具有硬件损伤的干扰辅助能量收集短分组通信

Dechuan Chen , Jin Li , Jianwei Hu , Xingang Zhang , Shuai Zhang , Dong Wang
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引用次数: 0

摘要

射频能量采集为低功耗物联网(IoT)设备提供了一种前景广阔的解决方案,它能为设备提供方便、持久的能量供应。在这项工作中,我们研究了能量受限的发射器与接收器在中上信道上通信的可靠性能,其中共同考虑了收发器硬件损伤和有限块长编码的影响。具体来说,发射器和接收器之间的通信链路在现有无线系统的覆盖范围内运行,现有系统的射频信号作为发射器的能量信号,同时作为接收器的干扰信号。通过利用有限块长信息理论,我们首先以闭式表达式推导出平均块误码率(BLER)和渐近平均 BLER,从而量化了可靠性损失的程度。然后,我们分析了系统的有效吞吐量,并确定了使有效吞吐量最大化的最佳分块长度。我们利用计算机模拟来验证我们分析结果的准确性,证明了仅由硬件损伤导致的中断阈值的存在。此外,如果传输速率超过由硬件损伤程度定义的中断阈值,则无论传输信噪比(SNR)如何,都无法在所考虑的系统内实现可靠的通信。
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Interference-assisted energy harvesting short packet communications with hardware impairments

Radio frequency energy harvesting offers a promising solution to provide low power Internet of Things (IoT) devices with convenient and perpetual energy supply. In this work, we investigate the reliable performance of an energy-constrained transmitter communicating with a receiver over Nakagami-m channel, where the effects of transceiver hardware impairments and finite blocklength coding are jointly considered. Specifically, the communication link between the transmitter and receiver operates within the coverage of an existing wireless system, with radio frequency signal from the existing system serving as an energy signal for the transmitter while acting as an interference signal for the receiver. By utilizing the finite-blocklength information theory, we first derive average block error rate (BLER) and asymptotic average BLER in closed-form expressions, which enable us to quantify the extent of reliability loss. Then, we analyze effective throughput of the system, and determine the optimal blocklength that maximizes the effective throughput. Computer simulations are employed to validate the accuracy of our analytical findings, demonstrating the presence of an outage threshold solely due to hardware impairments. Furthermore, if transmission rate exceeds the outage threshold defined by the level of hardware impairments, reliable communication within the system under consideration cannot be achieved, regardless of the transmit signal-to-noise ratio (SNR).

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