Non-orthogonal multiple access (NOMA) is an essential enabling technology for the fifth-generation (5G) wireless networks to meet the heterogeneous demands on low latency, high reliability, massive connectivity, improved fairness, and high throughput. The key idea behind NOMA is to serve multiple users in the same resource block, such as a time slot, subcarrier, or spreading code. The NOMA principle is a general framework, and several recently proposed 5G multiple access schemes can be viewed as special cases. This survey provides an overview of the latest NOMA research and innovations as well as their applications. Thereby, the papers published in this special issue are put into the context of the existing literature. Future research challenges regarding NOMA in 5G and beyond are also discussed.

A Survey on Non-Orthogonal Multiple Access for 5G Networks: Research Challenges and Future Trends

Non-orthogonal multiple access (NOMA) is an essential enabling technology for the fifth generation (5G) wireless networks to meet the heterogeneous demands on low latency, high reliability, massive connectivity, improved fairness, and high throughput. The key idea behind NOMA is to serve multiple users in the same resource block, such as a time slot, subcarrier, or spreading code. The NOMA principle is a general framework, and several recently proposed 5G multiple access schemes can be viewed as special cases. This survey provides an overview of the latest NOMA research and innovations as well as their applications. Thereby, the papers published in this special issue are put into the content of the existing literature. Future research challenges regarding NOMA in 5G and beyond are also discussed.

In the fifth generation (5G) of wireless communication systems, hitherto unprecedented requirements are expected to be satisfied. As one of the promising techniques of addressing these challenges, non-orthogonal multiple access (NOMA) has been actively investigated in recent years. In contrast to the family of conventional orthogonal multiple access (OMA) schemes, the key distinguishing feature of NOMA is to support a higher number of users than the number of orthogonal resource slots with the aid of non-orthogonal resource allocation. This may be realized by the sophisticated inter-user interference cancellation at the cost of an increased receiver complexity. In this paper, we provide a comprehensive survey of the original birth, the most recent development, and the future research directions of NOMA. Specifically, the basic principle of NOMA will be introduced at first, with the comparison between NOMA and OMA especially from the perspective of information theory. Then, the prominent NOMA schemes are discussed by dividing them into two categories, namely, power-domain and code-domain NOMA. Their design principles and key features will be discussed in detail, and a systematic comparison of these NOMA schemes will be summarized in terms of their spectral efficiency, system performance, receiver complexity, etc. Finally, we will highlight a range of challenging open problems that should be solved for NOMA, along with corresponding opportunities and future research trends to address these challenges.

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A Survey of Non-Orthogonal Multiple Access for 5G

What is index modulation (IM)? This is an interesting question that we have started to hear more and more frequently over the past few years. The aim of this paper is to answer this question in a comprehensive manner by covering not only the basic principles and emerging variants of IM, but also reviewing the most recent as well as promising advances in this field toward the application scenarios foreseen in next-generation wireless networks. More specifically, we investigate three forms of IM: spatial modulation, channel modulation and orthogonal frequency division multiplexing (OFDM) with IM, which consider the transmit antennas of a multiple-input multiple-output system, the radio frequency mirrors (parasitic elements) mounted at a transmit antenna and the subcarriers of an OFDM system for IM techniques, respectively. We present the up-to-date advances in these three promising frontiers and discuss possible future research directions for IM-based schemes toward low-complexity, spectrum- and energy-efficient next-generation wireless networks.

Index Modulation Techniques for Next-Generation Wireless Networks

Massive access, also known as massive connectivity or massive machine-type communication (mMTC), is one of the main use cases of the fifth-generation (5G) and beyond 5G (B5G) wireless networks. A typical application of massive access is the cellular Internet of Things (IoT). Different from conventional human-type communication, massive access aims at realizing efficient and reliable communications for a massive number of IoT devices. Hence, the main characteristics of massive access include low power, massive connectivity, and broad coverage, which require new concepts, theories, and paradigms for the design of next-generation cellular networks. This paper presents a comprehensive survey of massive access design for B5G wireless networks. Specifically, we provide a detailed review of massive access from the perspectives of theory, protocols, techniques, coverage, energy, and security. Furthermore, several future research directions and challenges are identified.

Massive Access for 5G and Beyond

Non-orthogonal multiple access (NOMA) is an emerging research topic in the future fifth generation wireless communication networks, which is expected to support massive connectivity for massive machine-type communications (mMTC). Due to the sporadic communication nature of mMTC, the grant-free transmission methodology is highly expected in uplink NOMA systems, to drastically reduce the transmission latency and signaling overhead. Exploiting the inherent sparsity nature of user activity, compressive sensing (CS) techniques have been applied for efficient multi-user detection in the uplink grant-free NOMA. In this paper, we propose a prior-information-aided adaptive subspace pursuit (PIA-ASP) algorithm to improve the multi-user detection performance. In this algorithm, a parameter evaluating the quality of the prior-information support set is introduced, in order to exploit the intrinsically temporal correlation of active user support sets in several continuous time slots adaptively. Then, to mitigate the incorrect estimation effect of the prior support quality information, a robust PIA-ASP algorithm is further proposed, which adaptively exploits the prior support based on the corresponding support quality information in a conservative way. It is noted that both of the two proposed algorithms do not require the knowledge of the user sparsity level, while most of the state-of-the-art CS-based multi-user detection algorithms usually need. Moreover, for the two proposed algorithms, the upper bound of the signal detection error and the computational complexity is derived. Simulation results demonstrate that the two proposed algorithms are capable of achieving much better performance than that of the existing CS-based multi-user detection algorithms with a similar computational complexity.

