U.S. patent application number 14/610196 was filed with the patent office on 2015-05-21 for compact floating point delta encoding for complex data.
The applicant listed for this patent is Rockstar Consortium US LP. Invention is credited to Edward Ken Kiu Mah, Neil McGowan, Bradley John Morris.
Application Number | 20150139285 14/610196 |
Document ID | / |
Family ID | 38188205 |
Filed Date | 2015-05-21 |
United States Patent
Application |
20150139285 |
Kind Code |
A1 |
McGowan; Neil ; et
al. |
May 21, 2015 |
COMPACT FLOATING POINT DELTA ENCODING FOR COMPLEX DATA
Abstract
A method, apparatus, and system for compression of complex data
signals within a telecommunications base station. The system may
include a transmitter configured to determine a larger value of
either real or imaginary components of a digital complex signal.
The transmitter designates an exponent of an exponential
representation of the larger value as a common exponent to be used
for compressing the digital complex signal. The transmitter also
compresses a digital complex signal into a series of bits by
sharing the common exponent across the real and imaginary
components of the digital complex signal, and transmits the series
of bits onto a physical medium of the communication system. The
system may also include a receiver configured to receive the series
of bits from the physical medium, and to expand the series of bits
to reconstitute the digital complex signal by again sharing the
common exponent across the real and imaginary components of the
digital complex signal.
Inventors: |
McGowan; Neil; (Stittsville,
CA) ; Morris; Bradley John; (Ottawa, CA) ;
Mah; Edward Ken Kiu; (Nepean, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Rockstar Consortium US LP |
Plano |
TX |
US |
|
|
Family ID: |
38188205 |
Appl. No.: |
14/610196 |
Filed: |
January 30, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
11303990 |
Dec 19, 2005 |
8972359 |
|
|
14610196 |
|
|
|
|
Current U.S.
Class: |
375/219 |
Current CPC
Class: |
H04W 88/08 20130101;
H03M 7/30 20130101; H04L 1/0009 20130101; H04L 1/0028 20130101 |
Class at
Publication: |
375/219 |
International
Class: |
H04L 1/00 20060101
H04L001/00; H04W 88/08 20060101 H04W088/08; H03M 7/30 20060101
H03M007/30 |
Claims
1. A communication system, comprising: a transmitter configured to:
determine a larger value of either real or imaginary components of
a digital complex signal; designate an exponent of an exponential
representation of the larger value as a common exponent to be used
for compressing the digital complex signal; compress the digital
complex signal into a series of bits by sharing the common exponent
across the real and imaginary components of the digital complex
signal; and transmit the series of bits onto a physical medium of
the communication system; and a receiver configured to: receive the
series of bits from the physical medium; and expand the series of
bits to reconstitute the digital complex signal by again sharing
the common exponent across the real and imaginary components of the
digital complex signal.
2. The system of claim 1, wherein the transmitter is configured to
compress the digital complex signal into a series of bits by
sharing the common exponent across the real and imaginary
components of the digital complex signal and delta-averaging.
3. The system of claim 2, wherein the transmitter is configured to
compress the digital complex signal into a series of bits by
sharing the common exponent across the real and imaginary
components of the digital complex signal, delta-averaging, and
clipping.
4. The system of claim 1, wherein the receiver is configured to
expand the series of bits by sharing the common exponent across the
real and imaginary components of the digital complex signal and
delta-averaging.
5. The system of claim 4, wherein the receiver is configured to
expand the series of bits by sharing the common exponent across the
real and imaginary components of the digital complex signal,
delta-averaging, and clipping.
6. The system of claim 1, comprising the physical medium of the
communication system.
7. A communication system, comprising a transmitter configured to:
determine a larger value of either real or imaginary components of
a digital complex signal; designate an exponent of an exponential
representation of the larger value as a common exponent to be used
for compressing the digital complex signal; compress the digital
complex signal into a series of bits by sharing the common exponent
across the real and imaginary components of the digital complex
signal; and transmit the series of bits onto a physical medium of
the communication system.
8. The system of claim 7, wherein the transmitter is configured to
compress the digital complex signal into a series of bits by
sharing the common exponent across the real and imaginary
components of the digital complex signal and delta-averaging.
