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Robust cognitive beamforming for cell-edge coverage in multicell networks with probabilistic constraints

机译:具有概率约束的多小区网络中的细胞边缘覆盖的鲁棒认知波束形成

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In this paper, we introduce a downlink beamforming strategy in a cognitive cell located at the boarder of two adjacent cells of a multicell network to support the local cell-edge users of both cells. The proposed strategy is formulated as an optimization problem to minimize a linear combination of total transmit power of the cognitive base station (BS) and the resulting total interference on the other users located outside of the cognitive cell, so that the signal-to-interference-plus-noise ratio (SINR) targets of the cell-edge users are maintained. In a realistic scenario where CSI may be imperfect, the beamforming design for the cognitive BS based on perfect channel state information (CSI) can easily end up violating the tolerable interference levels of the users falling outside of the cognitive cell. We reformulate the proposed strategy as a robust optimization problem with outage-probability based constraints to account for the imperfection in CSI. Using the S-Procedure, we transform the intractable probabilistic constraints to a computationally tractable set of conservative deterministic constraints. Finally, applying the rank relaxation, we rewrite the resulting problem in semidefinite programming (SDP) form that can be solved using the standard convex optimization packages. The simulation results confirm the effectiveness of the proposed robust scheme in power-efficiently expanding the range of achievable SINR targets for the cell-edge users.
机译:在本文中,我们在位于多小区网络中两个相邻小区边界的认知小区中引入下行链路波束成形策略,以支持两个小区的本地小区边缘用户。提出的策略被表述为优化问题,以最大程度地减少认知基站(BS)的总发射功率与对位于认知小区外部的其他用户的总干扰的线性组合,从而使信号干扰保留了小区边缘用户的超高噪声比(SINR)目标。在CSI可能不完美的现实情况下,基于完美信道状态信息(CSI)的认知BS的波束成形设计可能很容易违反违反认知小区的用户可容忍的干扰水平。我们将提出的策略重新构造为具有基于中断概率的约束的鲁棒优化问题,以解决CSI中的缺陷。使用S程序,我们将难处理的概率约束转换为一组计算易处理的保守确定性约束。最后,应用秩松弛,我们以半定型编程(SDP)形式重写结果问题,可以使用标准凸优化包解决该问题。仿真结果证实了所提出的鲁棒方案在功率有效地扩展小区边缘用户可实现的SINR目标范围方面的有效性。

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