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Distributed Interference Management in Two-Tier CDMA Femtocell Networks

机译:两层CDMA Femtocell网络中的分布式干扰管理

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This paper proposes distributed joint power and admission control algorithms for the management of interference in two-tier femtocell networks, where the newly-deployed femtocell users (FUEs) share the same frequency band with the existing macrocell users (MUEs) using code-division multiple access (CDMA). As the owner of the licensed radio spectrum, the MUEs possess strictly higher access priority over the FUEs; thus, their quality-of-service (QoS) performance, expressed in terms of the prescribed minimum signal-to-interference-plus-noise ratio (SINR), must be maintained at all times. For the lower-tier FUEs, we explicitly consider two different design objectives, namely, throughput-power tradeoff optimization and soft QoS provisioning. With an effective dynamic pricing scheme combined with admission control to indirectly manage the cross-tier interference, the proposed schemes lend themselves to distributed algorithms that mainly require local information to offer maximized net utility of individual users. The approach employed in this work is particularly attractive, especially in view of practical implementation under the limited backhaul network capacity available for femtocells. It is shown that the proposed algorithms robustly support all the prioritized MUEs with guaranteed QoS requirements whenever feasible, while allowing the FUEs to optimally exploit the remaining network capacity. The convergence of the developed solutions is rigorously analyzed, and extensive numerical results are presented to illustrate their potential advantages.
机译:本文提出了分布式联合功率和准入控制算法,用于管理两层毫微微小区网络中的干扰,其中,新部署的毫微微小区用户(FUE)使用码分倍数与现有的宏小区用户(MUE)共享相同的频带接入(CDMA)。作为授权无线电频谱的所有者,MUE具有比FUE严格更高的访问优先级;因此,必须始终保持以规定的最小信噪比(SINR)表示的服务质量(QoS)性能。对于较低层的FUE,我们明确考虑了两个不同的设计目标,即吞吐量-功耗权衡优化和软QoS设置。通过将有效的动态定价方案与准入控制相结合来间接管理跨层干扰,所提出的方案适用于分布式算法,这些算法主要需要本地信息来提供单个用户的最大净效用。这项工作中采用的方法特别有吸引力,尤其是考虑到在毫微微小区可用的有限回程网络容量下的实际实现。结果表明,所提出的算法在可行的情况下,以有保证的QoS要求,有力地支持了所有优先MUE,同时允许FUE最佳地利用剩余的网络容量。严格分析了所开发解决方案的收敛性,并给出了广泛的数值结果来说明其潜在的优势。

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