9. The system of claim 8, wherein the transmitter is configured to
compress the digital complex signal into a series of bits by
sharing the common exponent across the real and imaginary
components of the digital complex signal, delta-averaging, and
clipping.
10. A communication system, comprising a receiver configured to:
receive a series of bits from a physical medium; and expand the
series of bits to reconstitute a digital complex signal by sharing
a common exponent across real and imaginary components of the
complex digital signal, the common exponent having been determined
by determining a larger value of either real or imaginary
components of the digital complex signal and designating an
exponent of an exponential representation of the larger value as a
common value, and the digital complex signal having been compressed
into the series of bits by sharing the common exponents across the
real and imaginary components of the digital complex signal.
11. The system of claim 10, wherein the receiver is configured to
expand the series of bits by sharing the common exponent across the
real and imaginary components of the digital complex signal, and
delta-averaging.
12. The system of claim 11, wherein the receiver is configured to
expand the series of bits by sharing the common exponent across the
real and imaginary components of the digital complex signal,
delta-averaging, and clipping.
Description
[0001] This application is a Continuation application of co-pending
U.S. patent application Ser. No. 11/303,990, entitled COMPACT
FLOATING POINT DELTA ENCLODING FOR COMPLEX DATA, filed Dec. 19,
2005, the disclosure of which is hereby incorporated by reference
in its entirety.
FIELD OF THE INVENTION
[0002] The present invention relates generally to data compression.
More particularly, the present invention relates to compression of
complex signals within telecommunications.
BACKGROUND OF THE INVENTION
[0003] Within the field of telecommunications, the rapid transfer
of data is often degraded because of the inherent difficulties
associated with moving a large amount of data over a given period
of time. Compressing complex signals embodying such large amounts
of data enables an increase to the amount of data moved over the
same amount of time. Such data compression is the process of
encoding information using fewer bits than a more direct (i.e.,
linear) representation would use. Data compression is implemented
via the use of specific encoding schemes considered well known in
the art such as, but not limited to, linear encoding, exponential
encoding, and delta encoding. Data compression takes advantage of
statistical redundancy found within most real-world data. As with
any form of communication, compressed data communication only
functions when both sender and receiver understand the encoding
scheme. This typically requires an encoding mechanism and a
decoding mechanism appropriately located within the communications
link somewhere in the data path.
[0004] While data compression is often possible in
telecommunications, some loss of signal fidelity inevitably occurs.
Such signal losses using data compression are tolerated in view of
the desirable reduction in costly resources such as disk space or
connection bandwidth. Some data compression methods are reversible
so that the original data can be reconstructed in their entirety
(i.e., lossless data compression). Other such data compression
methods accept some loss of data in order to achieve higher
compression (i.e., lossy data compression). However, most data
compression methods often also require significant information
processing power that can also be resource intensive. Accordingly,
designing any given data compression scheme will involve trade-offs
among various factors including, but not limited to, compression
capability, any amount of introduced distortion, delay constraints,
and computational resource requirements.
[0005] It is, therefore, desirable to provide an optimized method
and apparatus for data compression within telecommunications that
reduces undesirable trade-offs.
SUMMARY OF THE INVENTION
[0006] It is an object of the present invention to obviate or
mitigate at least one disadvantage of previous data compression
methodologies.
[0007] In a first aspect, the present invention provides a method
of bit conversion of a digital complex signal transmitting over a
physical medium, the method including: receiving a digital complex
signal; compressing the digital complex signal into a series of
bits by sharing a common exponent across real and imaginary
components of the complex signal; transmitting the series of bits
across a physical medium; and expanding the series of bits to
reconstitute the digital complex signal by again sharing the common
exponent across the real and imaginary components of the complex
signal.
[0008] In a further aspect, there is provided a method of bit
conversion of a digital complex signal transmitting over a physical
medium, the method including: receiving a digital complex signal;
compressing the digital complex signal into a series of bits using
linear encoding in combination with delta-averaging; transmitting
the series of bits across a physical medium; and expanding the
series of bits to reconstitute the digital complex signal by using
linear decoding in combination with delta-averaging.
