A Robust Semi-Blind Receiver for Joint Symbol and Channel Parameter Estimation in Multiple-Antenna Systems

Abstract

For multiple-antenna systems, the technologies of joint symbol and channel parameter estimation have been developed in recent works. However, existing technologies have a number of problems, such as performance degradation and the large cost of prior information. In this paper, a tensor space-time coding scheme in multiple-antenna systems was considered. This scheme allowed spreading, multiplexing, and allocating information symbols associated with multiple transmitted data streams. We showed that the received signal was formulated as a third-order tensor satisfying a Tucker-2 model, and then a robust semi-blind receiver was developed based on the optimized Levenberg–Marquardt (LM) algorithm. Under the assumption that the instantaneous channel state information (CSI) is unknown at the receiving end, the proposed semi-blind receiver jointly estimates the information symbol and channel parameters efficiently. The proposed receiver had a better estimation performance compared with existing semi-blind receivers, and still performed well when the channel became strongly correlated. Moreover, the proposed semi-blind receiver could be extended to the multi-user massive multiple-input multiple-output (MIMO) system for joint symbol and channel estimation. Computer simulation results were shown to demonstrate the effectiveness of the proposed receiver.

Semi-Blind Receivers for Multi-User Massive MIMO Relay Systems Based on Block Tucker2-PARAFAC Tensor Model

“…In addition, 64QAM is adopted to modulate information symbols. The channel matrices H M R in order to eliminate scaling ambiguities as in [26] and [38]. δ th = 1 × 10 −4 is chosen for the proposed TP-ALS receiver.…”

“…In addition, the two receivers avoid sending training sequences. The work [26] presents a robust semi-blind receiver based on the Tucker2 model for joint symbol and channel estimation. Notably, the semi-blind receiver in [26] can be developed into the multi-user massive MIMO system.…”

Doubly coupled nested tensor decompositions with application to multirelay multicarrier MIMO communication networks

“…For the case addressed in this paper, one transmitted symbol (s 1,1,1 ) is assumed to be known, as well as one channel coefficient of each relay-destination link (h (RD) 1,1,k ), for k = 1, ..., K. In practice, this a priori information can be obtained simply by using one pilot-symbol sent from each relay to the destination. A similar procedure was adopted in other works [11,47,52,53] in the context of relaying systems. For the DCNTD system, the ambiguity removal is implemented after Steps 3 and 7 of Algorithm 1, while for the DCNPD system, the ambiguity removal is carried out after Steps 3, 4, and 8 of Algorithm 2.…”

Singular Value Decomposition Channel Estimation in STBC MIMO-OFDM System

“…The advantages of this method are that it has low system complexity and improves the nonlinear effect of radio over fiber link. A robust semi-blind receiver combined with the Tucker-2 model was proposed in [21]. The proposed receiver has high spectral efficiency and can be used in multi-user massive MIMO systems.…”