Journal ArticleDOI
Relay selection Algorithm for wireless cooperative networks: a learning-based approach
TLDR
A reinforcement learning technique, called as Q -learning (QL), is used to solve the relay selection problem and a `QL-based relay selection algorithm' (QL-RSA) is proposed for wireless cooperative networks that maximises the total capacity of the network.Abstract:
Relay selection in cooperative communication is a crucial task for achieving the spatial diversity since the improper relay selection can decrease the overall capacity of the network. In this study, the authors use a reinforcement learning technique, called as Q
-learning (QL), to solve the relay selection problem. They propose a `QL-based relay selection algorithm' (QL-RSA) for wireless cooperative networks that maximises the total capacity of the network. QL-RSA receives the reward (feedback) in terms of the capacity by learning a multi-node amplify-and-forward cooperative environment with time-varying Rayleigh fading channels. The advantages of QL-RSA are that it is less complex, requires less channel feedback information and it is distributed in a multiple-sources environment as it provides each source a self-learning capability to find the optimal relay without exchanging information with other source nodes.read more
Citations
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Journal ArticleDOI
Enabling Massive IoT Toward 6G: A Comprehensive Survey
TL;DR: A use case of fully autonomous driving is presented to show 6G supports massive IoT and some breakthrough technologies, such as machine learning and blockchain, in 6G are introduced, where the motivations, applications, and open issues of these technologies for massive IoT are summarized.
Journal ArticleDOI
Cooperative Communications With Relay Selection Based on Deep Reinforcement Learning in Wireless Sensor Networks
TL;DR: This paper proposes DQ-RSS, a deep-reinforcement-learning-based relay selection scheme in WSNs and uses DQN to process high-dimensional state spaces and accelerate the learning rate, and compares the network performance on the basis of three aspects: outage probability, system capacity, and energy consumption.
Journal ArticleDOI
Machine Learning for Advanced Wireless Sensor Networks: A Review
TL;DR: In this review, recent developments of ML techniques for WSNs are presented with much emphasis on DL techniques, and it is found that large training time and large dataset to get acceptable performance are accompanied with large energy consumption which is not favorable for resource-restrained W SNs.
Journal ArticleDOI
Delay-Constrained Buffer-Aided Relay Selection in the Internet of Things With Decision-Assisted Reinforcement Learning
Chong Huang,Gaojie Chen,Yu Gong +2 more
TL;DR: In this article, a decision-assisted deep reinforcement learning was proposed to improve the convergence of relay selection in buffer-aided relay systems. But, the proposed approaches can achieve high throughput subject to delay constraints, but often at the price of higher latency.
Proceedings ArticleDOI
Deep Reinforcement Learning Based Relay Selection in Delay-Constrained Secure Buffer-Aided CRNs
TL;DR: In this article, a Deep Reinforcement Learning based delay-constrained relay selection for secure buffer aided CRNs is investigated, where the relay selection problem in secure butter-aided CRNs was modeled as a Markov decision process (MDP) problem, and Deep Q-Learning was used to solve this MDP problem.
References
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Journal ArticleDOI
Cooperative diversity in wireless networks: Efficient protocols and outage behavior
TL;DR: Using distributed antennas, this work develops and analyzes low-complexity cooperative diversity protocols that combat fading induced by multipath propagation in wireless networks and develops performance characterizations in terms of outage events and associated outage probabilities, which measure robustness of the transmissions to fading.
Journal ArticleDOI
Cooperative communication in wireless networks
TL;DR: An overview of the developments in cooperative communication, a new class of methods called cooperative communication has been proposed that enables single-antenna mobiles in a multi-user environment to share their antennas and generate a virtual multiple-antenn transmitter that allows them to achieve transmit diversity.
Journal ArticleDOI
Fading relay channels: performance limits and space-time signal design
TL;DR: This paper examines the basic building block of cooperative diversity systems, a simple fading relay channel where the source, destination, and relay terminals are each equipped with single antenna transceivers and shows that space-time codes designed for the case of colocated multiantenna channels can be used to realize cooperative diversity provided that appropriate power control is employed.
[IEEE 2006 IEEE International Symposium on Information Theory - Seattle, WA (2006.7.9-2006.7.9)] 2006 IEEE International Symposium on Information Theory - Improving Amplify-and-Forward Relay Networks: Optimal Power Allocation versus Selection
TL;DR: It is shown that at reasonable power levels the selection AF scheme maintains full diversity order, and has significantly better outage behavior and average throughput than the conventional scheme or that with optimal power allocation.