Uplink Nonorthogonal Multiple Access Technologies Toward 5G: A Survey

Ye, Neng; Han, Hangcheng; Zhao, Lu; Wang, Aihua

doi:10.1155/2018/6187580

Cited by 61 publications

(34 citation statements)

References 85 publications

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“…The user located near the transmitter cancels the signals of the far users as they act as interference due to their weak SNRs. On the other hand, the farthest user, which has the highest allocated power and, therefore, the maximum contribution to the received superimposed signal, will initially decode and receive their signal [21]. The main challenge for the transmitter is to correctly assign the power for each user according to the channel conditions, as this affects the performance of the SIC [21,34].…”

Section: Appl Sci 2019 9 3022 4 Of 19mentioning

confidence: 99%

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Enhanced NOMA System Using Adaptive Coding and Modulation Based on LSTM Neural Network Channel Estimation

et al. 2019

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Non-orthogonal multiple access (NOMA) is the technique proposed for multiple access in the fifth generation (5G) cellular network. In NOMA, different users are allocated different power levels and are served using the same time/frequency resource blocks (RBs). The main challenges in existing NOMA systems are the limited channel feedback and the difficulty of merging it with advanced adaptive coding and modulation schemes. Unlike formerly proposed solutions, in this paper, we propose an effective channel estimation (CE) algorithm based on the long-short term memory (LSTM) neural network. The LSTM has the advantage of adapting dynamically to the behavior of the fluctuating channel state. On average, the use of LSTM results in a 10% lower outage probability and a 37% increase in the user sum rate as well as a maximal reduction in the bit error rate (BER) of 50% in comparison to the conventional NOMA system. Furthermore, we propose a novel power coefficient allocation algorithm based on binomial distribution and Pascal’s triangle. This algorithm is used to divide power among N users according to each user’s channel condition. In addition, we introduce adaptive code rates and rotated constellations with cyclic Q-delay in the quadri-phase shift keying (QPSK) and quadrature amplitude modulation (QAM) modulators. This modified modulation scheme overcomes channel fading effects and helps to restore the transmitted sequences with fewer errors. In addition to the initial LSTM stage, the added adaptive coding and modulation stages result in a 73% improvement in the BER in comparison to the conventional NOMA system.

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Section: Appl Sci 2019 9 3022 4 Of 19mentioning

confidence: 99%

“…The authors of [2,4,[21][22][23] surveyed all proposed NOMA algorithms, including single carrier, multi carrier, power domain (PD), and cognitive radio-NOMA (CR-NOMA) as well as SISO and…”

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confidence: 99%

Enhanced NOMA System Using Adaptive Coding and Modulation Based on LSTM Neural Network Channel Estimation

et al. 2019

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“…To enable a practical multiuser communication system, efficient resource mapping patterns [14] and new multiple access methods are required. In 5G communication, nonorthogonal multiple access (NOMA) has been recognized as the promising access protocol due to the superior performance in spectral efficiency, connectivity, and flexibility [15]. Nonorthogonal schemes allow overlapping among the signals from different users by exploiting power domain, code domain or interleaver pattern, etc., and thus can provide better performance than the orthogonal counterparts [16].…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning-Aided Detection Method for FTN-Based NOMA

Pan

Wang

et al. 2020

Wireless Communications and Mobile Computing

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The rapid booming of future smart city applications and Internet of things (IoT) has raised higher demands on the next-generation radio access technologies with respect to connection density, spectral efficiency (SE), transmission accuracy, and detection latency. Recently, faster-than-Nyquist (FTN) and nonorthogonal multiple access (NOMA) have been regarded as promising technologies to achieve higher SE and massive connections, respectively. In this paper, we aim to exploit the joint benefits of FTN and NOMA by superimposing multiple FTN-based transmission signals on the same physical recourses. Considering the complicated intra- and interuser interferences introduced by the proposed transmission scheme, the conventional detection methods suffer from high computational complexity. To this end, we develop a novel sliding-window detection method by incorporating the state-of-the-art deep learning (DL) technology. The data-driven offline training is first applied to derive a near-optimal receiver for FTN-based NOMA, which is deployed online to achieve high detection accuracy as well as low latency. Monte Carlo simulation results validate that the proposed detector achieves higher detection accuracy than minimum mean squared error-frequency domain equalization (MMSE-FDE) and can even approach the performance of the maximum likelihood-based receiver with greatly reduced computational complexity, which is suitable for IoT applications in smart city with low latency and high reliability requirements.

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“…To meet the rising demand for green communications, non-orthogonal multiple access (NOMA) has been regarded as a prime technology for future wireless networks to boost the spectral efficiency (SE) [17,18,19,20]. In [17], a cooperative relaying system using NOMA was designed to enhance the SE.…”

Section: Introductionmentioning

confidence: 99%

Outage Performance Analysis and SWIPT Optimization in Energy-Harvesting Wireless Sensor Network Deploying NOMA

Nguyen

et al. 2019

Sensors

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Thanks to the benefits of non-orthogonal multiple access (NOMA) in wireless communications, we evaluate a wireless sensor network deploying NOMA (WSN-NOMA), where the destination can receive two data symbols in a whole transmission process with two time slots. In this work, two relaying protocols, so-called time-switching-based relaying WSN-NOMA (TSR WSN-NOMA) and power-splitting-based relaying WSN-NOMA (PSR WSN-NOMA) are deployed to study energy-harvesting (EH). Regarding the system performance analysis, we obtain the closed-form expressions for the exact and approximate outage probability (OP) in both protocols, and the delay-limited throughput is also evaluated. We then compare the two protocols theoretically, and two optimization problems are formulated to reduce the impact of OP and optimize the data rate. Our numerical and simulation results are provided to prove the theoretical and analytical analysis. Thanks to these results, a great performance gain can be achieved for both TSR WSN-NOMA and PSR WSN-NOMA if optimal values of TS and PS ratios are found. In addition, the optimized TSR WSN-NOMA outperforms that of PSR WSN-NOMA in terms of OP.

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Uplink Nonorthogonal Multiple Access Technologies Toward 5G: A Survey

Cited by 61 publications

References 85 publications

Enhanced NOMA System Using Adaptive Coding and Modulation Based on LSTM Neural Network Channel Estimation

Enhanced NOMA System Using Adaptive Coding and Modulation Based on LSTM Neural Network Channel Estimation

A Deep Learning-Aided Detection Method for FTN-Based NOMA

Outage Performance Analysis and SWIPT Optimization in Energy-Harvesting Wireless Sensor Network Deploying NOMA

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