10th EAI International Conference on Mobile Multimedia Communications

Research Article

Joint Resource Allocation and Route Selection for Multi-hop Cognitive Relay Networks

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  • @INPROCEEDINGS{10.4108/eai.13-7-2017.2270671,
        author={Yuanpeng Gao and Ling Wang and Rong Chai},
        title={Joint Resource Allocation and Route Selection for Multi-hop Cognitive Relay Networks},
        proceedings={10th EAI International Conference on Mobile Multimedia Communications},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2017},
        month={12},
        keywords={cognitive network multi-hop relay resource allocation route selection energy efficiency},
        doi={10.4108/eai.13-7-2017.2270671}
    }
    
  • Yuanpeng Gao
    Ling Wang
    Rong Chai
    Year: 2017
    Joint Resource Allocation and Route Selection for Multi-hop Cognitive Relay Networks
    MOBIMEDIA
    EAI
    DOI: 10.4108/eai.13-7-2017.2270671
Yuanpeng Gao1,*, Ling Wang1, Rong Chai1
  • 1: CQUPT
*Contact email: gyp2342623@126.com

Abstract

In this paper, a multi-hop cognitive relay network consisting of multiple PU transmission pairs, SU transmission pairs and relay SUs is considered. To achieve the performance enhancement of multi-hop transmission links between SU pairs, an energy efficient constrained shortest path first (CSPF)- based joint resource allocation and route selection algorithm is proposed, which consists of two sub-algorithms, i.e., CSPFbased route selection sub-algorithm and energy efficiencybased resource allocation sub-algorithm. More specifically, we first apply CSPF-based route selection sub-algorithm to obtain the shortest transmission route under the transmission constraints. Then, an energy efficiency-based resource allocation problem of the shortest routes is formulated and solved by applying iterative algorithm and Lagrange dual method. Finally, the energy efficiency of the shortest transmission routes is examined and the globally optimal route selection and resource allocation strategy is obtained which offers the maximal energy efficiency of the transmission route. Simulation results demonstrate the effectiveness of the proposed algorithm.