Massive multiple-input multiple-output (MIMO) with low-resolution analog-to-digital converters is a rational solution to deal with hardware costs and accomplish optimal energy efficiency. In particular, utilizing 1-bit ADCs is one of the best choices for massive MIMO systems. This paper investigates the performance of the 1-bit ADC in the wireless coded communication systems where the robust channel coding, protograph low-density parity-check code (LDPC), is employed. The investigation reveals that the performance of the conventional 1-bit ADC with the truncation limit of 3-sigma is severely destroyed by the quantization distortion even when the number of antennas increases to 100. The optimized 1-bit ADC, though having substantial performance gain over the conventional one, is also affected by the quantization distortion at high coding rates and low MIMO configurations. Importantly, the investigation results suggest that the protograph LDPC codes should be re-designed to combat the negative effect of the quantization distortion of the 1-bit ADC.
Nowadays, large-scale multiple-input multiple-output (LS-MIMO) with low-resolution analogto-digital converters (ADCs) is a favorable transmission scheme for 5G and beyond wireless networks to reduce the power consumption of the radio frequency chains and to increase the network capacity. This paper derives the joint message-passing detection and decoding algorithm based on the double-layer graph for LS-MIMO communication systems with mixed-ADCs. The new protograph extrinsic information chart (PEXIT) algorithm is developed to analytically evaluate the performance of protograph low-density parity-check code under various mixed-ADC combinations and LS-MIMO configuration scenarios. The simulation results validate the accuracy of the proposed algorithm. Furthermore, our experiments show that the mixed-ADC system can achieve a significant power gain even when only one received antenna is equipped with high-resolution ADCs. It is observed that 4-bit or 5-bit resolution is an optimal choice for the high-resolution receive antennas. Interestingly, mixed-ADC systems with Ternay-ADCs generally provide significant gains at the cost of the increase in the average resolution by a fraction of a bit. There are specific scenarios where the Ternary-ADC-based system outperforms the 1-bit-ADC based system at the same or lower average resolution. In the particular case of 16 × 16 MIMO configuration where the number of low-resolution antennas is N L = 12 and the number of high-resolution antennas is N H = 4, the Ternary-ADC based system can obtain a power gain of about 2 dB at the frame error rate (FER) or bit error rate (BER) level of 10 −5 .
In this paper, we investigate the performance of a large-scale multiple-input multiple-output (LS-MIMO) receiver, which deploys a deep neural network and a low-density paritycheck (LDPC) code for detecting and decoding disturbed signals. The structure of the low-complexity receiver is also proposed. The proposed receiver was tested with different LS-MIMO configurations to reveal the performance and complexity tradeoff. Besides, our investigation shows that the performance gap of the proposed receiver and the conventional one decreases as the number of transmitting and receive antennas increase. In particular, our experiment results show that the proposed lowcomplexity receiver has performance loss of about 1.8 dB and 1.5 dB in 10 × 10 and 32 × 32 LS-MIMO configurations, respectively.
Recently, two emerging research topics are protograph low-density parity-check (P-LDPC) and large-scale multi-input multi-output (LS-MIMO) with low-resolution analog-to-digital (ADC) converters (LS-MIMO-LOW-ADC). In these directions, many research works have proposed 1-bit ADC as a good candidate for LS-MIMO systems in order to save both transmission power and circuit energy dissipation. However, we observed that previously reported P-LDPC codes might not have good performance for LS-MIMO systems with 1-bit ADC. Hence, we perform a re-design of the P-LDPC codes for the above systems in this paper. The new codes demonstrate a good coding gain from 0:3 dB at rate 1/2 to 0:5 dB at rate 2/3 in different LS-MIMO configurations with 1-bit ADC.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.