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Interference alignment in cognitive network with cooperative primary users

机译:合作主要用户在认知网络中的干扰对齐

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This paper considers a network consists of multiple primary users (PUs) and secondary users (SUs). To seek for the pre- and post-coding matrices of the PUs and SUs that improve the system output, the author applies Max-SINR algorithm for the PUs and cognitive interference alignment (IA) for the SUs. Then by counting the number of variables and the number of equations in the IA condition, this paper analyzes the achievable DoF of all users. Simulation results show that the PUs using max-SINR achieve higher rate than using standard IA with negligible SUs rate reduction.
机译:本文考虑了一个由多个主要用户(PU)和次要用户(SU)组成的网络。为了寻找可改善系统输出的PU和SU的预编码和后编码矩阵,作者将Max-SINR算法用于PU,并将SU应用于认知干扰对齐(IA)。然后,通过计算IA条件下的变量数量和方程数量,本文分析了所有用户可实现的DoF。仿真结果表明,使用max-SINR的PU可以获得比使用标准IA更高的速率,而SU速率降低可忽略不计。

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