In this paper, we optimize a Wireless Information and Power Transfer (WIPT) system including multiple pairs of users, where transmitters employ a single-antenna to transmit their information and power to their receivers with the help of one multiple-antenna Amplify-and-Forward (AF) relay or an active Intelligent Reflecting Surface (IRS). We propose a joint Time Switching (TS) scheme in which transmitters, receivers, and the relay/IRS are either in their energy or information transmission/reception modes. The transmitted multi-carrier unmodulated and modulated waveforms are used for Energy Harvesting (EH) and Information Decoding (ID) modes, respectively. In order to design an optimal fair system, we maximize the minimum rate of all pairs for both relay and IRS systems through a unified framework. This framework allows us to simultaneously design energy waveforms, find optimal relay/IRS amplification/reflection matrices, allocate powers for information waveforms, and allocate time durations for various phases. This problem turns out to be non-convex. Thus, we propose an iterative algorithm by using the Minorization-Maximization (MM) technique, which efficiently converges to the optimized solution, i.e., stationary point of the problem (under mild conditions). Numerical examples show that the proposed method improves the performance of the multi-pair WIPT relay/IRS system under various setups.

We investigate a partially blind channel estimation and symbol detection in an amplify-and-forward two way relay scheme. We derive generalized likelihood ratio test detectors for reciprocal and non-reciprocal channels, whose computational complexity (CC) grow exponentially with the block length. Therefore, we propose a convergent iterative method for joint channel estimation and symbol detection with CC proportional to the block length. We also address the convergence proof. We further propose the simple blind and partially-blind approaches based on least squares (LS) and weighted LS estimation, respectively, for operation at low SNRs and analyze their mean square errors (MSE). Our simulations reveal the effectiveness of the proposed method compared with its counterparts.

Two‐way relaying tends to become a celebrated technique in communication networks because of its unique characteristic in establishing a two‐step bilateral information exchange mechanism between users' pairs, as well as, arranging a virtual spatial diversity scenario. In this paper, two‐way relaying under amplify‐and‐forward strategy, and fast Rayleigh fading environment is considered. We investigate two distinct cases in which the relay retransmits users' superposed signals, either directly or after complex conjugation in two‐ or three‐phase modalities. We derive the optimal detection rule which is inherently computational complex. Two closed‐form suboptimal structures are proposed to circumvent this formidable problem. In the first form, we incorporate the destination noise into the relay counterpart, and assume Gaussian conditional distribution for the received signal in the latter. The first detector is designed using less stringent approximation and consequently has a better performance, whereas the second one benefits from a very low computational complexity and simple implementation and is more suitable for applications with strict computational and energy constraints such as sensor networks. Furthermore, we consider the imperfect self‐channel information case and extend the corresponding results. Bit error rate analyses and accompanying computer simulations show an improvement of about 5 dB over existing methods.

We consider the problem of sum-rate maximization in massive MIMO two-way relay networks with multiple (communication) operators employing the amplify-and-forward (AF) protocol. The aim is to design the relay amplification matrix (i.e., the relay beamformer) to maximize the achievable communication sum-rate through the relay. The design problem for the case of single-antenna users can be cast as a non-convex optimization problem, which in general, belongs to a class of NP-hard problems. We devise a method based on the minorization-maximization technique to obtain quality solutions to the problem. Each iteration of the proposed method consists of solving a strictly convex unconstrained quadratic program; this task can be done quite efficiently such that the suggested algorithm can handle the beamformer design for relays with up to ∼ 70 antennas within a few minutes on an ordinary PC. Such a performance lays the ground for the proposed method to be employed in massive MIMO scenarios.

We investigate non-coherent detection of $M$ -ary orthogonal signaling in a denoise-and-forward two-way relay scheme in fast fading, as well as block fading channels. We first design the maximum likelihood, as well as maximum a-posteriori detectors, and then propose a simple suboptimal version for this digital network coding system in Rayleigh fast fading environment. We find exact expression of bit error rate for this suboptimal detector. Interestingly, this suboptimal detector performs only less than 0.25 dB away from optimum, i.e., this expression is a tight upper bound for the performance of the optimal one. Moreover, we derive the optimal detector for the case where the channel amplitudes are known at the relay. To make this detector practical, we propose efficient estimators for the channel amplitudes at the relay for block fading environments. Finally, our simulations reveal the effectiveness of the proposed methods compared with the state-of-the-art method.

We consider the problem of sum-rate maximization in multiple-input multiple-output (MIMO) amplify-and-forward relay networks with multi-operator. The aim is to design the MIMO relay amplification matrix (i.e., the relay beamformer) to maximize the achievable communication sum rate through the relay. The design problem for the case of single-antenna users can be cast as a non-convex optimization problem, which, in general, belongs to a class of NP-hard problems. We devise a method based on the minorization–maximization technique to obtain quality solutions to the problem. Each iteration of the proposed method consists of solving a strictly convex unconstrained quadratic program. This task can be done quite efficiently, such that the suggested algorithm can handle the beamformer design for relays with up to$\sim 70$antennas within a few minutes on an ordinary personal computer. Such a performance lays the ground for the proposed method to be employed in medium-scale (or lower regime massive) MIMO scenarios.

In this study, a new method is proposed for channel estimation and symbol detection in amplify‐and‐forward two‐way relay networks with frequency shift keying signalling, over block fading as well as time‐varying Rayleigh flat fading channels. It relies solely on information symbols to estimate reciprocal and non‐reciprocal channels without pilot symbols assistance. To achieve this goal, users apply known periodic phase shifts to their transmit symbols and adopt maximum likelihood or linear minimum mean square error criteria to discriminate and estimate the two composite channels. Optimal and suboptimal phase shifts are designed to minimise the mean square error (MSE). Minimum distance receiver is then used for symbol detection. An approximate upper bound for the resulting bit error rate (BER) is derived and the effect of channel variation rate on the MSE and BER is studied. Finally, simulation results are provided to verify the effectiveness of the suggested method.