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Proceedings ArticleDOI

Soft output detection for MIMO systems using binary polar codes

01 Sep 2016-pp 400-404
TL;DR: A small length polar, encoded for a MIMO (Multiple-Input Multiple-Output) systems with soft output MMSE-SIC (Minimum Mean Square Error-Successive Cancellation) detection, is applied to improve the coded performance while reducing the complexity.
Abstract: Polar codes are proven capacity-achieving and are shown to have equivalent or even better finite length performance than turbo/LDPC codes under some improved decoding algorithm over the Additive White Gaussian Noise (AWGN) channels. Polar coding is based on the so-called channel polarization phenomenon induced by a transform over the underlying binary-input channel. The channel polarization is found to be universal in many signal processing problems and is applied to the coded modulation schemes. In this paper, a small length polar, encoded for a MIMO (Multiple-Input Multiple-Output) systems with soft output MMSE-SIC (Minimum Mean Square Error-Successive Cancellation) detection, is applied to improve the coded performance while reducing the complexity. In order to prove this theory, we compare the proposed MMSE-SIC BER to Zero Forcing (ZF) and Maximum Likelihood (ML) by using 2*2 MIMO systems into Rayleigh channel with BPSK (Binary Phase-Shift Keying) modulation. Simulation results show that MMSE-SIC complexity is lower than the two others detections. We show that the performance of the proposed approach using polar code (128, 64) at 10−2 BER (Bit Error Rate) is around 3dB i.e. 0,66% compared to the optimal ML, while ZF performance is the worst.
Citations
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Journal Article
TL;DR: In this paper antenna configuration is used and QPSK modulation is treated here for simulation purpose, and signal-noise ratio (SNR) curve of Constant modulus algorithm(CMA) equalizer exceeds that of ZF, MMSE and ML equalizer.
Abstract: Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing(OFDM) systems have recently emerged as key technology in wireless communication systems for increasing data rate and system performance. The effect of fading and interference can be combated to increase the capacity of the link. MIMO systems uses Multiple Transmit and Multiple Receive antennas which exploit the multipath propagation in rich scattering environment. The matrix channel plays a pivotal role in the throughput of a MIMO link since the modulation, data rate, power allocation and antenna weights are dependent on the channel gain. When data rate is transmitted at high bit rate, the channel impulse response can extend over many symbol periods which leads to Inter-Symbol Interference(ISI). ISI always caused an issue for signal recovery in wireless communication. In order to reduce the complexity of MIMO system, various detection algorithm such as Zero forcing(ZF), Minimum Mean Square Error(MMSE), Maximum Likelihood(ML) and a novel algorithm namely Constant Modulus Algorithm(CMA) are proposed that reduce bit error rate(BER) via spatial multiplexing. QPSK modulation is treated here for simulation purpose.Simulations are done by MatLab that shows BER vs. signal-noise ratio (SNR) curve of Constant modulus algorithm(CMA) equalizer exceeds that of ZF, MMSE and ML equalizer. In this paper antenna configuration is used.

2 citations

Proceedings ArticleDOI
01 Mar 2018
TL;DR: It is shown that the association of the SC decoder with the MMSE-SIC detector can reduce the Bit Error Rate (BER) instead of Believe Propagation (BP) decoding, which has increased the diversity and the ability to correct.
Abstract: The tools of information theory (error correcting codes) are exploited to improve the detection of MIMO channels. In particular, we use the polar codes, which currently represent the first and only code family to reach Shannon's two limits on channel and source coding. Our proposal consists in using a medium-length polar encoding, a detection minimizing the mean squared error by successive interference cancellation (MMSE- SIC) and a Successive Cancellation (SC) decoder.To improve the reliability of the information over the iterations, we added an iterative (turbo-equalization) process between the SC decoder and the MMSE-SIC detector. We have shown that the association of the SC decoder with the MMSE-SIC detector can reduce the Bit Error Rate (BER) instead of Believe Propagation (BP) decoding. This has increased the diversity and the ability to correct.

1 citations


Cites methods from "Soft output detection for MIMO syst..."

  • ...In [6] soft output detector with medium polar length was detailed and a good BER (Bit Error Rate) performances....

