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Entropy
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Information Theory in Emerging Wireless Communication Systems and Networks
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Information Theory in Emerging Wireless Communication Systems and Networks

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 (15 February 2024) | Viewed by 15372

Special Issue Editor

Dr. Erdem Koyuncu

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering University of Illinois, Chicago, IL 60607, USA
Interests: communication systems; machine learning; information systems; signal processing; networking theory
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wireless communication systems and networks are rapidly evolving to meet the ever-increasing demands for higher data rates, better reliability, and connectivity anywhere, anytime. There are various new technologies and communication techniques that are currently being proposed for 6G networks and beyond, including autonomous aerial networks and Internet of Space Things, terahertz communications, large-scale massive multiple-input multiple-output (MIMO), intelligent reflecting surfaces (IRS), visible light communications (VLC), molecular communications and Internet of Bio/Nano Things,  blockchain-based wireless systems, and quantum communications and computing, just to name a few. Artificial intelligence, machine learning, and edge computing are also expected to be key features of tomorrow’s wireless systems. The nascent nature of the many new proposed methods begs the following fundamental questions: What are the ultimate performance limits of emerging wireless communication systems and networks? How can we design practical schemes to achieve the ultimate limits? It is in these contexts that this Special Issue is soliciting original research articles.

Since its inception more than 70 years ago by Claude Shannon, the primary method to study the performance limits of communication systems and networks has been information theory. An information-theoretic analysis of emerging wireless communication systems and networks is thus the main focal point of this Special Issue. Practical schemes achieving the information-theoretical limits are also of interest. In general, prospective authors must either directly utilize or work with information theory or demonstrate the connection of their work to information-theoretic concepts.

Dr. Erdem Koyuncu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Related Special Issue

Published Papers (8 papers)

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Editorial

Jump to: Research

5 pages, 166 KiB  
Editorial
Information Theory in Emerging Wireless Communication Systems and Networks
by Erdem Koyuncu
Entropy 2024, 26(7), 543; https://doi.org/10.3390/e26070543 - 26 Jun 2024
Viewed by 1430
Abstract
Wireless communication systems and networks are rapidly evolving to meet the increasing demands for higher data rates, better reliability, and connectivity anywhere, anytime [...] Full article
(This article belongs to the Special Issue Information Theory in Emerging Wireless Communication Systems and Networks)

