认知无线网络中基于约束的中继站布局

M. Poornima, R. Sumathi, M. Suganthi
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引用次数: 0

摘要

认知无线电技术使二次用户能够伺机利用空闲的许可频谱,大大提高了频谱资源的利用率。认知无线网络(crn)的传统架构,如认知蜂窝网络和认知自组织网络,将消耗能量的认知无线电强加给SUs设备进行通信,并且不能有效利用从主用户(pu)获取的频谱。为了提高crn的频谱和能量效率,我们设计了一种新的架构,称为认知能力收获网络(CCH)。在CCH,我们部署了一组具有认知能力的中继站,以方便用户访问SUs。这样,该架构不仅消除了对单元的认知无线电需求,降低了单元的能耗,而且增加了频率复用,提高了频谱效率。鉴于RSs在提高频谱效率和能量效率方面的重要性,本文对CCH中的RS放置策略进行了研究。我们设计了一个启发式算法框架来计算近最优解。仿真结果表明,所提出的算法优于随机布局策略,且在最优解的2倍以内。
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Constraint-based relay station placement in cognitive radio networks
Cognitive radio technology enables secondary users (SUs) to opportunistically use the vacant licensed spectrum and significantly improves the utilization of spectrum resource. Traditional architectures for cognitive radio networks (CRNs), such as cognitive cellular networks and cognitive ad hoc networks, impose energy-consuming cognitive radios to SUs' devices for communication and cannot efficiently utilize the spectrum harvested from the primary users (PUs). To enhance the spectrum and energy efficiencies of CRNs, we have designed a new architecture, which is called the Cognitive Capacity Harvesting network (CCH). In CCH, a collection of relay stations (RSs) with cognitive capability are deployed to facilitate the accessing of SUs. In this way, the architecture not only removes the requirement of cognitive radios from SUs and reduces their energy consumption, but also increases frequency reuse and enhances spectrum efficiency. In view of the importance of the RSs on the improvement of spectrum and energy efficiencies, in this paper, we study the RS placement strategy in CCH. We design a framework of heuristic algorithms to compute the near-optimal solutions. The simulation result show that the proposed algorithms outperform the random placement strategy and is always within 2 times of that in the optimal solution.
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