With the goal of enabling ultrareliable and low-latency wireless communications for industrial internet of things (IIoT), this paper studies the use of energy-based modulations in noncoherent massive single-input multiple-output (SIMO) systems. We consider a one-shot communication over a channel with correlated Rayleigh fading and colored Gaussian noise, in which the receiver has statistical channel state information (CSI). We first provide a theoretical analysis on the limitations of unipolar pulse-amplitude modulation (PAM) in systems of this kind, based on maximum likelihood detection. The existence of a fundamental error floor at high signal-to-noise ratio (SNR) regimes is proved for constellations with more than two energy levels, when no (statistical) CSI is available at the transmitter. In the main body of the paper, we present a design framework for quadratic detectors that generalizes the widely-used energy detector, to better exploit the statistical knowledge of the channel. This allows us to design receivers optimized according to information-theoretic criteria that exhibit lower error rates at moderate and high SNR. We subsequently derive an analytic approximation for the error probability of a general class of quadratic detectors in the large array regime. Finally, we numerically validate it and discuss the outage probability of the system.

翻译：为实现工业物联网（IIoT）的超可靠低延迟无线通信，本文研究了非相干大规模单输入多输出（SIMO）系统中基于能量的调制方法。我们考虑在相关瑞利衰落和有色高斯噪声的信道中进行单次通信，其中接收端拥有统计信道状态信息（CSI）。首先，基于最大似然检测，从理论上分析了单极性脉冲幅度调制（PAM）在此类系统中的局限性。当发射端缺乏（统计）CSI且星座图包含两个以上能级时，我们证明了高信噪比（SNR）区域存在基本误码平层。本文主体部分提出了一个广义化能量检测器的二次检测器设计框架，以更充分利用信道统计知识。该框架使我们能够设计出根据信息论准则优化的接收机，在中高信噪比下实现更低的误码率。随后，我们推导了大规模阵列条件下一般二次检测器误码概率的解析近似表达式。最后通过数值仿真验证该近似，并讨论了系统的中断概率。