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Joint sub-carrier pairing and resource allocation for cognitive networks with adaptive relaying

机译:自适应中继的认知网络联合子载波配对和资源分配

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Relayed transmission in a cognitive radio (CR) environment could be used to increase the coverage and capacity of communication system that benefits already from the efficient management of the spectrum developed by CR. Furthermore, there are many types of cooperative communications, including decode-and-forward (DAF) and amplify-and-forward (AAF). In this paper, these techniques are combined in an adaptive mode to benefit from its forwarding advantages; this mode is called adaptive relaying protocol (ARP). Moreover, this work focuses on the joint power allocation in a cognitive radio system in a cooperative mode that operates ARP in multi-carrier mode. The multi-carrier scenario is used in an orthogonal frequency division multiplexing (OFDM) mode, and the problem is formulated to maximize the end-to-end rate by searching the best power allocation at the transmitters. This work includes, besides the ARP model, a sub-carrier pairing strategy that allows the relays to switch to the best sub-carrier pairs to increase the throughput. The optimization problem is formulated and solved under the interference and power budget constraints using the sub-gradient algorithm. The simulation results confirm the efficiency of the proposed adaptive relaying protocol in comparison to other relaying techniques. The results show also the consequence of the choice of the pairing strategy.
机译:认知无线电(CR)环境中的中继传输可用于增加通信系统的覆盖范围和容量,这已经受益于CR开发的频谱的有效管理。此外,存在许多类型的协作通信,包括解码转发(DAF)和放大转发(AAF)。在本文中,将这些技术以自适应模式进行组合以受益于其转发优势。此模式称为自适应中继协议(ARP)。而且,这项工作集中于在协作模式下的认知无线电系统中的联合功率分配,该协作模式以多载波模式操作ARP。多载波方案用于正交频分复用(OFDM)模式,并且通过在发射机处搜索最佳功率分配来制定问题以使端到端速率最大化。除ARP模型外,这项工作还包括子载波配对策略,该策略允许中继器切换到最佳子载波对以提高吞吐量。使用次梯度算法在干扰和功率预算约束条件下提出并解决了优化问题。与其他中继技术相比,仿真结果证实了所提出的自适应中继协议的效率。结果还显示了配对策略选择的结果。

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