1,686 research outputs found

    Directional Relays for Multi-Hop Cooperative Cognitive Radio Networks

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    In this paper, we investigate power allocation and beamforming in a relay assisted cognitive radio (CR) network. Our objective is to maximize the performance of the CR network while limiting interference in the direction of the primary users (PUs). In order to achieve these goals, we first consider joint power allocation and beamforming for cognitive nodes in direct links. Then, we propose an optimal power allocation strategy for relay nodes in indirect transmissions. Unlike the conventional cooperative relaying networks, the applied relays are equipped with directional antennas to further reduce the interference to PUs and meet the CR network requirements. The proposed approach employs genetic algorithm (GA) to solve the optimization problems. Numerical simulation results illustrate the quality of service (QoS) satisfaction in both primary and secondary networks. These results also show that notable improvements are achieved in the system performance if the conventional omni-directional relays are replaced with directional ones

    On the cognitive interference channel with causal unidirectional destination cooperation

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    In previous works, the cognitive interference channel with unidirectional destination cooperation has been studied. In this model, the cognitive receiver acts as a relay of the primary user's message, and its operation is assumed to be strictly causal. In this letter, we study the same channel model with a causal rather than a strictly causal relay, i.e., the relay's transmit symbol depends not only on its past but also on its current received symbol. We propose an outer bound for the discrete memoryless channel, which is later used to compute an outer bound for the Gaussian channel. We also propose an achievable scheme based on instantaneous amplify-and-forward relaying that meets the outer bound in the very strong interference regime

    Distributed Relay Selection for Heterogeneous UAV Communication Networks Using A Many-to-Many Matching Game Without Substitutability

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    This paper proposes a distributed multiple relay selection scheme to maximize the satisfaction experiences of unmanned aerial vehicles (UAV) communication networks. The multi-radio and multi-channel (MRMC) UAV communication system is considered in this paper. One source UAV can select one or more relay radios, and each relay radio can be shared by multiple source UAVs equally. Without the center controller, source UAVs with heterogeneous requirements compete for channels dominated by relay radios. In order to optimize the global satisfaction performance, we model the UAV communication network as a many-to-many matching market without substitutability. We design a potential matching approach to address the optimization problem, in which the optimizing of local matching process will lead to the improvement of global matching results. Simulation results show that the proposed distributed matching approach yields good matching performance of satisfaction, which is close to the global optimum result. Moreover, the many-to-many potential matching approach outperforms existing schemes sufficiently in terms of global satisfaction within a reasonable convergence time.Comment: 6 pages, 4 figures, conferenc
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