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Information-Theoretic Aspects of Non-orthogonal and Massive Access for Future Wireless Networks

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A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: closed (20 December 2021) | Viewed by 12852

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Special Issue Editors

Dr. Benjamin M. Zaidel

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Guest Editor

Faculty of Engineering, Bar-Ilan University, Ramat Gan, Israel
Interests: information theory; wireless communications; random matrix theory; statistical mechanics; MIMO techniques; cellular communication

Dr. Ori Shental

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Guest Editor

Qualcomm Inc., 5775 Morehouse Drive, San Diego, CA 92121, USA
Interests: wireless communications; information theory; statistical mechanics; inference in graphical models; machine learning

Special Issue Information

Dear Colleagues,

The vision for future wireless networks encompasses a wide variety of applications, featuring dramatically higher throughputs as well as massive machine-type communications. It manifests the evolution from human-centric communications, through the current epoch of “internet-of-things” (IoT), to the era of “internet-of-everything” (IoE) expected to evolve during the next decade. This motivates a paradigm shift from legacy orthogonal multiple access (OMA) to non-orthogonal multiple access (NOMA), where the number of simultaneously active users exceeds the number of available time–frequency–space resources. Information-theoretic analyses of NOMA schemes have been a fruitful ground for research in recent years; however, a full comprehension of the fundamental performance limits of the envisioned use-cases is still lacking. Obviously, classical Shannon-type approaches to deriving key performance measures, such as the achievable spectral efficiency, remain useful and of clear interest in certain settings. Nevertheless, some key features of massive machine-type communications may require new paradigms more suitable for the specific characteristics of such settings. In particular, the focus has seemed to shift to new scaling laws for the number of users, code blocklengths, and number of receiving antennas. Moreover, alternative performance measures, such as the recently introduced message-length capacity and per-user probability of error (PUPE), may be essential to a more insightful analytical foundation. In this framework, the notion of “massive access” has been recently considered as an alternative to the classical multiple-access channel setting. Essentially, the massive access model lets the number of active users scale with the blocklength and facilitates analysis of the impact of finite (and short) code blocklengths due to stringent delay constraints, user burstiness, and connectivity larger by orders of magnitude than in classical settings. This Special Issue aims to present a broad information-theoretic perspective of the state-of-the-art of non-orthogonal and massive access research and invites authors to present recent advances in the field that shed light on the challenges ahead in the design of future wireless networks.

This Special Issue solicits unpublished original papers and comprehensive reviews on topics including, but not limited to:

performance limits of NOMA and massive access;
low-complexity transceiver design for code-domain and power-domain NOMA;
techniques for coordinated/uncoordinated (unsourced) and grant-based/grant-free multiple access;
message-passing algorithms and sparse graph models for efficient NOMA and massive access;
finite blocklength and URLLC aspects in NOMA and massive access;
machine learning and data-aided aspects in NOMA and massive access design;
incorporating MIMO and massive MIMO with NOMA and massive access;
methods for active user identification in massive access, including machine learning and compressed-sensing-based techniques;
coding and modulation schemes designed for NOMA and massive access;
leveraging new advances in wireless communications, such as reconfigurable intelligent surfaces (RIS) and orbital angular momentum (OAM), to bolster multiple access; and
privacy and security aspects of NOMA and massive access.

Dr. Benjamin M. Zaidel
Dr. Ori Shental
Guest Editors

Manuscript Submission Information

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Keywords

information theory
signal processing
random matrix theory
statistical mechanics
multiple access
graph theory

Published Papers (6 papers)

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Research

36 pages, 870 KiB

Open AccessArticle

Beyond Equal-Power Sparse NOMA: Two User Classes and Closed-Form Bounds on the Achievable Region

by Benjamin M. Zaidel, Ori Shental and Shlomo Shamai (Shitz)

