Channel Estimation for Frequency Division Duplexing Multi-user Massive MIMO Systems via Tensor Compressive Sensing

Abstract

To make full use of space multiplexing gains for the multi-user massive multiple-input multiple-output, accurate channel state information at the transmitter (CSIT) is required. However, the large number of users and antennas make CSIT a higher-order data representation. Tensor-based compressive sensing (TCS) is a promising method that is suitable for high-dimensional data processing; it can reduce training pilot and feedback overhead during channel estimation. In this paper, we consider the channel estimation in frequency division duplexing (FDD) multiuser massive MIMO system. A novel estimation framework for three dimensional CSIT is presented, in which the modes include the number of transmitting antennas, receiving antennas, and users. The TCS technique is employed to complete the reconstruction of three dimensional CSIT. The simulation results are given to demonstrate that the proposed estimation approach outperforms existing algorithms.

Secret Key Generation Schemes for Physical Layer Security

“…(i) Channel sounding :Channel sounding 11 is the technique by which peers involved in wireless transmission and reception assess the channel by means of transmitting symbols referred to as pilot symbols. Received signal strength indicator (RSSI), channel impulse response (CIR), channel frequency response (CFR) are some of the examples.…”