Research

Jump to: Editorial

18 pages, 932 KiB  
Article
Anti-Jamming Communication Using Imitation Learning
by Zhanyang Zhou, Yingtao Niu, Boyu Wan and Wenhao Zhou
Entropy 2023, 25(11), 1547; https://doi.org/10.3390/e25111547 - 16 Nov 2023
Viewed by 1556
Abstract
The communication reliability of wireless communication systems is threatened by malicious jammers. Aiming at the problem of reliable communication under malicious jamming, a large number of schemes have been proposed to mitigate the effects of malicious jamming by avoiding the blocking interference of [...] Read more.
The communication reliability of wireless communication systems is threatened by malicious jammers. Aiming at the problem of reliable communication under malicious jamming, a large number of schemes have been proposed to mitigate the effects of malicious jamming by avoiding the blocking interference of jammers. However, the existing anti-jamming schemes, such as fixed strategy, Reinforcement learning (RL), and deep Q network (DQN) have limited use of historical data, and most of them only pay attention to the current state changes and cannot gain experience from historical samples. In view of this, this manuscript proposes anti-jamming communication using imitation learning. Specifically, this manuscript addresses the problem of anti-jamming decisions for wireless communication in scenarios with malicious jamming and proposes an algorithm that consists of three steps: First, the heuristic-based Expert Trajectory Generation Algorithm is proposed as the expert strategy, which enables us to obtain the expert trajectory from historical samples. The trajectory mentioned in this algorithm represents the sequence of actions undertaken by the expert in various situations. Then obtaining a user strategy by imitating the expert strategy using an imitation learning neural network. Finally, adopting a functional user strategy for efficient and sequential anti-jamming decisions. Simulation results indicate that the proposed method outperforms the RL-based anti-jamming method and DQN-based anti-jamming method regarding solving continuous-state spectrum anti-jamming problems without causing “curse of dimensionality” and providing greater robustness against channel fading and noise as well as when the jamming pattern changes. Full article
(This article belongs to the Special Issue Information Theory in Emerging Wireless Communication Systems and Networks)
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14 pages, 2045 KiB  
Article
Optimal Deployment Strategy for Reconfigurable Intelligent Surface under LoSD via Joint Active and Passive Beamforming
by Ke Zhao, Zhiqun Song and Jun Xiong
Entropy 2023, 25(7), 1073; https://doi.org/10.3390/e25071073 - 17 Jul 2023
Viewed by 1111
Abstract
A reconfigurable intelligent surface (RIS) is a new and revolutionizing technology to achieve spectrum-efficient (SE) and energy-efficient (EE) wireless networks. In this paper, we study an optimal deployment strategy of RIS in a line-of-sight domain (LoSD) based on an actual deployment scenario, which [...] Read more.
A reconfigurable intelligent surface (RIS) is a new and revolutionizing technology to achieve spectrum-efficient (SE) and energy-efficient (EE) wireless networks. In this paper, we study an optimal deployment strategy of RIS in a line-of-sight domain (LoSD) based on an actual deployment scenario, which jointly considers path loss, transmit power and the energy efficiency of the system. Furthermore, we aim to minimize the transmit power via jointly optimizing its transmit beamforming and the reflect phase shifts of RIS, subject to the quality-of-service (QoS) constraint, namely, the signal-to-noise ratio (SNR) constraint at the user. However, this optimization problem is non-convex with intricately coupled variables. To tackle this challenge, we first apply proper transformation on the QoS constraint and then propose an efficient alternating optimization (AO) algorithm. Simulation results demonstrate that compared to a conventional endpoint deployment strategy that simply deploys RIS at the transceiver ends, our proposed LoSD deployment strategy significantly reduces the transmit power by optimizing the available LoS links when a single RIS is relayed. The impact of the number of reflect elements on the system EE is also unveiled. Full article
(This article belongs to the Special Issue Information Theory in Emerging Wireless Communication Systems and Networks)
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19 pages, 2458 KiB  
Article
Deep Reinforcement Learning-Assisted Optimization for Resource Allocation in Downlink OFDMA Cooperative Systems
by Mulugeta Kassaw Tefera, Shengbing Zhang and Zengwang Jin
Entropy 2023, 25(3), 413; https://doi.org/10.3390/e25030413 - 24 Feb 2023
Cited by 7 | Viewed by 3260
Abstract
This paper considers a downlink resource-allocation problem in distributed interference orthogonal frequency-division multiple access (OFDMA) systems under maximal power constraints. As the upcoming fifth-generation (5G) wireless networks are increasingly complex and heterogeneous, it is challenging for resource allocation tasks to optimize the system [...] Read more.
