论文标题

功率自适应网络编码非正交多访问继电器频道

Power Adaptive Network Coding for a Non-Orthogonal Multiple-Access Relay Channel

论文作者

Wei, Sha, Li, Jun, Chen, Wen, Su, Hang, Lin, Zihuai, Vucetic, Branka

论文摘要

在本文中,我们为非正交多访问中继通道(MARC)提出了一种新颖的功率调整网络编码(PANC),其中两个来源在继电器的帮助下同时将其信息同时传输到目的地。与传统的基于XOR的网络编码(CXNC)不同,我们的PANC中的继电器通​​过考虑源到Relay通道的系数来生成网络编码的位,并以预先优化的功率水平向前转发。具体而言,通过将符号对定义为两个源的两个符号,我们首先得出系统的确切符号对错误率(SPER)。指出,由于由随机通道系数引起的决策区域的不规则性,确切的SPER的世代变得复杂,我们提出了一种坐标变换(CT)方法来简化SPER的衍生作用。接下来,我们证明,通过继电器的功率缩放因子,我们的panc方案可以实现系统的完全多样性增益,即系统的两阶多样性增益,而CXNC只能由于多用户干扰而获得一阶多样性增益。此外,我们优化了继电器处的功率水平,以等效地将目的地的SPER最小化,以使SPER与接收的星座的欧几里得距离之间的关系之间的关系。仿真结果表明,(1)基于我们的CT方法得出的SPER可以很好地近似具有较低复杂性的精确蜘蛛; (2)具有功率水平优化和功率缩放因子设计的PANC方案可以实现完全的多样性,并获得比随机选择功率水平的panc方案更高的编码增益。

In this paper we propose a novel power adapted network coding (PANC) for a non-orthogonal multiple-access relay channel (MARC), where two sources transmit their information simultaneously to the destination with the help of a relay. Different from the conventional XOR-based network coding (CXNC), the relay in our PANC generates network coded bits by considering the coefficients of the source-to-relay channels, and forwards each bit with a pre-optimized power level. Specifically, by defining a symbol pair as two symbols from the two sources, we first derive the exact symbol pair error rate (SPER) of the system. Noting that the generations of the exact SPER are complicated due to the irregularity of the decision regions caused by random channel coefficients, we propose a coordinate transform (CT) method to simplify the derivations of the SPER. Next, we prove that with a power scaling factor at relay, our PANC scheme can achieve full diversity gain, i.e., two-order diversity gain, of the system, while the CXNC can only achieve one-order diversity gain due to multi-user interference. In addition, we optimize the power levels at the relay to equivalently minimize the SPER at the destination concerning the relationship between SPER and minimum Euclidean distance of the received constellation. Simulation results show that (1) the SPER derived based on our CT method can well approximate the exact SPER with a much lower complexity; (2) the PANC scheme with power level optimizations and power scaling factor design can achieve full diversity, and obtain a much higher coding gain than the PANC scheme with randomly chosen power levels.

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