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On Capacity-Achieving Distributions for Complex AWGN Channels Under Nonlinear Power Constraints and Their Applications to SWIPT

机译:在非线性功率约束下复杂AWGN通道的能力 - 实现分布及其应用于SWIPT

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The capacity of a complex and discrete-time memoryless additive white Gaussian noise (AWGN) channel under three constraints, namely, input average power, input amplitude and output delivered power is studied. The output delivered power constraint is modelled as the average of linear combination of even moments of the channel input being larger than a threshold. It is shown that the capacity of an AWGN channel under transmit average power and receiver delivered power constraints is the same as the capacity of an AWGN channel under an average power constraint. However, depending on the two constraints, the capacity can be either achieved by a Gaussian distribution or arbitrarily approached by using time-sharing between a Gaussian distribution and On-Off Keying. As an application, a simultaneous wireless information and power transfer (SWIPT) problem is studied, where an experimentally-validated nonlinear model of the harvester is used. It is shown that the delivered power depends on higher order moments of the channel input. Two inner bounds, one based on complex Gaussian inputs and the other based on further restricting the delivered power are obtained for the Rate-Power (RP) region. For Gaussian inputs, the optimal inputs are zero mean and a tradeoff between transmitted information and delivered power is recognized by considering asymmetric power allocations between inphase and quadrature subchannels. Through numerical algorithms, it is observed that input distributions (obtained by restricting the delivered power) attain larger RP region compared to Gaussian input counterparts. The benefits of the newly developed and optimized input distributions are also confirmed and validated through realistic circuit simulations. The results reveal the crucial role played by the energy harvester (EH) nonlinearity on SWIPT and provide new engineering guidelines on how to exploit this nonlinearity in the design of SWIPT modulation, signal and architecture.
机译:研究了三个约束下的复杂和离散时间内记忆添加剂白色高斯噪声(AWGN)通道的容量,即输入平均功率,输入幅度和输出功率。输出传递功率约束被建模为即使是通道输入的偶数矩的线性组合的平均值大于阈值。结果表明,发射平均功率和接收器的功率约束下的AWGN信道的容量与平均功率约束下的AWGN信道的容量相同。然而,取决于两个约束,可以通过使用高斯分布与开关键控之间的时间共享来实现容量或通过使用时间共享来实现。作为应用,研究了同时无线信息和电力传输(SWIPT)问题,其中使用了收割机的实验验证的非线性模型。结果表明,交付的功率取决于通道输入的更高阶的矩。基于复杂高斯输入的两个内部界限,基于进一步限制输送功率的另一个内部界限是针对速率 - 功率(RP)区域的进一步限制输送电力。对于高斯输入,最佳输入是零均值,并且通过考虑inphase和正交子信道之间的不对称功率分配来识别所发送的信息和传送电力之间的折衷。通过数值算法,观察到与高斯输入对应物相比,通过限制较大的RP区域来观察到输入分布(通过限制传送的电源而获得。通过现实的电路模拟,还确认并验证了新开发和优化的输入分布的好处。结果揭示了能源收割机(EH)非线性在Swipt上发挥的至关重要作用,并为如何利用SWIPT调制,信号和架构设计的如何利用这种非线性提供新的工程准则。

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