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Book ChapterDOI
11 Apr 2017
TL;DR: A concatenation scheme performance, which employs a short polar encoder following to Spatial Time Block Codes (STBC), and an efficient detector for Multiple Input Multiple Output (MIMO) antennas, which adaptively combines Minimum Mean Square Error Successive Interference Canceller together (MMSE-SIC).
Abstract: Polar codes, proposed by Erdal Arikan, have attracted a lot of interest in the field of channel coding for their capacity-achieving trait as well as their low encoding and decoding complexity in order O (NlogN) under successive cancellation (SC) decoder. However, there remains one significant drawback, that is, the error correction performance of short and moderate length polar codes is unsatisfactory, especially when compared with low-density parity check (LDPC) codes and turbo codes. In this paper, we propose a concatenation scheme performance, which employs a short polar encoder following to Spatial Time Block Codes (STBC), and we develop an efficient detector for Multiple Input Multiple Output (MIMO) antennas, which adaptively combines Minimum Mean Square Error Successive Interference Canceller together (MMSE-SIC). We also compared to Maximum Likelihood in the literature and finally present a simulation results in binary input Additive White Gaussian Noise (BI-AWGN) with binary phase shift keying (BPSK) modulation, and we observe that, our proposed concatenation scheme significantly outperforms the Maximum Likelihood performance in the high Signal-to-Noise-Ratio (SNR).

1 citations


Cites background or methods from "Soft output detection for MIMO syst..."

  • ...In [8] a linear filter detection MMSE-SIC using a small polar code, which allowed reducing the complexity while maintaining the BER, performance is presented....

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  • ...The construction of polar codes is based on channel polarization [5, 8]....

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Book ChapterDOI
01 Jan 2018
TL;DR: In this article, a concatenation of small Polar Codes length (N=32) and Space Time Block Code (STBC) is applied to no diversity (SISO), SIMO, MISO and MIMO systems.
Abstract: This paper uses a concatenation of small Polar Codes length (N=32) and Space Time Block Code, this Polar-STBC is applied to no diversity (SISO), SIMO, MISO and MIMO systems. Minimum Mean Square Error using Successive Interference Cancellation (MMSE-SIC) is a soft output used to the receiver in order to improve Bit Error Rate (BER) and finally Successive Cancellation Decoder (SCD) is placed to the decoder in order to improve the BER and Frame Error Rate (FER). Comparison between several STBC without concatenation schemes and this small Polar-STBC shown that the proposed allows minimizing the BER and FER performances.

1 citations


Cites background or methods from "Soft output detection for MIMO syst..."

  • ...If the signal is detected, it is immediately fed back to the linear combining process and its contribution is cancelled from the received signal in the next detection iteration and found the next the minimum MSE as shown [8]....

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  • ...In [8] we proposed propose a linear filter detection MMSE-SIC using a small Polar Code which allowed to reduce the complexity while maintaining the BER performance....

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  • ...The construction of polar codes is based on channel polarization [5, 8]....

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Proceedings ArticleDOI
01 Dec 2019
TL;DR: It is shown that, with finite polynomial complexity time, the proposed SRSC algorithm obtains a better bits error rate performance and requires a lower minimum average received signal to noise ratio to achieve the theoretical spectral efficiency.
Abstract: Due to provable capacity-achieving performance and low encoding and decoding complexity, polar codes have received much attention in recent years. In this paper, polar codes are considered in uplink multiuser massive multiple-input multiple-output (MIMO) system. Large scaled antenas makes the processes of detecting and decoding polar coded signals being difficult at the receiving station. To solve this problem, a successive cancellation based semidefinite relaxation (SRSC) algorithm is proposed to detect as well as decode polar coded M-QAM signals in this system, where the detection process is implemented by likelihood ascent search based further semidefinite relaxation optimization in spatial domain and the decoding process is implemented by further successive cancellation in time domain. Simulation results verify the effectiveness of the proposed SRSC algorithm in massive connections scenarios. It is shown that, with finite polynomial complexity time, the proposed SRSC algorithm obtains a better bits error rate performance and requires a lower minimum average received signal to noise ratio to achieve the theoretical spectral efficiency.
References
More filters
Journal ArticleDOI
Emre Telatar1
01 Nov 1999
TL;DR: In this paper, the authors investigate the use of multiple transmitting and/or receiving antennas for single user communications over the additive Gaussian channel with and without fading, and derive formulas for the capacities and error exponents of such channels, and describe computational procedures to evaluate such formulas.
Abstract: We investigate the use of multiple transmitting and/or receiving antennas for single user communications over the additive Gaussian channel with and without fading. We derive formulas for the capacities and error exponents of such channels, and describe computational procedures to evaluate such formulas. We show that the potential gains of such multi-antenna systems over single-antenna systems is rather large under independenceassumptions for the fades and noises at different receiving antennas.

12,542 citations

Journal ArticleDOI
Gerard J. Foschini1
TL;DR: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver with the aim of leveraging the already highly developed 1-D codec technology.
Abstract: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver. Inventing a codec architecture that can realize a significant portion of the great capacity promised by information theory is essential to a standout long-term position in highly competitive arenas like fixed and indoor wireless. Use (n T , n R ) to express the number of antenna elements at the transmitter and receiver. An (n, n) analysis shows that despite the n received waves interfering randomly, capacity grows linearly with n and is enormous. With n = 8 at 1% outage and 21-dB average SNR at each receiving element, 42 b/s/Hz is achieved. The capacity is more than 40 times that of a (1, 1) system at the same total radiated transmitter power and bandwidth. Moreover, in some applications, n could be much larger than 8. In striving for significant fractions of such huge capacities, the question arises: Can one construct an (n, n) system whose capacity scales linearly with n, using as building blocks n separately coded one-dimensional (1-D) subsystems of equal capacity? With the aim of leveraging the already highly developed 1-D codec technology, this paper reports just such an invention. In this new architecture, signals are layered in space and time as suggested by a tight capacity bound.

