Blind estimation of MIMO relay channels

Abstract

In this paper, we integrate two blind source separation (BSS) methods to estimate the individual channel state information (CSI) for the source-relay and relay-destination links of three-node two-hop multiple-input multiple-output (MIMO) relay systems. In particular, we propose a first-order Zdomain precoding technique for the blind estimation of the relay-destination channel matrix, while an algorithm based on the constant modulus and mutual information properties is developed to estimate the source-relay channel matrix. Compared with training-based MIMO relay channel estimation approaches, our algorithm has a better bandwidth efficiency as no bandwidth is wasted for sending the training sequences. Numerical examples are shown to demonstrate the performance of the proposed algorithm.

Antijamming Schemes for the Generalized MIMO Y Channel

“…In that case, the channel between the source nodes and the relay could be estimated using 5G NR demodulation reference signal (DMRS), with the pattern being best suited to the given use case scenario. The channel coefficient vector between the jammer and the relay should be estimated based on the blind channel estimation, which can obtain CSI without a training sequence or pilots, as proposed in the following publications [38][39][40][41][42][43][44].…”

Security Performance Analysis of Relay Networks Based on κ - μ Shadowed Channels with RHIs and CEEs

“…As can be seen, the communication system of this model is divided into two time slots: (i) B sends the original signals to H; (ii) the H decodes the signals and forwards them to D. To improve the antieavesdropping ability, we have added artificial noise to the model. Since it is difficult to acquire the channel state information (CSI) of all nodes, the effective way to solve this problem is channel estimation which can be divided into three types, including reference signal-based estimation [38], blind estimation [39], and semiblind estimation [40]. The method used in this paper belongs to the first category that uses training sequences to estimate the CSI.…”