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• Multiple-Input Multiple-Output (MIMO) is a wireless technology that uses multiple transmitters and receivers to transfer more data at the same time. • A high performance belief propagation detection-decoding algorithm for NB-LDPC MIMO codes with a low complexity approach. • Vertical Shuffle Schedule (VSS) reduces processing latency and therefore introduces greater flexibility into the receiver. • A dynamic approach can detect the closest point to the channel observation without calculating all the candidate symbols in a constellation. MIMO systems exploit multi-path propagation in a rich broadcast environment to improve throughput and performance of digital communication systems. The correspondent demappers require additional computational complexity. In this paper, a new detection-decoding approach based on vertical shuffle scheduling is proposed. Space exploration for the maximum likelihood detection is reduced to a dynamic region that surrounds the received symbol. Thus, a dynamic approach is proposed to detect the closest point of the channel observation without calculating all the candidate symbols in a constellation. In addition, a novel method based on EXIT chart study is proposed to find the sufficient number of neighboring points to search around a local minimum and then compute by recursion their Euclidean distances. Compared to the conventional Maximum Likelihood detector, the proposed algorithm allows a reduction in the computational complexity, in terms of number of multiplication, reaching 98%. The simulation results show that the proposed algorithm outperforms the state-of-the-art algorithms like MMSE, sphere decoding, DBTC and DaVinci codes. [ABSTRACT FROM AUTHOR]

Superposition coding (SC) with successive interference cancellation (SIC) is considered a promising non-orthogonal multiple access (NOMA) technique for improving spectral efficiency recently. In contrast, the residual interference after SIC at the receiver severely degrades the BER performance when applied in underwater acoustic (UWA) channels. In this paper, we propose a receiver that combined SIC and turbo equalization for superposition coding based downlink UWA orthogonal frequency-division multiplexing (OFDM) system, where a near-far user pair is mainly considered. We design an SC signal detector based on the minimum mean square error (MMSE) algorithm and eliminate the far user information with high power after detection. After SIC, the turbo equalization composed of an MMSE equalizer and LDPC decoder is adopted for the near user symbols with residual interference from the SIC process. Simulation results and recorded data from the Yellow Sea, China, show that the proposed receiver has a performance gain of at least 1 dB under different modulation pairs compared with traditional SIC receiver based on maximum a posteriori probability principle (MAP SIC). The error-free two-user downlink communication result shows a maximum sum-rate of 8kbps over the horizontal range of downlink 3.55km has been achieved in the Yellow Sea test. • Iterative Turbo structure and implementation algorithm for downlink near user receiver. • Different superposition coding modulation pairs can be processed. • The proposed receiver can achieve error-free communication through iteration. • Receiver was successfully verified by simulation and sea test. [ABSTRACT FROM AUTHOR]

In transmit-reference (TR) receivers, noise in the reference (pilot) pulse causes a noise × noise term in the decision statistic. This term severely degrades receiver performance. We propose a detection algorithm to decrease the noise in the reference pulse in TR receivers. Computer simulations show that at BER = 10−5, the proposed algorithm outperforms the existing algorithm by about 0.8 dB in both coded and uncoded scenarios. In high-rate applications, inter-symbol interference (ISI) drastically impairs the received signal. Monobit quantization intensifies the ISI and hence dramatically degrades the receiver performance. At first glance, channel coding increases ISI and seems useless to combat ISI. However, we propose to employ channel coding to overcome the severe performance loss caused by ISI. Simulation results show that in high SNR values, channel coding tackles the ISI problem especially when convolutional coding is used. Moreover, simulations reveal that convolutional coding is more robust to ISI compared to block coding schemes. Furthermore, the digital circuit design of coded/uncoded traditional and proposed monobit TR receivers is done in 0.18 µm CMOS technology at 2 V supply voltage. Simulations confirm the numerical results obtained in MATLAB. Finally, the power consumption of each receiver is reported. [ABSTRACT FROM AUTHOR]