6,812 citations


"Soft output detection for MIMO syst..." refers background in this paper

  • ...Therefore a number of suboptimal approaches have been proposed in the literature [5]-[6]....

    [...]

Journal ArticleDOI
Erdal Arikan1
TL;DR: The paper proves that, given any B-DMC W with I(W) > 0 and any target rate R< I( W) there exists a sequence of polar codes {Cfrn;nges1} such that Cfrn has block-length N=2n, rate ges R, and probability of block error under successive cancellation decoding bounded as Pe(N,R) les O(N-1/4) independently of the code rate.
Abstract: A method is proposed, called channel polarization, to construct code sequences that achieve the symmetric capacity I(W) of any given binary-input discrete memoryless channel (B-DMC) W. The symmetric capacity is the highest rate achievable subject to using the input letters of the channel with equal probability. Channel polarization refers to the fact that it is possible to synthesize, out of N independent copies of a given B-DMC W, a second set of N binary-input channels {WN(i)1 les i les N} such that, as N becomes large, the fraction of indices i for which I(WN(i)) is near 1 approaches I(W) and the fraction for which I(WN(i)) is near 0 approaches 1-I(W). The polarized channels {WN(i)} are well-conditioned for channel coding: one need only send data at rate 1 through those with capacity near 1 and at rate 0 through the remaining. Codes constructed on the basis of this idea are called polar codes. The paper proves that, given any B-DMC W with I(W) > 0 and any target rate R< I(W) there exists a sequence of polar codes {Cfrn;nges1} such that Cfrn has block-length N=2n , rate ges R, and probability of block error under successive cancellation decoding bounded as Pe(N,R) les O(N-1/4) independently of the code rate. This performance is achievable by encoders and decoders with complexity O(N logN) for each.

3,554 citations

Journal ArticleDOI
TL;DR: This work provides a simple method to iteratively detect and decode any linear space-time mapping combined with any channel code that can be decoded using so-called "soft" inputs and outputs and shows that excellent performance at very high data rates can be attained with either.
Abstract: Recent advancements in iterative processing of channel codes and the development of turbo codes have allowed the communications industry to achieve near-capacity on a single-antenna Gaussian or fading channel with low complexity. We show how these iterative techniques can also be used to achieve near-capacity on a multiple-antenna system where the receiver knows the channel. Combining iterative processing with multiple-antenna channels is particularly challenging because the channel capacities can be a factor of ten or more higher than their single-antenna counterparts. Using a "list" version of the sphere decoder, we provide a simple method to iteratively detect and decode any linear space-time mapping combined with any channel code that can be decoded using so-called "soft" inputs and outputs. We exemplify our technique by directly transmitting symbols that are coded with a channel code; we show that iterative processing with even this simple scheme can achieve near-capacity. We consider both simple convolutional and powerful turbo channel codes and show that excellent performance at very high data rates can be attained with either. We compare our simulation results with Shannon capacity limits for ergodic multiple-antenna channel.

2,291 citations


"Soft output detection for MIMO syst..." refers background in this paper

  • ...Zero Forcing Equalizer As described by [8]-[12], MIMO channel version of Zero Forcing equalizer is inverted when the signal is at the receiver in order to totally suppress the signal interference from other transmitted symbol data....

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  • ...The ML detector has the desirable property that, under the statistical assumptions on S , it minimizes the probability error [8]...

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Proceedings ArticleDOI
11 Dec 2006
TL;DR: A field-programmable gate array (FPGA) implementation of a new detection algorithm for uncoded multiple input-multiple output (MIMO) systems based on the complex version of the sphere decoder (SD) shows that the algorithm is highly parallelizable and can be fully pipelined.
Abstract: A field-programmable gate array (FPGA) implementation of a new detection algorithm for uncoded multiple input-multiple output (MIMO) systems based on the complex version of the sphere decoder (SD) is presented in this paper. The algorithm overcomes the main drawback of the SD: its variable throughput, depending on the noise level and the channel conditions. Implementation results show that the algorithm is highly parallelizable and can be fully pipelined. This reduces the use of FPGA resources and results in a constant throughput, which is significantly higher than previous SD implementations at a cost of a very small bit error ratio (BER) degradation.

101 citations


"Soft output detection for MIMO syst..." refers background in this paper

  • ...Therefore a number of suboptimal approaches have been proposed in the literature [5]-[6]....

    [...]