Spectrum Sharing in Cache-Empowered Wireless Networks: Reservation-Based Versus Auction-Based Approaches

IF 7.4 1区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Cognitive Communications and Networking Pub Date : 2023-07-07 DOI:10.1109/TCCN.2023.3293018
Haiming Hui;Xin Guo;Haiming Wang;Wei Chen
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Abstract

Spectrum sharing has attracted much recent attention from both industry and academia due to its significant potential of achieving high radio resource efficiency and scaling the service capability in wireless networks. However, how to fairly and efficiently share the radio spectrum or bandwidth in cache-empowered wireless networks remains open. In this paper, we present a reservation-based and an auction-based approach for dynamic spectrum access in cache-empowered wireless networks that serves both on-demand and pushing traffics. More specifically, a virtual network operator (VNO) is introduced as a spectrum access scheduler, which pays to the spectrum owner for the bandwidth it uses while charging its users for their content requests. To ensure the quality of service, a VNO is punished if it fails to satisfy a user’s request in peak time. By balancing the bandwidth cost and penalty, multiple VNOs may maximize the spectrum efficiency in a distributed manner. To further improve the spectrum efficiency in cache-empowered wireless networks, we formulate a linear program and a nonlinear program for both the reservation-based and the auction-based spectrum access, respectively. A modified deep Q-network algorithm is also presented to substantially reduce the computational complexity and to attain a distributed online spectrum sharing protocol.
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高速缓存无线网络中的频谱共享:基于预约与基于拍卖的方法
频谱共享由于其在实现高无线电资源效率和扩展无线网络服务能力方面的巨大潜力,最近引起了工业界和学术界的广泛关注。然而,如何在高速缓存授权的无线网络中公平有效地共享无线电频谱或带宽仍然是悬而未决的。在本文中,我们提出了一种基于预约和拍卖的方法,用于缓存授权的无线网络中的动态频谱接入,该网络同时服务于点播和推送业务。更具体地说,虚拟网络运营商(VNO)被引入作为频谱接入调度器,它向频谱所有者支付其使用的带宽,同时向用户收取其内容请求的费用。为了确保服务质量,如果VNO在高峰时间未能满足用户的请求,它将受到惩罚。通过平衡带宽成本和惩罚,多个VNO可以以分布式方式最大化频谱效率。为了进一步提高高速缓存无线网络的频谱效率,我们分别为基于预约和基于拍卖的频谱接入制定了线性规划和非线性规划。提出了一种改进的深度Q网络算法,大大降低了计算复杂度,实现了分布式在线频谱共享协议。
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来源期刊
IEEE Transactions on Cognitive Communications and Networking
IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence
CiteScore
15.50
自引率
7.00%
发文量
108
期刊介绍: The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.
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