Abstract
This article proposes a novel postcoding design scheme for suppressing inter-user interference (IUI) and inter-cell interference (ICI) in uplink multiuser massive multiple-input multiple-output (MIMO) system in time-varying channel environments. In the uplink system, the base station (BS) designs postcoding weight based on estimated channel state information (CSI) to suppress IUI. When user terminals move, the estimated CSI is outdated because actual channels vary with time. This causes IUI and leads to degrading the system capacity. Besides, ICI extensively arises in multiuser massive MIMO systems since many users are simultaneously supported in each cell. The accuracy of CSI estimates is degraded since ICI contaminates the uplink pilot sequences from desired users. Adopting a weight design based on minimum mean square error (MMSE) criteria, we can suppress ICI adequately, and exploiting plentiful degrees of freedom (DoFs) of massive array, we can also suppress IUI even in time-varying channels by steering many nulls for one user based on null-space expansion (NSE) scheme. The computer simulations clarify that the proposed scheme has superior SINR performance in Rayleigh fading channel at low speed, low SIR, and high SNR regions while it is effective at almost all conditions in Rician fading channel.
Highlights
The spread of the number of mobile terminals such as smartphones, PCs, and tablets has led to an explosion in data traffic
The carrier frequency is set to 28 GHz which is licensed for the 5G system
This article proposed a novel interference suppression scheme for uplink multiuser massive multiple-input multiple-output (MIMO) systems based on null-space expansion and minimum mean square error (MMSE)-sample matrix inversion (SMI) algorithm, under the time-varying channel environment as well as unknown interference existence
Summary
The spread of the number of mobile terminals such as smartphones, PCs, and tablets has led to an explosion in data traffic. In a cellular-based uplink multiuser MIMO system, BS estimate channel state information (CSI) from the pilot signal transmitted by the desired user in the target cell. As for the data-aided interference suppression schemes related to massive MIMO systems, its main target is to overcome the pilot contamination problem These methods are completely blind [22] or semi-blind [23], [24] approaches that utilize many received data in addition to the pilot signal in order to estimate both intra-cell and inter-cell CSI. CONTRIBUTION Based on the above background, a joint application of NSE and adaptive algorithms brings us expectations to deliver a promising solution against the extensive co-channel interference problem We address this issue to realize the effective and generic use of spectrum resources in mobile communications.
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