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Message-Passing Receiver for Joint Channel Estimation and Decoding in 3D Massive MIMO-OFDM Systems | IEEE Journals & Magazine | IEEE Xplore

Message-Passing Receiver for Joint Channel Estimation and Decoding in 3D Massive MIMO-OFDM Systems


Abstract:

In this paper, we address the design of message-passing receiver for massive multiple-input multiple-output orthogonal frequency division multiplex (MIMO-OFDM) systems. W...Show More

Abstract:

In this paper, we address the design of message-passing receiver for massive multiple-input multiple-output orthogonal frequency division multiplex (MIMO-OFDM) systems. With the aid of the central limit argument and Taylor-series approximation, a computationally efficient receiver that performs joint channel estimation and decoding is devised by the framework of expectation propagation. In particular, the local belief defined at the channel transition function is expanded up to the second order with Wirtinger calculus, to transform the messages sent by the channel transition function to a tractable form. As a result, the channel impulse response between each pair of antennas is estimated by Gaussian message passing. In addition, a variational expectation-maximization-based method is derived to learn the channel power-delay profiles. The proposed scheme is assessed in 3D massive MIMO-OFDM systems with spatially correlated channels, and the empirical results corroborate its superiority in terms of performance and complexity.
Published in: IEEE Transactions on Wireless Communications ( Volume: 15, Issue: 12, December 2016)
Page(s): 8122 - 8138
Date of Publication: 22 September 2016

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I. Introduction

Recently, massive multiple-input multiple-output (MIMO) systems with tens to hundreds of antennas at the base-station (BS) have gained significant attention [1]. It has been proved that massive MIMO systems can scale down transmit power as well as increase spectrum efficiency by orders of magnitude [2]. One of the challenges in massive MIMO systems is estimating the channel impulse response (CIR) for each transmit-receive link, since high data rates and energy efficiency can only be achieved when CIR is known [3], [4]. In contrast to the conventional MIMO systems with a small number of antennas, a large number of channel parameters need to be estimated in massive MIMO systems. In the meantime, the available pilot resources for channel estimation are restricted by the channel coherence time [5]. Hence, the pilot overhead may be one of the limiting factors in massive MIMO systems [1], [6]. On the other hand, the energy consumption by baseband processing grows with the number of antennas, which may obliterate the advantage of massive MIMO systems in energy efficiency. Thus, low-complexity receiver with reduced overhead is critical to massive MIMO systems.

References

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