[0009] In still a further aspect, the present invention provides a
method of bit conversion of a digital signal transmitting over a
physical medium, the method including: receiving a digital signal;
compressing the digital signal into a series of bits using encoding
with delta-averaging; transmitting the series of bits across a
physical medium; and expanding the series of bits to reconstitute
the digital complex signal by using decoding with
delta-averaging.
[0010] In yet a further aspect, the present invention provides an
apparatus for encoding a digital complex signal transmitted over a
physical medium, the apparatus including: a compression module
compressing a digital complex signal into a series of bits by
sharing a common exponent across real and imaginary components of
said complex signal, the common exponent being determined by the
compression module as an exponent of an exponential representation
of a larger value of either the real or imaginary components.
[0011] In another aspect, the present invention provides an
apparatus for decoding an encoded digital complex signal
transmitted over a physical medium, the apparatus including: an
expansion module expanding a series of bits forming an encoded form
of a digital complex signal to reconstitute the digital complex
signal by sharing a common exponent across real and imaginary
components of the complex signal, the common exponent being
determined by the expansion module as an exponent of an exponential
representation of a larger value of either the real or imaginary
components.
[0012] In still another aspect, the present invention provides an
apparatus for encoding a digital complex signal transmitted over a
physical medium, the apparatus including: a compression module
compressing a digital complex signal into a series of bits using
linear encoding in combination with delta-averaging.
[0013] In yet still another aspect, the present invention provides
an apparatus for decoding a digital complex signal transmitted over
a physical medium, the apparatus including: an expansion module
expanding a series of bits forming an encoded form of a digital
complex signal to reconstitute the digital complex signal by using
linear encoding in combination with delta-averaging.
[0014] In again a further aspect, the present invention provides an
apparatus for encoding a digital signal transmitted over a physical
medium, the apparatus including: a compression module compressing a
digital complex signal into a series of bits by using encoding with
delta-averaging.
[0015] In still again a further aspect, the present invention
provides an apparatus for decoding a digital signal transmitted
over a physical medium, the apparatus including: an expansion
module expanding the series of bits to reconstitute the digital
complex signal by using decoding with delta-averaging.
[0016] Other aspects and features of the present invention will
become apparent to those ordinarily skilled in the art upon review
of the following description of specific embodiments of the
invention in conjunction with the accompanying figures.
BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Embodiments of the present invention will now be described,
by way of example only, with reference to the attached Figures,
wherein:
[0018] FIG. 1 is a graphical comparison of output signal to noise
ratio (SNR) for different 10-bit quantization formats.
[0019] FIG. 2 is a graphical comparison of output SNR for different
5-bit quantization formats.
DETAILED DESCRIPTION
[0020] Generally, the present invention provides a method and
apparatus for compression of complex data signals--i.e., digital
discrete time complex signals. The invention includes a method of
representing a sample of a complex value discrete time signal using
2(L-N)-S mantissa bits and 2N+S exponent bits to realize peak
output SNR over a wider dynamic range compared to a conventional
L-bit uniform quantization format. The improvement in dynamic range
and peak output SNR is achieved without increasing the average
number of data bits per sample and with relatively simple
computational effort. The resultant SNR is dependent upon the value
of L and power spectrum of the signal.
[0021] Within a telecommunications network, the present invention
is described for purposes of illustration as residing within an
intermediate device between the radio and modem of a typical base
station. Such intermediate device could conventionally provide
routing and/or signal processing typically found between the radio
and modem (or multiple radios and modems) and also include a module
incorporating the present invention. Such module could be in the
form of hardware such as an application specific integrated circuit
(ASIC) or field programmable gate array (FPGA). Alternatively, such
module may be an encoder/decoder device that implements the present
invention in terms of software. In terms of wireless
telecommunications, the present invention therefore provides a
reasonably efficient compressed bit stream within base station
components where such compressed bit stream represents wireless
communication signals between a base station and mobile stations
over the air.
