In cooperative communication systems, multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying is a promising solution for upcoming wireless standards due to its intrinsic benefits in terms of extended coverage and increased spatial diversity. However, the deployment of MIMO AF relays faces some key challenges such as the need of channel state information (CSI) for the partial channels associated with the different communication links, which is required by some transmit optimization techniques. In this paper, we consider a one-way two-hop MIMO AF cooperative scheme employing space-time (ST) codings at the transmitter and relay nodes. First, we formulate a nested PARAFAC model for the tensor of signals received at destination. A theoretical study on the identifiability and uniqueness issues for the nested PARAFAC model is also carried out. Then, two iterative semi-blind receivers that exploit differently the algebraic properties of this model are formulated for a joint channel and symbol estimation at the destination. Uniqueness and least squares identifiability conditions are derived for these receivers, and their computational complexities are analyzed. Simulation results evaluate the bit error rate and the channel estimation accuracy obtained with the proposed semi-blind receivers, corroborating the performance improvements over recent semi-blind and supervised competitors, thanks to the use of a double Khatri-Rao coding associated with the source and relay nodes.

Semi-Blind Receivers for Non-Regenerative Cooperative MIMO Communications Based on Nested PARAFAC Modeling

One of the major challenges the mobile broadband community faces is the exponential increase in mobile data traffic, even more so, for cell-edge users. Thus, in a multitier network, the demand for high-speed and interference-free transmission and reception is inevitable. Beamforming (BF) is an advanced technology that offers a significantly improved solution to reduce the interference levels and improve the system capacity. Accordingly, the establishment of relays in mobile data networks has emerged spectral efficiency enhancements and cell capacity gains from an overall system perspective. This paper provides a comprehensive survey focused on the performance of adopted beamforming technique on MIMO relay networks that is expected to overcome crucial obstacles in terms of capacity and interference. The main objective is to point out the state-of-the-art research activity on BF techniques in MIMO relay networks, under various network performance challenges. Thereby, it focuses on recently developed procedures for interference modeling and mitigation, BF channel modeling, channel estimation and feedback, complexity and power consumption, adaptive BF for multiuser relaying, degrees of freedom, diversity issues, and spectral efficiency, in cooperative and opportunistic systems. Different network topologies have been considered and categorized, pertaining the challenges of BF implementation in MIMO relay networks.

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A Survey on Beamforming Techniques for Wireless MIMO Relay Networks

This paper investigates the relay-assisted wireless information and power transfer enabled hybrid visible light communication (VLC)-radio frequency (RF) network, where a light emitting diode (LED) access point (AP) serves multiple information users (IUs) and multiple energy harvesting users (EHUs). IUs are allowed to receive information from the LED AP through time-division-multiple-access (TDMA) manner by either the single-hop VLC-ONLY mode or the relay-assisted dual-hop VLC-RF mode, while EHUs harvest energy via the VLC links. An optimization problem is formulated to maximize the achievable information rate of IUs by jointly optimizing the access mode selection, the direct current (DC) offset at the LED AP, the peak amplitude of the alternating current (AC) component at the LED AP, the electrical power allocated to the LED AP and the power allocation at relay, subject to the energy harvesting (EH) requirement constraints of EHUs. To tackle the non-convex problem with binary variables, we first decompose it into two subproblems in terms of the two access modes. Then, the subproblems are equivalently transformed and solved by the proposed successive convex approximation (SCA)-based algorithms. Simulation results show that significant performance gain can be achieved by optimizing the DC offset. It is also observed that the area where the VLC-ONLY mode is superior to the VLC-RF mode is enlarged with the decrease of the minimal EH requirement. Besides, the achievable information rate of IUs by the VLC-RF mode first increases and then decreases with the increment of the distance between the relay and the LED AP.

Achievable Information Rate in Hybrid VLC-RF Networks With Lighting Energy Harvesting

We propose a unified approach to transceiver optimization for nonregenerative multiple-input–multiple-output (MIMO) relay networks. This approach leads to new transceiver designs and reduces algorithmic complexity with adaptive implementations. First, we formulate a generic system model that accommodates various network topologies by imposing structural constraints on the source precoder, the relaying matrix, and the destination equalizer. Based on the minimum-mean-square-error (MMSE) criterion, we derive the optimal relaying matrix as a function of the other two matrices, thereby freeing the optimization problem from this matrix and its associated power constraint with no loss of optimality. Subsequently, we study how to optimize either the precoder or the equalizer under different structural constraints and propose an alternating algorithm for the joint design. When optimizing the equalizer, the optimum from the previous transmission block is chosen as the initial search point to speed up convergence and, hence, to reduce computational complexity. The proposed framework is further explained and numerically validated within the context of different system configurations.

