Protograph LDPC (P-LDPC) codes and large-scale multiple-input multiple-output (LS-MIMO) are cornerstones of 5G and future wireless systems, thanks to their powerful error-correcting capability and high spectral efficiency. To alleviate the high complexity in signal detection/decoding that dramatically grows with the number of antennas (in the order of tens or even hundreds), low-resolution analog-to-digital converters (ADCs) and joint detection and decoding using factor graph have recently attracted paramount interest. Unlike high-resolution ADCs, by using a small number of bits to quantize the received signal, lowresolution ADCs help reduce the hardware cost and power consumption of the RF circuit of practical LS-MIMO transceivers. Such a very much desirable reduction comes at the cost of additional quantization noise, introduced by low-resolution ADCs. This work aims to provide a unified framework to analyze the impact of the low-resolution ADCs on the performance of P-LDPC codes in practical LS-MIMO systems. It is worth noting that the previous analytical tools that have been used to evaluate the performance of P-LDPC codes do not account for the quantization noise effect of the low-resolution ADCs and the fact that the covariance of quantization noise depends on the fading channels. This article addresses this shortcoming by first leveraging the additive quantization noise model. We then derive the expression of extrinsic information for the belief-propagation LS-MIMO detector. The mutual information functions, which are the core elements of our proposed protograph extrinsic information transfer (PEXIT) algorithm, are analyzed for LS-MIMO communication systems. Our proposed PEXIT algorithm allows us to analyze and predict the impact of the low-resolution ADCs on the performance of P-LDPC codes, considering various input parameters, including the LS-MIMO configuration, the code rate, and the maximum number of decoding iterations, and the code structure. Based on our extensive analytical and simulation results, we found that the performance of 3-bit and 4-bit ADC systems only have a small gap to that of the unquantized systems. Especially when the 5-bit ADC scheme is applied, the performance loss is negligible. This finding sheds light on the practical design of LS-MIMO systems using P-LDPC codes.INDEX TERMS Protograph LDPC codes, large-scale MIMO, joint detection and decoding, PEXIT algorithm, low-resolution ADC.
Protograph low-density parity-check (LDPC) codes and large-scale multi-input multi-output (LS-MIMO) systems have achieved great interest with various practical applications. However, how to effectively evaluate and design protograph LDPC codes for LS-MIMO systems remains a challenging yet critical problem, especially for low-latency applications. To solve that design challenge, the protograph extrinsic information transfer chart (PEXIT) algorithm for LS-MIMO systems, so-called LS-MIMO-PEXIT algorithm, is first derived based on the mutual information functions of messages that are passed on the joint MIMO detection and LDPC decoding graph. The proposed LS-MIMO-PEXIT algorithm plays a vital role in the optimization process of designing new protograph LDPC codes, tailored for LS-MIMO communications systems. Experiment results demonstrate that the analytical results based on the LS-MIMO-PEXIT algorithm are in good agreement with the simulation results under various input constraints, including the coding rate, the number of decoding iterations, and the LS-MIMO configuration. On top of that, the new protograph LDPC codes designed using our LS-MIMO-PEXIT algorithm achieve a coding gain from 0.2 dB at a low coding rate to 0.4 dB at a high coding rate in comparison with the state-of-the-art protograph codes in the literature. Additionally, we incorporate the practical design experience and the theoretical analysis of mutual functions into a two-step procedure to search for protograph LDPC codes that do not have error-floor behavior at frame error rate (FER) or bit error rate (BER) as low as 10 −5 or 10 −7 , respectively. Together with the coding gain, the error-floor-free feature of the proposed protograph LDPC codes is vitally important for future wireless networks where the ultra-reliability is one of the critical requirements. INDEX TERMS Large-scale multiple-input multiple-output (LS-MIMO), protograph low-density paritycheck (LDPC) codes, channel coding, protograph extrinsic information transfer chart, iterative decoding threshold, low latency.
We derive the belief propagation (BP) detector for large-scale multiple-input multiple-out communication systems where the low-resolution analog-to-digital converters (ADCs) are used to save the power and hardware costs. By modeling the quantization noise as an additive noise element, we derive a new expression for the extrinsic information passed from the observation node to the symbol node on the Tanner graph. Furthermore, we study the performance of the BP-based MIMO detector under different low-resolution ADCs and multiple-input multiple-output (MIMO) configurations. The study results show that one can achieve almost the same performance of highresolution MIMO systems with the 5-bit ADC in the worst scenario where the number of transmit antennas M and the number of receive antennas N are equal. In the favorable situation that N > M , for example M = 10 and N = 30, the 3-bit ADC system has the performance that approaches the performance of the high-resolution ADC system.
In this paper, we develop a new algorithm of joint detection and decoding receiver for the large-scale multipleinput multiple-out (LS-MIMO) coded communication systems with low-resolution ADCs. The new algorithm enables us to perform extensive experiments to address the performance and complexity tradeoff issue for LS-MIMO communication systems. Our study results indicate that 4-bit ADC is the best choice to achieve an excellent balance between the transmit power and complexity. Furthermore, the experiments reveal that the LS-MIMO system with 4-bit ADC can approach the performance of the high-resolution LS-MIMO system in the entire range of signal to noise ratio. In the other extreme, the LS-MIMO system with 2-bit ADC suffers 2.2 dB performance loss in terms of transmit power at bit error rate (BER) 10 −6. In all test cases, an extra bit to increase the resolution from 4-bit ADC to 5-bit ADC achieves a tiny fraction of power gain in return.
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