This paper considers a downlink resource-allocation problem in distributed interference orthogonal frequency-division multiple access (OFDMA) systems under maximal power constraints. As the upcoming fifth-generation (5G) wireless networks are increasingly complex and heterogeneous, it is challenging for resource allocation tasks to optimize the system performance metrics and guarantee user service requests simultaneously. Because of the non-convex optimization problems, using existing approaches to find the optimal resource allocation is computationally expensive. Recently, model-free reinforcement learning (RL) techniques have become alternative approaches in wireless networks to solve non-convex and NP-hard optimization problems. In this paper, we study a deep Q-learning (DQL)-based approach to address the optimization of transmit power control for users in multi-cell interference networks. In particular, we have applied a DQL algorithm for resource allocation to maximize the overall system throughput subject to the maximum power and SINR constraints in a flat frequency channel. We first formulate the optimization problem as a non-cooperative game model, where the multiple BSs compete for spectral efficiencies by improving their achievable utility functions while ensuring the quality of service (QoS) requirements to the corresponding receivers. Then, we develop a DRL-based resource allocation model to maximize the system throughput while satisfying the power and spectral efficiency requirements. In this setting, we define the state-action spaces and the reward function to explore the possible actions and learning outcomes. The numerical simulations demonstrate that the proposed DQL-based scheme outperforms the traditional model-based solution. Full article
(This article belongs to the Special Issue Information Theory in Emerging Wireless Communication Systems and Networks)
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16 pages, 648 KiB  
Article
Intelligent Path-Selection-Aided Decoding of Polar Codes
by Hongji Cui, Kai Niu and Shunfu Zhong
Entropy 2023, 25(2), 200; https://doi.org/10.3390/e25020200 - 19 Jan 2023
Cited by 1 | Viewed by 1601
Abstract
CRC-aided successive cancellation list (CA-SCL) decoding is a powerful algorithm that dramatically improves the error performance of polar codes. Path selection is a major issue that affects the decoding latency of SCL decoders. Generally, path selection is implemented using a metric sorter, which [...] Read more.
CRC-aided successive cancellation list (CA-SCL) decoding is a powerful algorithm that dramatically improves the error performance of polar codes. Path selection is a major issue that affects the decoding latency of SCL decoders. Generally, path selection is implemented using a metric sorter, which causes its latency to increase as the list grows. In this paper, intelligent path selection (IPS) is proposed as an alternative to the traditional metric sorter. First, we found that in the path selection, only the most reliable paths need to be selected, and it is not necessary to completely sort all paths. Second, based on a neural network model, an intelligent path selection scheme is proposed, including a fully connected network construction, a threshold and a post-processing unit. Simulation results show that the proposed path-selection method can achieve comparable performance gain to the existing methods under SCL/CA-SCL decoding. Compared with the conventional methods, IPS has lower latency for medium and large list sizes. For the proposed hardware structure, IPS’s time complexity is O(klog2(L)) where k is the number of hidden layers of the network and L is the list size. Full article
(This article belongs to the Special Issue Information Theory in Emerging Wireless Communication Systems and Networks)
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10 pages, 281 KiB  
Article
Joint Power and Time Allocation in Hybrid NoMA/OMA IoT Networks for Two-Way Communications
by Dong-Hua Chen and En-Hua Jiang
Entropy 2022, 24(12), 1756; https://doi.org/10.3390/e24121756 - 30 Nov 2022
Cited by 2 | Viewed by 1557
Abstract
This article investigates two-way communications between an access point (AP) and multiple terminals in low-cost Internet of Things (IoT) networks. The main issues considered are the asymmetric transmission traffic on the uplink (UL) and downlink (DL), and the unbalanced receivers processing capability at [...] Read more.
This article investigates two-way communications between an access point (AP) and multiple terminals in low-cost Internet of Things (IoT) networks. The main issues considered are the asymmetric transmission traffic on the uplink (UL) and downlink (DL), and the unbalanced receivers processing capability at the AP and the terminals. As a solution, a hybrid non-orthogonal multiple access/orthogonal multiple access (NoMA/OMA) scheme together with a joint power and time allocation method is proposed to address these issues. For the system design, we formulated the optimization problem with the aim of minimizing the system power and satisfying the UL and DL transmission rate constraints. Due to the coupling of power and time variables in the objective function and the multi-user interference (MUI) in the UL transmission rate constraints, the formulated problem is shown to be non-linear and non-convex and thus is hard to solve. To obtain a numerical, efficient solution, the original problem is first reformulated to be a convex one relying on the successive convex approximation (SCA) method, and then a numerical efficient solution is thus obtained by using an iterative routine. The proposed transmission scheme is shown to be not only physically feasible but also power-efficient. Full article