[0022] It should be understood that such compressed bit stream is
of course particularly advantageous when the modem(s) and radio(s)
within any given base station are separated by any significant
distance (i.e. not co-located) or where data transport is a limited
or costly resource. The present invention is intended for data
communications within some physical medium including, but not
limited to, optical fiber, copper wire, or printed circuit board
(PCB) traces typical of smaller distances such as between adjacent
radio and modem modules within a base station. While the present
invention is intended for intra-module communication within a base
station where the present inventive data compression is applied
within an intermediate module, it should be readily apparent to one
of ordinary skill in the art that the present invention is not
module dependent. That is to say, the compression methodology of
the present invention for conversion of complex signals to minimize
bit rates is not dependent upon any specific module configuration
or physical implementation.
[0023] The present invention is described in terms of compact
floating point delta encoding/decoding and utilizes a combination
of innovative data compression mechanisms to reduce the number of
required bits to represent a signal. Effectively, the present
invention represents a zero delay compression scheme with
substantially reduced sampling requirements. Each data compression
mechanism has value taken alone, though particularly advantageous
cumulative benefits are possible when taken together. These data
compression mechanisms include exponential encoding/decoding with a
shared exponent between the real and imaginary components of a
complex signal, delta-average encoding/decoding, and clipping.
Compact floating point delta encoding/decoding in accordance with
the present invention involves representing a complex signal in
terms of its real and imaginary components.
[0024] In terms of the encoding side in accordance with the present
invention, let X={x.sub.k} denote a complex value discrete time
signal indexed by k. Let {M.sub.1,k, M.sub.Q,k, E.sub.k,
.DELTA.M.sub.1,k, .DELTA.M.sub.Q,k, .DELTA.E.sub.k} denote the
compact floating point delta encoded representation of X. Let
Y={y.sub.k} denote the numerical value associated with this encoded
representation of X. The value of y.sub.k is defined by Equation 1
(Eq. 1).
y k = { ( M l , k + j M Q , k ) 2 E k , k even ( .DELTA. M l , k +
j M Q , k ) 2 .DELTA. E k , k odd ( Eq . 1 ) ##EQU00001##
[0025] where
[0026] M.sub.1,k is the (L-N)-bit mantissa for the real component
of y.sub.k|.sub.k even,
[0027] M.sub.Q,k is the (L-N)-bit mantissa for the imaginary
component of y.sub.k|.sub.k even,
[0028] E.sub.k is the (2N+S)-bit exponent for y.sub.k|.sub.k
even,
[0029] .DELTA.M.sub.1,k is the (L-N-S)-bit mantissa for the real
component of y.sub.k|.sub.k odd,
[0030] .DELTA.M.sub.Q,k is the (L-N-S)-bit mantissa for the
imaginary component of y.sub.k|.sub.k odd,
[0031] .DELTA.E.sub.k is the (2N+S)-bit exponent for y.sub.k|.sub.k
odd, and
[0032] j equals {square root over (-1)}.
[0033] The samples y.sub.k|.sub.k odd are labeled the delta samples
whereas the samples y.sub.k|.sub.k even are labeled the non-delta
samples. Note that the association of delta samples with odd values
of k is arbitrary. Also, the association of positive valued
exponents with upward scaling is arbitrary. The values for
M.sub.1,k, M.sub.Q,k, and E.sub.k are chosen by the encoder to
minimize the absolute error |x.sub.k-y.sub.k| for all even values
of k. The values for .DELTA.M.sub.1,k, .DELTA.M.sub.Q,k, and
.DELTA.E.sub.k are chosen by the encoder to minimize the
quantity
x k - f n , S ( y k - 1 + y k + 1 2 ) ##EQU00002##
for all odd values of k where the function f.sub.n,S(.cndot.) is
defined by Equation 2 (Eq. 2).
f n , S ( u ) = clip n , S ( Re { u } ) + j clip n , S ( Im { u } )
( Eq . 2 ) clip n , S ( v ) = { 2 n - 2 - S , v > 2 n - 2 - S -
2 n + 2 - S , v < - 2 n + 2 - S v , otherwise ( Eq . 3 )
##EQU00003##
[0034] The parameter n is the number of integer bits in the
full-scale representation of Y. For example, n=0 for signed
fractional numbers with a range [-1, +1) whereas n=L-1 for signed
integers with a range [-2.sup.L-1, 2.sup.L-1). The parameter S is
the difference in number of mantissa bits between non-delta and
delta samples per real or imaginary component.
