Multihop Nonregenerative MIMO Relays - QoS Considerations

For nonregenerative multihop multiple-input multiple-output (MIMO) relay communication systems, the optimal source precoding matrix and the optimal relay amplifying matrices have been recently established for a broad class of objective functions subjecting to the transmission power constraint at each node. However, existing works do not consider any quality-of-service (QoS) constraints, which are important in practical communication systems. In this paper, we derive the optimal source and relay matrices of a multihop MIMO relay system that guarantee the predetermined QoS criteria be attained with the minimal total transmission power. In particular, we consider two types of receivers at the destination node: the linear minimal mean-squared error (MMSE) receiver and the nonlinear decision feedback equalizer (DFE) based on the MMSE criterion. We show that for both types of receivers, the solution to the original optimization problem can be upper-bounded by using a successive geometric programming (GP) approach and lower-bounded by utilizing a dual decomposition technique. Simulation results show that both bounds are tight, and to obtain the same QoS, the MIMO relay system using the nonlinear MMSE-DFE receiver requires substantially less total transmission power than the linear MMSE receiver-based system

Robust MMSE beamforming for multiantenna relay networks

In this paper, we propose a robust minimum mean square error (MMSE) based beamforming technique for multiantenna relay broadcast channels, where a multi-antenna base station transmits signal to single antenna users with the help of a multiantenna relay. The signal transmission from the base station to the single antenna users is completed in two time slots, where the relay receives the signal from the base station in the first time slot and it then forwards the received signal to different users based on amplify and forward protocol. We propose a robust beamforming technique for sum-power minimization problem with imperfect channel state information (CSI) between the relay and the users. This robust scheme is developed based on the worst-case optimization framework and Nemirovski Lemma by incorporating uncertainties in the CSI. The original optimization problem is divided into three subproblems due to joint non-convexity in terms of beamforming vectors at the base station, the relay amplification matrix, and receiver coefficients. These subproblems are formulated into a convex optimization framework by exploiting Nemirovski Lemma, and an iterative algorithm is developed by alternatively optimizing each of them with channel uncertainties. In addition, we provide an optimization framework to evaluate the achievable worst-case mean square error (MSE) of each user for a given set of design parameters. Simulation results have been provided to validate the convergence of the proposed algorithm

Near-Optimal Energy-Efficient Joint Resource Allocation for Multi-Hop MIMO-AF Systems

Energy efficiency (EE) is becoming an important performance indicator for ensuring both the economical and environmental sustainability of the next generation of communication networks. Equally, cooperative communication is an effective way of improving communication system performances. In this paper, we propose a near-optimal energy-efficient joint resource allocation algorithm for multi-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) systems. We first show how to simplify the multivariate unconstrained EE-based problem, based on the fact that this problem has a unique optimal solution, and then solve it by means of a low-complexity algorithm. We compare our approach with classic optimization tools in terms of energy efficiency as well as complexity, and results indicate the near-optimality and low-complexity of our approach. As an application, we use our approach to compare the EE of multi-hop MIMO-AF with MIMO systems and our results show that the former outperforms the latter mainly when the direct link quality is poor

A Tutorial on the Optimization of Amplify-and-Forward MIMO Relay Systems

The remarkable promise of multiple-input multiple-output (MIMO) wireless channels has motivated an intense research activity to characterize the theoretical and practical issues associated with the design of transmit (source) and receive (destination) processing matrices under different operating conditions. This activity was primarily focused on point-to-point (single-hop) communications but more recently there has been an extensive work on two-hop or multi-hop settings in which single or multiple relays are used to deliver the information from the source to the destination. The aim of this tutorial is to provide an up-to-date overview of the fundamental results and practical implementation issues of designing amplify-and-forward MIMO relay systems

Radio Resource Management for Cellular Networks Enhanced by Inter-User Communication

The importance of radio resource management will be more and more emphasized in future wireless communication systems. For fair penetration of wireless services and for improved local services, inter-user communication has been receiving wide attention as it opens up various possibilities for user cooperation. The capability of inter-user communication imposes higher demands on radio resource management as additional considerations are needed. The demands for intelligent management of radio resources is also emphasized by the sparsity of radio resources. As the available spectral resources are assessed as under-utilized, much effort is devoted to developing advanced resource management methods for improving the spectral usage efficiency. The research of this thesis has contributed to the radio resource management for cellular networks enhanced by inter-user communication. Recognizing that inter-user communication can be used for message relaying or for direct communication purposes, two use cases are considered that leverage the synergy of users: cooperative relay selection and Device-to-Device (D2D) communication. We identify the importance of stochastic geometry consideration on cellular users for evaluating system performance in cooperative networking. We develop an algorithm for efficiently selecting cooperative users to maximize an End-to-End (e2e) performance metric. We analyze the optimal resource sharing problem between D2D communication and infrastructure-supported communication. We study the impact of imperfect Channel State Information (CSI) on the performance of systems with inter-user communication. Simulation results show that the performance of users with unfavorable propagation conditions can be improved with cooperative communication in a multi-cell cellular environment, at the expense of radio resources. Further, our results show that the selection of multiple cooperative users is beneficial in cases where the candidate cooperative users are spatially distributed. For resource sharing between the D2D and infrastructure-supported communication, our results show that the proposed resource sharing scheme enables higher intra-cell resource reuse without blocking the infrastructure-supported communication

Radio resource allocation in relay based OFDMA cellular networks

PhDAdding relay stations (RS) between the base station (BS) and the mobile stations (MS) in a cellular system can extend network coverage, overcome multi-path fading and increase the capacity of the system. This thesis considers the radio resource allocation scheme in relay based cellular networks to ensure high-speed and reliable communication. The goal of this research is to investigate user fairness, system throughput and power consumption in wireless relay networks through considering how best to manage the radio resource. This thesis proposes a two-hop proportional fairness (THPF) scheduling scheme fair allocation, which is considered both in the first time subslot between direct link users and relay stations, and the second time subslot among relay link users. A load based relay selection algorithm is also proposed for a fair resource allocation. The transmission mode (direct transmission mode or relay transmission mode) of each user will be adjusted based on the load of the transmission node. Power allocation is very important for resource efficiency and system performance improvement and this thesis proposes a two-hop power allocation algorithm for energy efficiency, which adjusts the transmission power of the BS and RSs to make the data rate on the two hop links of one RS match each other. The power allocation problem of multiple cells with inter-cell interference is studied. A new multi-cell power allocation scheme is proposed from non-cooperative game theory; this coordinates the inter-cell interference and operates in a distributed manner. The utility function can be designed for throughput improvement and user fairness respectively. Finally, the proposed algorithms in this thesis are combined, and the system performance is evaluated. The joint radio resource allocation algorithm can achieve a very good tradeoff between throughput and user fairness, and also can significantly improve energy efficiency