Analysis of PAPR on NOMA Waveforms Using Hybrid Algorithm

We investigate in this paper how to optimize the number of iterations required for sliding window decoding of low-density parity-check (LDPC) codes. The aim of this study is to reduce decoding complexity and overcome the phenomenon of decoder blocking. We propose a new design of SC-LDPC codes based on some 5G short LDPC codes to reduce decoding complexity. Simulation results demonstrate a potential reduction in decoding computational complexity of the order of 30% without significant degradation in decoding performance. In addition to taking care of complexity, this mitigates the problem of sliding window decoder blocking by reducing the probability of observing this phenomenon.

Low-Complexity Sliding Window Decoding of Spatially-Coupled LDPC Codes Constructed from Short 5G NR LDPC

Non-orthogonal multiple access (NOMA) scheme is a promising multiple access technique for the fifth generation (5G) New Radio (NR) due to its high spectral efficiency, massive connectivity and low latency. In this paper, a Low Density Superposition Modulation (LDSM) using discrete-cosine transform (DCT) scheme with 5G-NR low-density parity-check (LDPC) channel code is proposed for the 5G scenario. Moreover, we adopt a low-complexity elementary signal estimator (ESE) detection algorithm for the multi-user detection. Simulation results show that our proposed scheme has the 3–5 dB peak-to-average power ratio (PAPR) reduction as compared with the conventional sparse code multiple access (SCMA) and pattern division multiple access (PDMA). Besides, our scheme brings about 0.6 dB-2.0 dB performance gains. Therefore, the DCT-LDSM scheme is efficient and suitable for 5G scenario.

Low Density Superposition Modulation using DCT for 5G NOMA scheme

In this paper, we propose a parallel and memory-efficient decoding for spatially-coupled low-density parity-check (SC LDPC) codes. The new decoding was obtained by applying parallel architecture and efficient memory management to the windowed decoding. Simulation results show that the new decoding greatly reduces decoding latency and requires less memory, and there is no performance degradation. The advantage of the proposed decoding make it appealing in practical applications, especially in low latency scenario.

A Parallel and Memory-Efficient Decoding for Spatially-Coupled LDPC Codes

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Low Density Superposition Modulation using DCT for 5G NOMA scheme

A Parallel and Memory-Efficient Decoding for Spatially-Coupled LDPC Codes