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Joint resource allocation and interference avoidance with fairness consideration for multi-cell cognitive radio networks

机译:考虑公平性的多小区认知无线电网络的联合资源分配和干扰避免

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This paper presents a joint resource allocation and interference avoidance algorithm for uplink transmissions in a multi-cell cognitive radio network (CRN), which overlays with a multi-cell primary network (PN). We consider a primary willingness based coexistent architecture. Primary base stations will broadcast pilot signals and interference margins to the CRN for interference channel evaluation and power control. The objective of the algorithm is to maximize the sum rate of cognitive radio cells without causing unacceptable interference to primary receivers, where Lagrangian duality based technique has been utilized to solve the maximization problem and jointly allocate the subchannels and power for each user. The fairness among users is considered within the joint resource allocation to guarantee that the instantaneous rate for each user is larger than a given minimum rate. Simulation results show the efficiency of our algorithm, which has good convergent performance. Moreover, compared to the conventional schemes, the proposed algorithm can satisfy the fairness well, and also obtain a large gain on cell-edge user throughput only with a small reduction in cell sum rate.
机译:本文提出了一种在多小区认知无线网络(CRN)中上行链路传输的联合资源分配和干扰避免算法,该网络覆盖了多小区主网络(PN)。我们考虑基于主要意愿的共存架构。主基站将向CRN广播导频信号和干扰余量,以进行干扰信道评估和功率控制。该算法的目的是最大化认知无线电小区的总速率,而不会对主接收器造成不可接受的干扰,其中基于拉格朗日对偶的技术已被用来解决最大化问题,并为每个用户共同分配子信道和功率。在联合资源分配中考虑用户之间的公平性,以确保每个用户的瞬时速率大于给定的最小速率。仿真结果表明了该算法的有效性,具有良好的收敛性能。而且,与传统方案相比,所提出的算法可以很好地满足公平性,并且仅在小区总和率降低很小的情况下,在小区边缘用户吞吐量上获得了较大的收益。

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