Entropy 2022, 24(2), 227; https://doi.org/10.3390/e24020227 - 31 Jan 2022

Cited by 4 | Viewed by 1925

Abstract

Non-orthogonal multiple access (NOMA) is a promising technology for future beyond-5G wireless networks, whose fundamental information-theoretic limits are yet to be fully explored. Considering regular sparse code-domain NOMA (with a fixed and finite number of orthogonal resources allocated to any designated user and vice versa), this paper extends previous results by the authors to a setting comprising two classes of users with different power constraints. Explicit rigorous closed-form analytical inner and outer bounds on the achievable rate (total class throughput) region in the large-system limit are derived and comparatively investigated in extreme-SNR regimes. The inner bound is based on the conditional vector entropy power inequality (EPI), while the outer bound relies on a recent strengthened version of the EPI. Valuable insights are provided into the potential performance gains of regular sparse NOMA in practically oriented settings, comprising, e.g., a combination of low-complexity devices and broadband users with higher transmit power capabilities, or combinations of cell-edge and cell-center users. The conditions for superior performance over dense code-domain NOMA (taking the form of randomly spread code-division multiple access), as well as a relatively small gap to the ultimate performance limits, are identified. The proposed bounds are also applicable for the analysis of interference networks, e.g., Wyner-type cellular models. Full article

(This article belongs to the Special Issue Information-Theoretic Aspects of Non-orthogonal and Massive Access for Future Wireless Networks)

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25 pages, 2929 KiB

Open AccessArticle

Optimization Algorithms for Joint Power and Sub-Channel Allocation for NOMA-Based Maritime Communications

by Huanyu Li, Hui Li and Youling Zhou

Entropy 2021, 23(11), 1454; https://doi.org/10.3390/e23111454 - 1 Nov 2021

Cited by 2 | Viewed by 1523

Abstract

This paper investigates resource optimization schemes in a marine communication scenario based on non-orthogonal multiple access (NOMA). According to the offshore environment of the South China Sea, we first establish a Longley–Rice-based channel model. Then, the weighted achievable rate (WAR) is considered as the optimization objective to weigh the information rate and user fairness effectively. Our work introduces an improved joint power and user allocation scheme (RBPUA) based on a single resource block. Taking RBPUA as a basic module, we propose three joint multi-subchannel power and marine user allocation algorithms. The gradient descent algorithm (GRAD) is used as the reference standard for WAR optimization. The multi-choice knapsack algorithm combined with dynamic programming (MCKP-DP) obtains a WAR optimization result almost equal to that of GRAD. These two NOMA-based solutions are able to improve WAR performance by 7.47% compared with OMA. Due to the high computational complexity of the MCKP-DP, we further propose a DP-based fully polynomial-time approximation algorithm (DP-FPTA). The simulation results show that DP-FPTA can reduce the complexity by 84.3% while achieving an approximate optimized performance of 99.55%. This advantage of realizing the trade-off between performance optimization and complexity meets the requirements of practical low-latency systems. Full article

(This article belongs to the Special Issue Information-Theoretic Aspects of Non-orthogonal and Massive Access for Future Wireless Networks)

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27 pages, 539 KiB

Open AccessArticle

Spectrum Slicing for Multiple Access Channels with Heterogeneous Services

by Federico Chiariotti, Israel Leyva-Mayorga, Čedomir Stefanović, Anders E. Kalør and Petar Popovski

Entropy 2021, 23(6), 686; https://doi.org/10.3390/e23060686 - 28 May 2021

Cited by 5 | Viewed by 2425

Abstract

Wireless mobile networks from the fifth generation (5G) and beyond serve as platforms for flexible support of heterogeneous traffic types with diverse performance requirements. In particular, the broadband services aim for the traditional rate optimization, while the time-sensitive services aim for the optimization of latency and reliability, and some novel metrics such as Age of Information (AoI). In such settings, the key question is the one of spectrum slicing: how these services share the same chunk of available spectrum while meeting the heterogeneous requirements. In this work we investigated the two canonical frameworks for spectrum sharing, Orthogonal Multiple Access (OMA) and Non-Orthogonal Multiple Access (NOMA), in a simple, but insightful setup with a single time-slotted shared frequency channel, involving one broadband user, aiming to maximize throughput and using packet-level coding to protect its transmissions from noise and interference, and several intermittent users, aiming to either to improve their latency-reliability performance or to minimize their AoI. We analytically assessed the performances of Time Division Multiple Access (TDMA) and ALOHA-based schemes in both OMA and NOMA frameworks by deriving their Pareto regions and the corresponding optimal values of their parameters. Our results show that NOMA can outperform traditional OMA in latency-reliability oriented systems in most conditions, but OMA performs slightly better in age-oriented systems. Full article

