the population of data
points (e.g., transmuted population) identified by the indexed
samples meeting the target are forwarded for transmission (step
670). For example, the indexed samples may be forwarded for other
processing for radio frequency transmission (step 690).
[0060] FIG. 7 is a illustrative graph illustrating the
effectiveness of the present invention. The graph shown is an
example using multi-user MIMO code vector. The graph illustrates
the optimization of a particular characteristic, such as PAPR, over
an initial population of data samples. The target PAPR for the MIMO
system is 9 dB. The graph shows MAX PAPR performance for data
samples evaluated over 27 OFDM data symbols. This example shows a
joint optimization with a spatial criterion over the
collective.
[0061] As shown, the MAX PAPR is calculated for data samples at
each data symbol. Graph 702 illustrates techniques which MAX PAPR
over a randomly selected data samples. As can be seen, MAX PAPR
values for graph 702 are unpredictable relative to previously
selected data samples. That is, MAX PAPR values may become closer
to the target value at an OFDM Symbol, but become much farther away
at other later OFDM symbols. Specifically, there are no limitations
placed on which data samples should be successively selected to
ensure that the MAX PAPR calculations of subsequently selected data
samples are nearer to the target PAPR. As shown in graph 702, the
MAX PAPR does not converge to the targeted PAPR of 9. dB (+/-0.5
dB) over 27 OFDM data symbols.
[0062] On the other hand, graph 704 shows the result of operation
of the present invention on the same data signals. As shown, when
the initial population of data samples is optimized under the
present invention, the PAPR of the samples converge to at or near
the target PAPR. The present invention evaluates the MAX PAPR of
the initial population samples at each OFDMS. However, each
subsequent sample set evaluated is further constrained. For
example, the subsequent samples chosen are identified based on the
previously evaluated data samples. As such, the PAPR of
subsequently selected data samples is further reduced with each
iteration of the method of the present invention that is performed.
That is, over the 27 OFDM data signals illustrated, the MAX PAPR
converges or near converges to the targeted PAPR of 9. dB (+/-0.5
dB). That is, subsequent sample sets that are evaluated are
constrained to marginalize the unpredictability of the total MAX
PAPR over the entire population.
[0063] It should be appreciated by one skilled in art, that the
present invention may be utilized in any device that implements the
OFDM encoding scheme. The foregoing description has been directed
to specific embodiments of this invention. It will be apparent;
however, that other variations and modifications may be made to the
described embodiments, with the attainment of some or all of their
advantages. Therefore, it is the object of the appended claims to
cover all such variations and modifications as come within the true
spirit and scope of the invention.
* * * * *