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Power allocation for block-fading channels with arbitrary input constellations

机译:具有任意输入星座图的衰落信道的功率分配

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摘要

We consider power allocation strategies for arbitrary input channels with peak, average and peak-to-average power ratio (PAPR) constraints. We are focusing on systems with a fixed and finite input constellation, as encountered in most practical systems. Generalizing previous results, we derive the optimal power allocation scheme that minimizes the outage probability of block-fading channels with arbitrary input constellations, subject to PAPR constraints. We further show that the signal-to-noise ratio exponent for any finite peak-to-average power ratio is the same as that of the peak-power limited problem, resulting in an error floor. We also derive the optimal power allocation strategies that maximize the ergodic capacity for arbitrary input channels, subject to average and PAPR constraints.We show that capacities with peak-to-average power ratio constraints, even for small ratios, are close to capacities without peak-power restrictions. For both delay-limited and ergodic block-fading channels, the optimal power allocation strategies rely on the first derivative of the input-output mutual information, which may be computationally prohibitive for efficient practical implementation. To overcome this limitation, we develop suboptimal power allocation schemes that resemble the traditional water-filling technique. The suboptimal power allocation schemes significantly reduce computational and storage requirements, while enjoying minimal performance losses as compared to optimal schemes.
机译:我们考虑针对具有峰值,平均和峰均功率比(PAPR)约束的任意输入通道的功率分配策略。正如大多数实际系统中遇到的那样,我们专注于具有固定和有限输入星座的系统。概括先前的结果,我们得出了一种最佳功率分配方案,该方案将在PAPR约束下,将具有任意输入星座图的衰落信道的中断概率降至最低。我们进一步表明,任何有限的峰均功率比的信噪比指数与峰值功率受限问题的信噪比指数相同,从而导致误差底限。我们还推导出了最佳功率分配策略,该策略在受到平均和PAPR约束的情况下最大化了任意输入通道的遍历容量。我们证明了具有峰均功率比约束的容量(即使是小比率)也接近于没有峰值的容量-功率限制。对于延迟限制和遍历块衰落信道,最佳功率分配策略都依赖于输入输出互信息的一阶导数,这对于有效的实际实现可能在计算上是不利的。为了克服此限制,我们开发了类似于传统注水技术的次优功率分配方案。与最优方案相比,次优功率分配方案显着降低了计算和存储需求,同时享有最小的性能损失。

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