Methodology and method and appartus for signaling with capacity optimized constellations

• US 8,270,511 B2
• Filed: 05/31/2011
• Issued: 09/18/2012
• Est. Priority Date: 06/05/2007
• Status: Active Grant

• Current Assignee: Constellation Designs, LLC (SoftBank Group Corp.)
• Original Assignee: Constellations Designs, Inc.
• Inventors: Barsoum, Maged F., Jones, Christopher R.
• Primary Examiner(s): Bocure, Tesfaldet
• Application Number:
  US13/118,921
• Publication Number:
  US 20110228869A1
• Time in Patent Office: 476 Days
• Field of Search: 375259-262, 375/268, 375/269, 375/295, 375/298, 375/279, 375/280, 375/329, 375/308, 375/316, 375/340, 375/341, 375/332, 332/103, 329/304
• US Class Current: 375/261
• CPC Class Codes: H03M 13/255 with Low Density Parity Check [LDPC] codes
• CPC Class Codes: H03M 13/6325 Error control coding in combination with demodulation
• CPC Class Codes: H04B 15/00 Suppression or limitation of noise or interference by means associated with receiver H04B1/10
• CPC Class Codes: H04B 17/336 Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
• CPC Class Codes: H04L 1/0003 by switching between different modulation schemes
• CPC Class Codes: H04L 1/0009 by adapting the channel coding H04L1/1812 takes precedence
• CPC Class Codes: H04L 27/3405 Modifications of the signal space to increase the efficiency of transmission, e.g. reduction of the bit error rate, bandwidth, or average power
• CPC Class Codes: H04L 27/3483 using a modulation of the constellation points
• CPC Class Codes: H04L 27/3809 Amplitude regulation arrangements
• CPC Class Codes: H04W 24/02 Arrangements for optimising operational condition
• CPC Class Codes: Y02D 30/50 in wire-line communication networks, e.g. low power modes or reduced link rate

Abstract

Communication systems are described that use geometrically shaped constellations that have increased capacity compared to conventional constellations operating within a similar SNR band. In several embodiments, the geometrically shaped is optimized based upon a capacity measure such as parallel decoding capacity or joint capacity. In many embodiments, a capacity optimized geometrically shaped constellation can be used to replace a conventional constellation as part of a firmware upgrade to transmitters and receivers within a communication system. In a number of embodiments, the geometrically shaped constellation is optimized for an Additive White Gaussian Noise channel or a fading channel.

Claims

1. A digital communication system, comprising:

a transmitter configured to transmit signals to a receiver via a communication channel;

wherein the transmitter, comprises;

a coder configured to receive user bits and output encoded bits at an expanded output encoded bit rate;

a mapper configured to map the encoded bits to symbols in an N-dimensional symbol constellation;

a modulator configured to generate a signal for transmission via the communication channel using symbols generated by the mapper;

wherein the receiver, comprises;

a demodulator configured to demodulate the received signal via the communication channel;

a demapper configured to estimate likelihoods from the demodulated signal;

a decoder that is configured to estimate decoded bits from the likelihoods generated by the demapper; and

wherein the symbol constellation is an N-dimensional capacity optimized geometrically spaced symbol constellation that provides a given capacity at a reduced signal-to-noise ratio compared to an N-dimensional signal constellation that maximizes d_min.

2. The communication system of claim 1, wherein the geometrically spaced symbol constellation is capacity optimized subject to additional constraints.

3. The communication system of claim 1, wherein the geometrically shaped symbol constellation is optimized for capacity using parallel decode capacity.

4. The communication system of claim 1, wherein the geometrically shaped symbol constellation is optimized for capacity using joint capacity.

5. The communication system of claim 1, wherein the code is a Turbo code.

6. The communication system of claim 1, wherein the code is a LDPC code.

7. The communication system of claim 1, wherein the modulation scheme is a QAM scheme.

8. The communication system of claim 1, wherein the modulation scheme is a QPSK scheme.

9. The communication system of claim 1, wherein the channel is an AWGN channel.

10. The communication system of claim 1, wherein the channel is a fading channel.

11. The communication system of claim 1, wherein the constellations points of the geometrically spaced symbol constellation are variable depending on the user rate.

12. The communication system of claim 11, wherein:

the transmitter is configured to modify the rate of the code in order to change the user bit rate of the communication system;

the transmitter is configured to move the constellation points of the symbol constellation used by the mapper based upon the code rate of the coder;

the receiver is configured to receive information concerning code rate changes from the transmitter; and

the receiver is configured to modify the decoder and the constellation used by the demapper in response to receipt of a notification of a change of user bit rate.

