Design of H-inf channel estimation in multi-cell MU-MIMO OFDM systems

Abstract

This paper investigates the uplink transmission in multi-cell multi-user multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The system model considers imperfect channel estimation, pilot contamination (PC), multiple sub-carriers and multi-path channels. We propose a simple H-inf channel estimation that achieves good suppression to PC. The approach exploits the space-alternating generalized EM (SAGE) iterative process to decompose multi-cell multi-user MIMO problem into a series of single-cell single-user SISO problems, which reduces the complexity drastically. Analysis on mean square error (MSE) of H-inf in the presence of PC is also presented. The numerical results show that increasing the number of pilot subcarriers cannot mitigate PC, and a clue for relieving PC can be obtained. The H-inf realizes better suppression to PC than the LS and ML algorithms. Its performance is close to the optimal MMSE algorithm and can be improved as the increase in the length of channel impulse response (CIR). By using the SAGE process, the performance of the H-inf does not degrade in case of a large number of antennas at base station (BS).

Iterative Joint Detection and Channel Estimation Algorithm for Large-scale MIMO System

“…The channel estimation algorithms have been extensively investigated and some approaches have been proved effective in suppressing and even eliminating the pilot contamination [3][4][5][6][7][8][9][10][11][12][13]. In Reference [3], a Bayesian estimation approach was presented.…”

“…Ref. [6] exploited the Space-Alternating Generalized Expectation-maximization (SAGE) iterative process to iteratively estimate the channel information. It focused to reduce the complexity and mitigate the pilot contamination.…”

On the use of H-inf criterion in channel estimation and precoding in massive MIMO systems

“…Define W = wI K , where w denotes the diagonal elements of W , and then w < s jj,DL is required. When W is fixed, the monotonic relations between s jj,UL and r jj,UL is generally presented [29]. Besides, in this paper, W is used in the uplink and downlink, and it is not difficult to find w < s jj,UL .…”

“…Since r jj,UL (r qj,UL ) and s jj,UL (s qj,UL ) have the monotonic relations [29], adjusting the value of s jj,UL (s qj,UL ) is equivalent to adjusting r jj,UL (r qj,UL ). Accordingly, the mitigation to PC can be implemented by adjusting the uplink thresholds s jj,UL and s qj,UL .…”

“…The performance of setting different thresholds in the uplink and downlink will be assessed in the following theoretical analyses and simulation experiments. According to [29,36], W is a diagonal matrix. Define W = wI K , where w denotes the diagonal elements of W , and then w < s jj,DL is required.…”