Efficient Multi-User Detection for Uplink Grant-Free NOMA: Prior-Information Aided Adaptive Compressive Sensing Perspective

Grant-free non-orthogonal multiple access is an emerging research topic in machine-type communications, which is used to reduce signaling overhead. In this context, this letter introduces a novel joint channel estimation (CE) and multiuser detection (MUD) framework for the frame based multi-user transmission scenario where users are (in)active for the duration of a frame. First, considering the inherent frame-wise joint sparsity of the pilot and data phases in the entire frame, we formulate the multiple measurement vector-compressive sensing (MMV-CS) framework. Then, transfer the MMV-CS to a block-sparse single measurement vector-CS (BS-SMV-CS) model. Finally, to make explicit use of the block sparsity inherent in the BS-SMV-CS model and consider that the user sparsity level should be unknown for receiver, an enhanced subspace pursuit (SP) algorithm is developed, i.e., block sparsity adaptive SP. Superior performance of the proposed joint CE and MUD framework is demonstrated by simulation results.

Joint Channel Estimation and Multiuser Detection for Uplink Grant-Free NOMA

Grant-free non-orthogonal multiple access has recently gained significant attention for reducing signaling overhead in machine-type communications. In this context, compressed sensing (CS) has been identified as a good candidate for joint activity and data detection due to the inherent sparsity nature of user activity. This paper augments activity and data detection for frame-based multi-user uplink scenarios where users are (in)-active for the duration of a frame, namely, the frame-wise joint sparsity model. First, we formulate the block CS (BCS)-based sparse signal recovery framework, by fully extracting and exploiting the underlying frame-wise joint sparsity of the user activity. Then, to make explicit use of the block sparsity inherent in the equivalent block-sparse model and considering the user sparsity level to be unknown for multiuser detection, two enhanced BCS-based greedy algorithms are developed, i.e., threshold aided block sparsity adaptive subspace pursuit (TA-BSASP) and cross-validation aided block sparsity adaptive subspace pursuit (CVA-BSASP). Specifically, the proposed TA-BSASP algorithm can approach the oracle least squares (LS) performance by reasonably setting the threshold based on the additive white Gaussian noise floor. Moreover, the proposed CVA-BSASP algorithm is a highly practical algorithm design that adopts the statistical and machine learning mechanism cross-validation to determine the stopping condition of the algorithm and this does not require prior knowledge. Furthermore, the convergence and the computational complexity of the proposed algorithms are derived and the superior performance of the proposed algorithms is demonstrated by numerical experiments.

Block-Sparsity-Based Multiuser Detection for Uplink Grant-Free NOMA

The existing multiuser detection schemes for uplink (UP) sparse code multiple access (SCMA) systems are based on a parallel message update for message passing algorithm (MPA). In this letter, a shuffled MPA (S-MPA) scheme for UP SCMA systems is proposed, based on a serial message update strategy. Since the updated messages can join the message propagation immediately in current iteration, the convergence rate is accelerated, so that the complexity of the proposed S-MPA scheme can be substantially reduced with negligible bit error rate (BER) degradation. Simulations show that the proposed S-MPA scheme with two iterations provides similar BER performance to the original MPA scheme with six iterations. Furthermore, a parallel form of the proposed S-MPA scheme, termed group S-MPA, is developed to decrease the detection delay of the proposed S-MPA scheme, which offers a good BER-latency tradeoff.

Shuffled Multiuser Detection Schemes for Uplink Sparse Code Multiple Access Systems

Sparse code multiple access (SCMA) is a competitive non-orthogonal multiple access technique for fifth generation wireless communication networks which can accommodate massive connectivity. Among the existing multiuser detection schemes for uplink (UP) SCMA systems, the asynchronous message passing algorithm (ASYN-MPA) scheme, where messages are updated sequentially, generally converges faster than the synchronous variant, where all messages are updated in parallel manner. Nevertheless, the specific pre-defined order of the ASYN-MPA scheme is not always the best option. In this letter, we tackle the problem of how to schedule message for the ASYN-MPA scheme that results in the best convergence rate. Specifically, a novel residual-aided message propagation approach for scheduling messages in the ASYN-MPA scheme, termed residual-aided MPA, is proposed for UP SCMA systems, which exploits the dynamic selection of the message which has the largest residual. Simulations show that the proposed scheme with two iterations provides very similar bit error rate performance to the existing multiuser detection schemes with six iterations (only less than 0.05 dB degradation), whose complexity is reduced substantially.

Binhong Dong

Papers

Efficient Multi-User Detection for Uplink Grant-Free NOMA: Prior-Information Aided Adaptive Compressive Sensing Perspective

Joint Channel Estimation and Multiuser Detection for Uplink Grant-Free NOMA

Block-Sparsity-Based Multiuser Detection for Uplink Grant-Free NOMA

Shuffled Multiuser Detection Schemes for Uplink Sparse Code Multiple Access Systems

A Fast Convergence Multiuser Detection Scheme for Uplink SCMA Systems