[0035] Having a common exponent for the real and imaginary
component of Y halves the number of bits required to represent the
exponent information compared to case of having separate exponents.
The SNR penalty arising from having a common exponent is small due
to the fact that the absolute error |x.sub.k-y.sub.k| is dominated
by the larger of Re{x.sub.k-y.sub.k} and Im{x.sub.k-y.sub.k} and
the encoder chooses the values for E.sub.k and .DELTA.E.sub.k to
minimize the dominant error term. The gain in terms of number of
bits saved from having a common exponent more than offsets the
slight degradation in SNR.
[0036] The average of neighboring samples in the computation of
.DELTA.M.sub.1,k, .DELTA.M.sub.Q,k, and .DELTA.E.sub.k is used as
the reference point for computing the delta sample. The statistical
property that adjacent samples of X tend to be correlated is used
to reduce the variance of the delta sample. The benefit of the
latter is that fewer mantissa bits are required to encode the odd
samples of Y for a given SNR.
[0037] The parameter S corresponds to the bit saving that is
realized via delta averaging. By applying the bit saving to
increasing the number of exponent bits, the dynamic range of the
exponential format is increased by 20 log.sub.10
2(2.sup.2N+S-2.sup.2N) dB. Alternatively, the same number of
mantissa bits could be used to increase the SNR of the odd samples
of Y.
[0038] Since y.sub.k|.sub.k even is known to both the encoder and
decoder with exactitude, using y.sub.k|.sub.k even rather than
x.sub.k|.sub.k even in the computation of delta samples ensures
both encoder and decoder use identical reference points for
computing the delta samples. This improves the SNR of Y.
[0039] The clipping operation in the computation of
.DELTA.M.sub.1,k, .DELTA.M.sub.Q,k, and .DELTA.E.sub.k ensures that
the range spanned by the delta encoding is confined within the
range spanned by the signal X. This maximizes the useful range of
the signed delta samples which in turn minimizes the absolute error
|x.sub.k-y.sub.k| for all odd values of k. The result is an
improvement in SNR of the encoded signal.
[0040] Note that the mantissa values M.sub.1,k, M.sub.Q,k,
.DELTA.M.sub.1,k, and .DELTA.M.sub.Q,k are least significant bits
(LSB) aligned with respect to their fixed-point precision. This
implies that .DELTA.M.sub.1,k and .DELTA.M.sub.Q,k have S fewer
most significant bits (MSBs) than M.sub.1,k and M.sub.Q,k
respectively. In all, a total of 4L bits are needed to represent a
non-delta sample and delta sample pair. This corresponds to an
average of L bits per sample per real or imaginary component.
[0041] The values of M.sub.1,k, M.sub.Q,k, E.sub.k,
.DELTA.M.sub.1,k, .DELTA.M.sub.Q,k, and .DELTA.E.sub.k constitute
the output of the compact floating point delta encoder. The encoded
data is used for transmission in lieu of un-encoded data. The
formatting of the encoded data for the purposes of data transport
is arbitrary.
[0042] In terms of the decoding side in accordance with the present
invention, the compact floating point delta decoder constructs an
estimate {circumflex over (X)}={{circumflex over (x)}.sub.k} of the
original signal X via Equation 4 (Eq. 4).
x ^ k = { y k , k even y k + f n , S ( y k - 1 + y k + 1 2 ) , k
odd ( Eq . 4 ) ##EQU00004##
[0043] In the above, y.sub.k is derived from the received data
using Equation 1.
[0044] In the case of X being a real value signal, the present
invention as described still applies with M.sub.Q,k and
.DELTA.M.sub.Q,k set to zero. Hence, M.sub.Q,k and .DELTA.M.sub.Q,k
need not be sent to the decoder.
[0045] In the case of linear (i.e. non-exponential) encoding, the
present invention as described still applies with E.sub.k and
.DELTA.E.sub.k set to zero. Hence, E.sub.k and .DELTA.E.sub.k need
not be sent to the decoder.
[0046] In the case of non-delta average encoding, the odd samples
are processed in the same manner as the even samples. Non-delta
average encoding may be preferable for applications in which the
signal X has very low correlation between adjacent samples.
