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Iterative Approaches for Massive MIMO Uplink Processing Under Imperfect Channel Conditions | IEEE Journals & Magazine | IEEE Xplore

Iterative Approaches for Massive MIMO Uplink Processing Under Imperfect Channel Conditions


Abstract:

Obtaining channel state information in massive multiple-input multiple-output (MIMO) systems is challenging because of significant multiple-access interference and very l...Show More

Abstract:

Obtaining channel state information in massive multiple-input multiple-output (MIMO) systems is challenging because of significant multiple-access interference and very limited resources available for channel estimation. Most existing equalization schemes for massive MIMO systems assume perfect channel knowledge at the receivers. When channel estimation error is present, however, significant performance degradation will be experienced, which has been demonstrated in the literature. In this paper, we model the maximum-likelihood channel estimation as the sum of real channel and random channel estimation error, and develop a minimum mean-square error (MMSE) based turbo equalization method conditioned on the channel estimate. We demonstrate that our newly developed iterative processing approach is a general expression, whereas existing methods can be viewed as special cases. We further derive an MMSE-sorted QR decomposition (MMSE-SQRD) based turbo equalization to further improve the performance for massive MIMO systems under large user numbers and severe channel estimation error conditions. Numerical results and performance comparison show that the proposed MMSE-based turbo equalization scheme greatly outperforms the existing schemes. With a large number of users being simultaneously served, our proposed MMSE-SQRD-based scheme can further enhance system performance over the MMSE-based turbo equalization scheme.
Published in: IEEE Transactions on Vehicular Technology ( Volume: 68, Issue: 4, April 2019)
Page(s): 3642 - 3654
Date of Publication: 15 February 2019

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I. Introduction

Yet the field trials and standard development for the 5th generation (5G) wireless communication systems are still undergoing, rapidly increasing interests have been gained in the related techniques from both academia and industry [1]–[6]. Among them, massive multiple-input multiple-output (MIMO) and millimeter wave communications, have been two promising candidate techniques [1]–[3], [7]–[9]. In massive MIMO systems, a large-scale antennas array will be deployed at the base station. As a result, the remarkable spacial diversity and multiplexing gain is achieved. This gain leads to the significantly improved system spectrum and energy efficiency by orders of magnitudes over single antenna systems [7], [8].

References

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