Efficient Downlink Channel Estimation Scheme Based on Block-Structured Compressive Sensing for TDD Massive MU-MIMO Systems

Abstract

Abstract-In this letter, an efficient channel estimation approach based on the emerging block-structured compressive sensing is proposed for the downlink massive multiuser (MU) MIMO system. By exploiting the channel properties of block sparsity and channel reciprocity in TDD mode, the auxiliary information based block subspace pursuit (ABSP) algorithm is proposed to recover the downlink channels, where the path delays acquired from uplink training is utilized as the auxiliary information. Unlike traditional approaches where the channel estimation overhead is proportional to the number of BS antennas, the proposed approach could provide an accurate channel estimation approaching the performance bound while reduce the pilot overhead by nearly one-third.Index Terms-Massive MU-MIMO, channel estimaion, block compressive sensing.

Weighted compressive sensing based uplink channel estimation for time division duplex massive multi‐input multi‐output systems

“…The distance between two adjacent antennas is d = λ 2 = 0.058m. Hence, the maximum distance between two BS antennas is D = 15d = 0.87m (D is a function of the antenna spacing d and the number of antennas in the array), while d max = c 10B = 3.96m which is much larger than D. As a result, the BS uplink channels share the common support S i , i.e., [10].…”

“…Therefore, according to the law of large numbers, it is more likely to capture the correct path delays since the antennas share information with each other to reach a decision on the most probable support (see more details in our previous work [10]). …”

“…7(b) that the channel estimation performance improves as M increases. This is because that the BS antennas could coordinate with each other and reach a decision on the most probable channel support for channel estimation (i.e., Line 5 and Line 7 of Algorithm 1) [10]. Thus, according to the law of large numbers, more coordinated BS antennas could provide more accurate support detection, as long as Observation II is satisfied.…”

“…[7]- [9] proposed the modified basis pursuit (MBP) utilizing the a priori signal support. In [10], the Auxiliary information based Block Subspace Pursuit (ABSP) is proposed, which utilizes the previous channel support to initialize the estimated support for subspace pursuit algorithm. However, using the a priori support information directly may lead to even worse performance when the channel is fast varying, since the path delays may change from their previous locations.…”

An Efficient Downlink Channel Estimation Approach for TDD Massive MIMO Systems

“…In [4], block based orthogonal matching pursuit scheme is proposed for downlink massive multiple-input single-output (MISO) systems. In order to further improve the channel estimation, the authors in [2] exploit the channel reciprocity in time division duplex (TDD) mode whereby the user terminals (UTs) could utilize the channel support estimated from the uplink training to enhance the downlink channel estimation [2]. Based on this idea, they propose the Auxiliary information based Block Subspace Pursuit (ABSP) algorithm.…”