13. The communication system of claim 12, wherein:

the receiver is configured to acknowledge receipt of a modification to the code rate and the constellation of the communication system; and

the transmitter is configured to commence transmitting using the new code rate and symbol constellation upon receipt of the acknowledgement from the receiver.

14. The communication system of claim 13, wherein:

a backchannel communication link exists between the transmitter and the receiver;

the receiver is configured to monitor receiver performance and initiate a change in code rate in response to the observed receiver performance;

the receiver is configured to transmit to the transmitter via the backchannel a change in user bit rate; and

both the mapper and the demapper are configured to move the constellation points of the geometrically shaped symbol constellation based upon the change in user bit rate.

15. The communication system of claim 1, wherein the constellations points of the geometrically spaced symbol constellation are variable depending on the channel.

16. The communication system of claim 15, wherein the constellations points of the geometrically spaced symbol constellation are variable depending on the channel SNR.

17. The communication system of claim 16, wherein:

a backchannel communication link exists between the transmitter and the receiver;

the receiver is configured to transmit information to the transmitter from which the transmitter can compute the channel SNR;

the transmitter is configured to transmit to the receiver information indicative of a symbol constellation and a code configuration; and

the demapper is configured to move the constellation points of the geometrically shaped symbol constellation based upon the information received from the transmitter.

18. A method of transmitting bits of user information between a transmitter and a receiver over a communication channel, comprising:

using a coder within the transmitter to encode the bits of user information in accordance with a coding scheme;

using a mapper within the transmitter to map the encoded bits of user information to an N-dimensional symbol constellation, wherein the symbol constellation is an N-dimensional capacity optimized geometrically spaced symbol constellation that provides a given capacity at a reduced signal-to-noise ratio compared to an N-dimensional signal constellation that maximizes d_min;

using a modulator within the transmitter to modulate the symbols in accordance with a modulation scheme;

transmitting the modulated signal via the communication channel using the transmitter;

receiving a modulated signal at the receiver;

using a demodulator within the receiver to demodulate the modulated signal in accordance with the modulation scheme;

using a demapper within the receiver to demap the demodulated signal using the geometrically shaped signal constellation to produce likelihoods; and

decoding the likelihoods using the receiver to obtain an estimate of the decoded bits.

19. A method of selecting the points of an N-dimensional geometrically shaped symbol constellation for use in the mapper of a transmitter and the demapper of a receiver in a communication system using a computing device, comprising:

storing in a memory of the computing device a selected constellation size; and

using the computing device to iteratively optimize the location of the points of the N-dimensional constellation to maximize a capacity measure using the stored constellation size, where the iterative optimization proceeds until a predetermined termination condition is reached that results in an N-dimensional geometrically spaced symbol constellation that provides a given capacity at a reduced signal-to-noise ratio compared to a signal constellation that maximizes d_min.

20. The process of claim 19, wherein the capacity measure is parallel decoding capacity.

21. The process of claim 20, further comprising iteratively optimizing both constellation labels and point locations to maximize parallel decoding capacity.

22. The process of claim 19, wherein the capacity measure is joint capacity.

23. The process of claim 19, wherein the process iterates until a predetermined SNR gain is achieved.

24. The process of claim 23, wherein the predetermined SNR gain is 0.5 db.

25. The process of claim 19, further comprising:

selecting the SNR performance of each optimized constellation as the new SNR at which to optimize the location of the points of the constellation based on the capacity measure in each iteration; and

iterating until the SNR performance obtained by the optimized constellation converges to within a predetermined amount of the SNR performance of the optimized constellation obtained in the previous iteration.

26. The process of claim 19, wherein the initial SNR estimate is the SNR required by a constellation that maximizes d_min to obtained the desired capacity.

27. The process of claim 19, wherein the optimization process is an iterative numerical process that selects the constellation points with the highest measure of capacity.

28. The process of claim 27, wherein the optimization process is subject additional to constraints.

29. The process of claim 28, wherein the additional constraints include one of a constant energy constraint (as in PSK constellations), a peak to average power constraint, or labeling constraints.

30. The process of claim 19, wherein the optimization process yields a geometrically shaped symbol constellation having a suboptimal capacity.

31. The method of claim 19, wherein the constellation points of the optimized constellation are then approximated, quantized or varied slightly.