Efficient Non-linear Equalization for 1-bit Quantized Cyclic Prefix-Free Massive MINO Systems

This paper addresses the problem of data detection for a massive Multiple-Input-Multiple-Output (MINO) base station which utilizes 1-bit Analog-to-Digital Converters (ADCs) for quantizing the uplink signal. The existing literature on quantized massive MINO systems deals with Cyclic Prefix (CP) transmission over frequency-selective channels. In this paper, we propose a computationally efficient block processing equalizer based on the Expectation Maximization (EM) algorithm in CPfree transmission for 1-bit quantized systems. We investigate the optimal block length and overlapping factor in relation to the Channel Impulse Response (CIR) length based on the Bit Error- Rate (BER) performance metric. As EM is a non-linear algorithm, the optimal estimate is found iteratively depending on the initial starting point of the algorithm. Through numerical simulations we show that initializing the EMalgorithm with a Wiener-Filter (WF) estimate, which takes the underlying quantization into account, achieves superior BERperformance compared to initialization with other starting points.