Gaussian orthogonal relay channels: optimal resource allocation and capacity
Gaussian orthogonal relay channels: optimal resource allocation and capacity
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DOI：
10.1109/tit.2005.853305
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发表时间：
2005-09
影响因子：
2.5
通讯作者：
Yingbin Liang;V. Veeravalli
中科院分区：
文献类型：
--
作者：
Yingbin Liang;V. Veeravalli
研究了高斯正交中继模型，其中信源在信道1中向中继器和目的地发送，中继器在信道2中向目的地发送，其中信道1和2在时频平面上被正交化以满足实际约束。将总的可用信道资源(时间和带宽)分为两个正交信道，将两个信道的资源分配视为需要优化的设计参数。分析的主要焦点是源到中继链路比源到目的链路更好的情况，这是实践中遇到的通常情况。推导了容量(可达速率)的下界，并在参数/SPL_(？)上进行了优化，该参数表示分配给信道1的资源的比例。结果表明，该下界在优化/_(SPL)_(？)时达到最大流最小截断上限，因此公共值是在优化/_(SPL)_(？)时的信道容量。此外，证明了当中继信噪比(SNR)小于某一阈值时，在所有可能的资源分配参数/SPLθ/下，优化/SPLθ/时的容量也是信道的最大容量。最后，比较了最优资源分配和平均资源分配的可实现速率，结果表明，优化资源分配可以显著提高性能。
A Gaussian orthogonal relay model is investigated, where the source transmits to the relay and destination in channel 1, and the relay transmits to the destination in channel 2, with channels 1 and 2 being orthogonalized in the time-frequency plane in order to satisfy practical constraints. The total available channel resource (time and bandwidth) is split into the two orthogonal channels, and the resource allocation to the two channels is considered to be a design parameter that needs to be optimized. The main focus of the analysis is on the case where the source-to-relay link is better than the source-to-destination link, which is the usual scenario encountered in practice. A lower bound on the capacity (achievable rate) is derived, and optimized over the parameter /spl theta/, which represents the fraction of the resource assigned to channel 1. It is shown that the lower bound achieves the max-flow min-cut upper bound at the optimizing /spl theta/, the common value thus being the capacity of the channel at the optimizing /spl theta/. Furthermore, it is shown that when the relay-to-destination signal-to-noise ratio (SNR) is less than a certain threshold, the capacity at the optimizing /spl theta/ is also the maximum capacity of the channel over all possible resource allocation parameters /spl theta/. Finally, the achievable rates for optimal and equal resource allocations are compared, and it is shown that optimizing the resource allocation yields significant performance gains.