(This article belongs to the Special Issue Information Theory in Emerging Wireless Communication Systems and Networks)
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22 pages, 5021 KiB  
Article
Intelligent Reflecting Surface Assisted Secure Transmission in UAV-MIMO Communication Systems
by Tianhao Cheng, Buhong Wang, Zhen Wang, Kunrui Cao, Runze Dong and Jiang Weng
Entropy 2022, 24(11), 1605; https://doi.org/10.3390/e24111605 - 4 Nov 2022
Cited by 1 | Viewed by 1672
Abstract
This paper studies the intelligent reflecting surface (IRS) assisted secure transmission in unmanned aerial vehicle (UAV) communication systems, where the UAV base station, the legitimate receiver, and the malicious eavesdropper in the system are all equipped with multiple antennas. By deploying an IRS [...] Read more.
This paper studies the intelligent reflecting surface (IRS) assisted secure transmission in unmanned aerial vehicle (UAV) communication systems, where the UAV base station, the legitimate receiver, and the malicious eavesdropper in the system are all equipped with multiple antennas. By deploying an IRS on the facade of a building, the UAV base station can be assisted to realize the secure transmission in this multiple-input multiple-output (MIMO) system. In order to maximize the secrecy rate (SR), the transmit precoding (TPC) matrix, artificial noise (AN) matrix, IRS phase shift matrix, and UAV position are jointly optimized subject to the constraints of transmit power limit, unit modulus of IRS phase shift, and maximum moving distance of UAV. Since the problem is non-convex, an alternating optimization (AO) algorithm is proposed to solve it. Specifically, the TPC matrix and AN covariance matrix are derived by the Lagrange dual method. The alternating direction method of multipliers (ADMM), majorization-minimization (MM), and Riemannian manifold gradient (RCG) algorithms are presented, respectively, to solve the IRS phase shift matrix, and then the performance of the three algorithms is compared. Based on the proportional integral (PI) control theory, a secrecy rate gradient (SRG) algorithm is proposed to iteratively search for the UAV position by following the direction of the secrecy rate gradient. The theoretic analysis and simulation results show that our proposed AO algorithm has a good convergence performance and can increase the SR by 40.5% compared with the method without IRS assistance. Full article
(This article belongs to the Special Issue Information Theory in Emerging Wireless Communication Systems and Networks)
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15 pages, 499 KiB  
Article
The Optimal Power Allocation for Sum Rate and Energy Efficiency of Full-Duplex Two-Way Communication Network
by Hengdong Ye, Zhengchuan Chen, Yunjian Jia and Shutong Chen
Entropy 2022, 24(4), 537; https://doi.org/10.3390/e24040537 - 11 Apr 2022
Viewed by 1745
Abstract
Full-duplex (FD) transmission holds a great potential of improving the sum data rate of wireless communication systems. However, the self-interference introduced by the full-duplex transmitter brings a big challenge to enhance the energy efficiency. This paper investigates the power allocation problem in a [...] Read more.
Full-duplex (FD) transmission holds a great potential of improving the sum data rate of wireless communication systems. However, the self-interference introduced by the full-duplex transmitter brings a big challenge to enhance the energy efficiency. This paper investigates the power allocation problem in a full-duplex two-way (FDTW) communication network over an OFDM channel, aiming at improving the sum data rate and energy efficiency. We first characterize the sum rate and energy efficiency achieved in a single-carrier FDTW system. The optimal transmit power that achieves the maximal sum data rate is presented. The energy efficiency maximization problem is solved by using fractional programming. Then we further formulate sum rate and energy efficiency maximization problem in a multi-subcarrier FDTW system. In particular, the sub-optimal transmit power allocation which achieves a decent sum rate improvement is found by using a proposed iterative algorithm. By combining the iterative algorithm and fractional programming, we further maximize the energy efficiency of the multi-subcarrier system. With our proposed algorithm, we can easily obtain an optimal transmit power that approximates the global optimal solution. Simulation results show that using the obtained optimal transmit power allocation algorithm can significantly improve the sum rate and energy efficiency in both single-carrier and multi-subcarrier systems. Full article
(This article belongs to the Special Issue Information Theory in Emerging Wireless Communication Systems and Networks)
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