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This paper addresses the problem of data detection for a massiveMultiple-Input-Multiple-Output (MIMO) base station which utilizes 1-bitAnalog-to-Digital Converters (ADCs) for quantizing the uplink signal. Theexisting literature on quantized massive MIMO systems deals with Cyclic Prefix(CP) transmission over frequency-selective channels. In this paper, we proposea computationally efficient block processing equalizer based on the ExpectationMaximization (EM) algorithm in CP-free transmission for 1-bit quantizedsystems. We investigate the optimal block length and overlapping factor inrelation to the Channel Impulse Response (CIR) length based on the BitError-Rate (BER) performance metric. As EM is a non-linear algorithm, theoptimal estimate is found iteratively depending on the initial starting pointof the algorithm. Through numerical simulations we show that initializing theEM-algorithm with a Wiener-Filter (WF) estimate, which takes the underlyingquantization into account, achieves superior BER-performance compared toinitialization with other starting points.

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