[0047] The performance of the compact floating point delta codec in
accordance with the present invention is assessed in terms of the
output SNR that is realized at a given input signal level. The
power of the input signal to the encoder normalized relative to
full-scale power is given by Equation 5 (Eq. 5).
P norm = E [ X 2 ] 2 2 n + 1 . ( Eq . 5 ) ##EQU00005##
[0048] Where E[.cndot.] is the expectation operator, the SNR of the
output signal from the decoder is computed as shown in Equation 6.
(Eq. 6).
SNR = E [ X X ^ - X 2 ] ( Eq . 6 ) ##EQU00006##
[0049] By way of example, an example system is discussed in terms
of application of the present invention to a code division
multiplexing (CDMA) system. However, it should be readily
understood that any system including a complex signal such as, but
not limited to orthogonal frequency division multiplexing (OFDM) or
any similar system can benefit by use of the present invention.
Accordingly, an example system is herein considered in which the
power spectral density function of X is described by the magnitude
squared of the discrete Fourier transform of the reference transmit
filter coefficients for Spreading Rate 1 in the CDMA standard,
TIA/EIA/IS-2000.2B, Physical Layer Standard for cdma2000 Spread
Spectrum Systems. The sampling rate is assumed to be twice the chip
rate for CDMA.
[0050] With reference to FIG. 1, a graphical comparison of a
simulated output SNR for different 10-bit quantization formats is
shown. The plot of SNR versus P.sub.norm for 9E3.DELTA. encoded
signals is shown. The notation 9E3.DELTA. is used to denote the
format associated with an (L=10, N=1, S=1) encoder. The solid line
graph of 9E3.DELTA. represents encoding in accordance with the
present invention with both the shared exponential and delta
aspects as described above. Here, the SNR is held constant over a
wide range of P.sub.norm which is beneficial to systems such as
OFDM. The SNR curve for a comparable 10-bit floating point
non-delta format, but including the shared exponent aspect, is
denoted as 9E2. With regard to this a comparable 10-bit floating
point non-delta format, the exponential non-delta average format
representation of X is given by
y.sub.k=(M.sub.1,k+jM.sub.Q,k)2.sup.E.sup.k for all values of k. It
should be noted that the number of exponent bits is reduced by one
due to the loss of the free bit that the delta average encoding
provided. For comparison purposes, the SNR curves for 9E3.DELTA.
and 9E2 formats along with a 10-bit uniform quantization (i.e.,
conventional) format are superimposed on the same plot.
[0051] As shown by FIG. 1, the 9E3.DELTA. format provides a 36 dB
increase in dynamic range and a 1.8 dB increase in peak output SNR
compared to a conventional 10-bit uniform quantization format. The
extra exponent bit that is realized using delta encoding enables
the 9E3.DELTA. format to have a 24 dB improvement in dynamic range
compared to 9E2 format.
[0052] With reference to FIG. 2, a graphical comparison of a
simulated output SNR for different 5-bit quantization formats is
shown. Here, the notation 4E3.DELTA. is used to denote the format
associated with an (L=5, N=1, S=1) encoder. The plot of SNR versus
P.sub.norm for 4E3.DELTA. encoded signals is shown. Similar to the
graph of FIG. 1, the SNR curves for a comparable 5-bit floating
point non-delta format, denoted as 4E2, and a 5-bit uniform
quantization format are superimposed on the same plot. The
4E3.DELTA. format provides a 35 dB increase in dynamic range
compared to conventional 5-bit uniform quantization. Although there
is a reduction in 1.2 dB in peak output SNR, the input single level
range over which 5-bit uniform quantization outperforms the
4E3.DELTA. format is limited to a span of 3.3 dB. When averaged
over a wide input signal range, the 4E3.DELTA. format outperforms
5-bit uniform quantization. The extra exponent bit that is realized
using delta encoding enables the 4E3.DELTA. format to have a 24 dB
improvement in dynamic range compared to 4E2 format.
[0053] The above-described embodiments of the present invention are
intended to be examples only. Alterations, modifications and
variations may be effected to the particular embodiments by those
of skill in the art without departing from the scope of the
invention, which is defined solely by the claims appended
hereto.
* * * * *