Closed-Form Solutions to the Pareto Boundary and Distributed Beamforming Strategy for the Two-User MISO Interference Channel

Closed-Form Solutions to the Pareto Boundary and Distributed Beamforming Strategy for the Two-User MISO Interference Channel
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DOI:
10.1007/s11277-013-1007-1
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发表时间:
2013-01
影响因子:
2.2
通讯作者:
Jiamin Li;Dongming Wang;Pengcheng Zhu;Lan Tang;X. You
Jiamin Li;Dongming Wang;Pengcheng Zhu;Lan Tang;X. You
中科院分区:
计算机科学4区
文献类型:
--
作者:
Jiamin Li;Dongming Wang;Pengcheng Zhu;Lan Tang;X. You

文献摘要

相似文献

多输入单输出(MISO)干扰信道(IC)的可达速率域的外边界为Pareto边界,Pareto边界上的所有点都可以通过求解加权和速率最大化问题得到。不幸的是,由于优化问题是非凸的,它通常是很难获得的解决方案,而不执行穷举搜索。本文研究了两用户MISO集成电路的可达速率域。首先,通过最小化泄漏到另一个接收器的干扰功率,在预期接收器处接收的固定有用信号功率,非凸优化问题被转换成一族凸优化问题。其次,经过一些转换,所有Pareto最优点的封闭形式的解决方案,推导出拉格朗日对偶理论,所涉及的唯一计算是解决一个基本的二次方程。然后,进行天线降阶以进一步简化推导过程。为了避免基站之间的信道状态信息(CSI)的交换,分布式迭代波束形成策略,可以实现近似Pareto最优结果,只有几个迭代也被提出。最后,通过数值仿真验证了结果的正确性.
The outer boundary of the achievable rate region for multiple-input single-output (MISO) interference channel (IC) is Pareto boundary, and all points on the Pareto boundary can be obtained by solving weighted sum rate maximization problem. Unfortunately, since the optimization problem is non-convex, it is generally very difficult to obtain the solutions without performing an exhaustive search. In this paper, the achievable rate region of the two-user MISO IC is considered. Firstly, by minimizing the interference power leaked to the other receiver for fixed useful signal power received at the intended receiver, the non-convex optimization problem is converted into a family of convex optimization problems. Secondly, after some conversions, the closed-form solutions to all Pareto optimal points are derived using the Lagrange duality theory, and the only computation involved is to solve a basic quadratic equation. Then, the antenna reduction is performed to further simplify the process of derivation. In order to avoid the exchange of channel state information (CSI) between base stations, a distributed iterative beamforming strategy which can achieve a approximate Pareto optimal outcome with only a few iterations is also proposed. Finally, the results are validated via numerical simulations.