A Unified Approach to Optimal Transceiver Design for Nonregenerative MIMO Relaying

This paper studies a multiple-input multiple-output (MIMO) broadcast relay channel (BRC), in which a multiple-antenna base station (BS) communicates with multiple-antenna users through an infrastructure-based multiple-antenna relay station (RS). Applying dirty paper coding (DPC) at the BS and linear processing at the RS, our aim is to find the input covariance matrices and the RS beamforming matrix that maximize the system sum-rate. To solve this non-convex problem, a more tractable dual multiple access relay channel (MARC) is investigated and an alternating-minimization algorithm is proposed. Furthermore, the mapping from the resulting covariance matrices for the MARC to the covariance matrices for the BRC is derived. Unlike other existing single-antenna-user schemes, our solution is applicable to a more general network with any number of antennas at the users. Compared with two such single-antenna-user schemes, simulations show that the proposed scheme outperforms the all-pass relay design and performs similarly to the SVD-relay design. Moreover, the proposed design performs close to the sum-rate upper bound with the performance gap decreasing with increasing number of antennas per user. It is also observed that having more antennas at the RS than at the BS is desirable for better system performance.

Beamforming in Non-Regenerative MIMO Broadcast Relay Networks

In this work, we study joint user-relay selection and association in multi-user multi-relay cooperative wireless relay uplinks with multi-antenna nodes. For non-regenerative and altruistic relays we propose a low-complexity joint scheme, which simultaneously selects multiple relays and users for cooperation as well as assigns the selected users to different selected relays for service. The proposed scheme is sub-optimal and utilizes only the channel gains between the nodes, which leads to reduced feedback and overhead in comparison to schemes that require full channel knowledge. Furthermore, the complexity of the scheme scales linearly as the product of the total number of relays, the total number of users and the number of selected users. Simulation results demonstrate the superiority of the proposed joint scheme compared to a scheme with neither user-relay selection nor user-relay association and another scheme with user-relay association, but no user-relay selection. The favorable performance and low-complexity of the proposed scheme make it very attractive for possible implementation in emerging broadband wireless relay networks (e.g., LTE-Advanced).

A Novel Low-Complexity Joint User-Relay Selection and Association for Multi-User Multi-Relay MIMO Uplink

This paper studies a multiple-input multiple-output (MIMO) broadcast relay channel (BRC) in which a multiple-antenna base station (BS) communicates with multiple-antenna users through a fixed infrastructure-based multiple-antenna relay station (RS) Applying dirty paper coding (DPC) at the BS and linear processing at the RS, our goal is to find the optimal input covariance matrices at the BS and the beamforming matrix at the RS that jointly maximize the system sum-rate To solve the optimization problem, a more tractable dual multiple access relay channel (MARC) is investigated and an iterative algorithm is proposed to obtain the optimal matrices for the dual system The mapping from the resulting covariance matrices for the MARC to the covariance matrices for the original BRC is derived Unlike other existing MIMO BRC schemes, designed for networks with single-antenna users only, our solution is applicable to networks with multiple-antenna users Compared with two such single-antenna-user schemes, simulations show that the proposed scheme outperforms the all-pass relay design and performs similar to the SVD-relay design Also, the proposed design performs close to a sum-rate upper bound with the gap decreasing with increasing number of users' antennas

Beamforming in MIMO broadcast relay networks with multiple antenna users

In this paper we study a cellular network, in which multiple-antenna users communicate with multiple-antenna base stations (BSs) through fixed infrastructure-based multiple antenna relay stations (RSs). With cooperation among the BSs and linear processing at the RSs, we aim to find the optimal precoding matrices at the users and the beamforming matrices at the RSs that jointly maximize the system sum rate. Unlike for the conventional uplink (without relays), the sum-rate optimization is non-convex. More so, there is cross-coupling of the RSs' channels due to the forwarded interferences by the RSs. Firstly, we incorporate interference pre-cancelation into the RSs' beamforming designs. Secondly, we match each RS's beamforming matrix to the corresponding backward and forward channels such that the end-to-end channel is diagonalizable. Furthermore, we propose an iterative alternating minimization based algorithm to maximize the system sum rate. Finally, we consider two user-RS scheduling/mapping schemes namely the “random” and “channel-aware” schemes. Simulation results show that the channel-aware scheme outperform the random scheme with the performance gap unchanged with increasing number of antennas at the nodes.

Godfrey O. Okeke

Papers

Beamforming in Non-Regenerative MIMO Broadcast Relay Networks

A Novel Low-Complexity Joint User-Relay Selection and Association for Multi-User Multi-Relay MIMO Uplink

Beamforming in MIMO broadcast relay networks with multiple antenna users

Distributed beamforming in multi-cell cooperative MIMO Cellular Networks with non-regenerative relays: An LTE-Advanced framework