• Title/Summary/Keyword: joint relay selection and power allocation

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Performance Analysis And Optimization For AF Two-Way Relaying With Relay Selection Over Mixed Rician And Rayleigh Fading

  • Fan, Zhangjun;Guo, Daoxing;Zhang, Bangning;Zeng, Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.12
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    • pp.3275-3295
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    • 2012
  • In this paper, we analyze the performance of an amplify-and-forward (AF) two-way relaying system, where two sources exchange information via the aid of an intermediate relay that is selected among multiple relays according to max-min criterion. We consider a practical scenario, where one source-relay link undergoes Rician fading, and the other source-relay link is subject to Rayleigh fading. To be specific, we derive a tight lower bound for the outage probability. From this lower bound, the asymptotic outage probability and average symbol error rate (SER) expressions are derived to gain insight into the system performance at high signal-to-noise ratio (SNR) region. Furthermore, we investigate the optimal power allocation (PA) with fixed relay location (RL), optimal RL with fixed PA and joint optimization of PA and RL to minimize the outage probability and average SER. The analytical expressions are verified through Monte Carlo simulations, where the positive impact of Rician factor on the system performance is also illustrated. Simulation results also validate the effectiveness of the proposed PA and relay positioning schemes.

Efficient Resource Allocation with Multiple Practical Constraints in OFDM-based Cooperative Cognitive Radio Networks

  • Yang, Xuezhou;Tang, Wei;Guo, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.7
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    • pp.2350-2364
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    • 2014
  • This paper addresses the problem of resource allocation in amplify-and-forward (AF) relayed OFDM based cognitive radio networks (CRNs). The purpose of resource allocation is to maximize the overall throughput, while satisfying the constraints on the individual power and the interference induced to the primary users (PUs). Additionally, different from the conventional resource allocation problem, the rate-guarantee constraints of the subcarriers are considered. We formulate the problem as a mixed integer programming task and adopt the dual decomposition technique to obtain an asymptotically optimal power allocation, subcarrier pairing and relay selection. Moreover, we further design a suboptimal algorithm that sacrifices little on performance but could significantly reduce computational complexity. Numerical simulation results confirm the optimality of the proposed algorithms and demonstrate the impact of the different constraints.

Spectrum Leasing and Cooperative Resource Allocation in Cognitive OFDMA Networks

  • Tao, Meixia;Liu, Yuan
    • Journal of Communications and Networks
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    • v.15 no.1
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    • pp.102-110
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    • 2013
  • This paper considers a cooperative orthogonal frequency division multiple access (OFDMA)-based cognitive radio network where the primary system leases some of its subchannels to the secondary system for a fraction of time in exchange for the secondary users (SUs) assisting the transmission of primary users (PUs) as relays. Our aim is to determine the cooperation strategies among the primary and secondary systems so as to maximize the sum-rate of SUs while maintaining quality-of-service (QoS) requirements of PUs. We formulate a joint optimization problem of PU transmission mode selection, SU (or relay) selection, subcarrier assignment, power control, and time allocation. By applying dual method, this mixed integer programming problem is decomposed into parallel per-subcarrier subproblems, with each determining the cooperation strategy between one PU and one SU. We show that, on each leased subcarrier, the optimal strategy is to let a SU exclusively act as a relay or transmit for itself. This result is fundamentally different from the conventional spectrum leasing in single-channel systems where a SU must transmit a fraction of time for itself if it helps the PU's transmission. We then propose a subgradient-based algorithm to find the asymptotically optimal solution to the primal problem in polynomial time. Simulation results demonstrate that the proposed algorithm can significantly enhance the network performance.