(This article belongs to the Special Issue Information-Theoretic Aspects of Non-orthogonal and Massive Access for Future Wireless Networks)

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23 pages, 454 KiB

Open AccessArticle

DRL-Assisted Resource Allocation for NOMA-MEC Offloading with Hybrid SIC

by Haodong Li, Fang Fang and Zhiguo Ding

Entropy 2021, 23(5), 613; https://doi.org/10.3390/e23050613 - 14 May 2021

Cited by 13 | Viewed by 2564

Abstract

Multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA) are regarded as promising technologies to improve the computation capability and offloading efficiency of mobile devices in the sixth-generation (6G) mobile system. This paper mainly focused on the hybrid NOMA-MEC system, where multiple users were first grouped into pairs, and users in each pair offloaded their tasks simultaneously by NOMA, then a dedicated time duration was scheduled to the more delay-tolerant user for uploading the remaining data by orthogonal multiple access (OMA). For the conventional NOMA uplink transmission, successive interference cancellation (SIC) was applied to decode the superposed signals successively according to the channel state information (CSI) or the quality of service (QoS) requirement. In this work, we integrated the hybrid SIC scheme, which dynamically adapts the SIC decoding order among all NOMA groups. To solve the user grouping problem, a deep reinforcement learning (DRL)-based algorithm was proposed to obtain a close-to-optimal user grouping policy. Moreover, we optimally minimized the offloading energy consumption by obtaining the closed-form solution to the resource allocation problem. Simulation results showed that the proposed algorithm converged fast, and the NOMA-MEC scheme outperformed the existing orthogonal multiple access (OMA) scheme. Full article

(This article belongs to the Special Issue Information-Theoretic Aspects of Non-orthogonal and Massive Access for Future Wireless Networks)

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20 pages, 431 KiB

Open AccessArticle

On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel

by Elad Romanov and Or Ordentlich

Entropy 2021, 23(5), 605; https://doi.org/10.3390/e23050605 - 14 May 2021

Cited by 6 | Viewed by 2020

Abstract

Motivated by applications in unsourced random access, this paper develops a novel scheme for the problem of compressed sensing of binary signals. In this problem, the goal is to design a sensing matrix A and a recovery algorithm, such that the sparse binary [...] Read more.

x

can be recovered reliably from the measurements

y = A x + σ z

, where

z

is additive white Gaussian noise. We propose to design A as a parity check matrix of a low-density parity-check code (LDPC) and to recover

x

from the measurements

y

using a Markov chain Monte Carlo algorithm, which runs relatively fast due to the sparse structure of A. The performance of our scheme is comparable to state-of-the-art schemes, which use dense sensing matrices, while enjoying the advantages of using a sparse sensing matrix. Full article

(This article belongs to the Special Issue Information-Theoretic Aspects of Non-orthogonal and Massive Access for Future Wireless Networks)

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17 pages, 502 KiB

Open AccessArticle

Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access

by Ralf R. Müller

Entropy 2021, 23(5), 539; https://doi.org/10.3390/e23050539 - 28 Apr 2021

Cited by 2 | Viewed by 1389

Abstract

In 2017, Polyanskiy showed that the trade-off between power and bandwidth efficiency for massive Gaussian random access is governed by two fundamentally different regimes: low power and high power. For both regimes, tight performance bounds were found by Zadik et al., in 2019. This work utilizes recent results on the exact block error probability of Gaussian random codes in additive white Gaussian noise to propose practical methods based on iterative soft decoding to closely approach these bounds. In the low power regime, this work finds that orthogonal random codes can be applied directly. In the high power regime, a more sophisticated effort is needed. This work shows that power-profile optimization by means of linear programming, as pioneered by Caire et al. in 2001, is a promising strategy to apply. The proposed combination of orthogonal random coding and iterative soft decoding even outperforms the existence bounds of Zadik et al. in the low power regime and is very close to the non-existence bounds for message lengths around 100 and above. Finally, the approach of power optimization by linear programming proposed for the high power regime is found to benefit from power imbalances due to fading which makes it even more attractive for typical mobile radio channels. Full article

(This article belongs to the Special Issue Information-Theoretic Aspects of Non-orthogonal and Massive Access for Future Wireless Networks)

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