Channel Hardening-Exploiting Message Passing (CHEMP) Receiver in Large-Scale MIMO Systems

In this paper, we propose a MIMO receiver algorithm that exploits {\em channel hardening} that occurs in large MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of the ${\bf H}^H{\bf H}$ matrix become increasingly weaker compared to the diagonal terms as the size of the channel gain matrix ${\bf H}$ increases. Specifically, we propose a message passing detection (MPD) algorithm which works with the real-valued matched filtered received vector (whose signal term becomes ${\bf H}^T{\bf H}{\bf x}$, where ${\bf x}$ is the transmitted vector), and uses a Gaussian approximation on the off-diagonal terms of the ${\bf H}^T{\bf H}$ matrix. We also propose a simple estimation scheme which directly obtains an estimate of ${\bf H}^T{\bf H}$ (instead of an estimate of ${\bf H}$), which is used as an effective channel estimate in the MPD algorithm. We refer to this receiver as the {\em channel hardening-exploiting message passing (CHEMP)} receiver. The proposed CHEMP receiver achieves very good performance in large-scale MIMO systems (e.g., in systems with 16 to 128 uplink users and 128 base station antennas). For the considered large MIMO settings, the complexity of the proposed MPD algorithm is almost the same as or less than that of the minimum mean square error (MMSE) detection. This is because the MPD algorithm does not need a matrix inversion. It also achieves a significantly better performance compared to MMSE and other message passing detection algorithms using MMSE estimate of ${\bf H}$. We also present a convergence analysis of the proposed MPD algorithm. Further, we design optimized irregular low density parity check (LDPC) codes specific to the considered large MIMO channel and the CHEMP receiver through EXIT chart matching. The LDPC codes thus obtained achieve improved coded bit error rate performance compared to off-the-shelf irregular LDPC codes

Simulations of Implementation of Advanced Communication Technologies

Wireless communication systems have seen significant advancements with the introduction of 3G, 4G, and 5G mobile standards. Since the simulation of entire systems is complex and may not allow evaluation of the impact of individual techniques, this thesis presents techniques and results for simulating the performance of advanced signaling techniques used in 3G, 4G, and 5G systems, including Code division multiple access (CDMA), Multiple Input Multiple Output (MIMO) systems, and Low-Density Parity Check (LDPC) codes. One implementation issue that is explored is the use of quantized Analog to Digital Converter (ADC) outputs and their impact on system performance. Code division multiple access (CDMA) is a popular wireless technique, but its effectiveness is limited by factors such as multiple access interference (MAI) and the near far effect (NFE). The joint effect of sampling and quantization on the analog-digital converter (ADC) at the receiver\u27s front end has also been evaluated for different quantization bits. It has been demonstrated that 4 bits is the minimum ADC resolution sensitivity required for a reliable connection for a quantized signal with 3- and 6-dB power levels in noisy and interference-prone environments. The demand for high data rate, reliable transmission, low bit error rate, and maximum transmission with low power has increased in wireless systems. Multiple Input Multiple Output (MIMO) systems with multiple antennas at both the transmitter and receiver side can meet these requirements by exploiting diversity and multipath propagation. The focus of MIMO systems is on improving reliability and maximizing throughput. Performance analysis of single input single output (SISO), single input multiple output (SIMO), multiple input single output (MISO), and MIMO systems is conducted using Alamouti space time block code (STBC) and Maximum Ratio Combining (MRC) technique used for transmit and receive diversity for Rayleigh fading channel under AWGN environment for BPSK and QPSK modulation schemes. Spatial Multiplexing (SM) is used to enhance spectral efficiency without additional bandwidth and power requirements. Minimum mean square error (MMSE) method is used for signal detection at the receiver end due to its low complexity and better performance. The performance of MIMO SM technique is compared for different antenna configurations and modulation schemes, and the MMSE detector is employed at the receiving end. Advanced error correction techniques for channel coding are necessary to meet the demand for Mobile Internet in 5G wireless communications, particularly for the Internet of Things. Low Density Parity Check (LDPC) codes are used for error correction in 5G, offering high coding gain, high throughput, low latency, low power dissipation, low complexity, and rate compatibility. LDPC codes use base matrices of 5G New Radio (NR) for LDPC encoding, and a soft decision decoding algorithm is used for efficient Frame Error Rate (FER) performance. The performance of LDPC codes is assessed using a soft decision decoding layered message passing algorithm, with BPSK modulation and AWGN channel. Furthermore, the effects of quantization on LDPC codes are analyzed for both small and large numbers of quantization bits