Resource allocation for transmit hybrid beamforming in decoupled millimeter wave multiuser-MIMO downlink

This paper presents a study on joint radio resource allocation and hybrid precoding in multicarrier massive multiple-input multiple-output communications for 5G cellular networks. In this paper, we present the resource allocation algorithm to maximize the proportional fairness (PF) spectral efficiency under the per subchannel power and the beamforming rank constraints. Two heuristic algorithms are designed. The proportional fairness hybrid beamforming algorithm provides the transmit precoder with a proportional fair spectral efficiency among users for the desired number of radio-frequency (RF) chains. Then, we transform the number of RF chains or rank constrained optimization problem into convex semidefinite programming (SDP) problem, which can be solved by standard techniques. Inspired by the formulated convex SDP problem, a low-complexity, two-step, PF-relaxed optimization algorithm has been provided for the formulated convex optimization problem. Simulation results show that the proposed suboptimal solution to the relaxed optimization problem is near-optimal for the signal-to-noise ratio SNR <= 10 dB and has a performance gap not greater than 2.33 b/s/Hz within the SNR range 0-25 dB. It also outperforms the maximum throughput and PF-based hybrid beamforming schemes for sum spectral efficiency, individual spectral efficiency, and fairness index

Resource Allocation for Power Minimization in the Downlink of THP-based Spatial Multiplexing MIMO-OFDMA Systems

In this work, we deal with resource allocation in the downlink of spatial multiplexing MIMO-OFDMA systems. In particular, we concentrate on the problem of jointly optimizing the transmit and receive processing matrices, the channel assignment and the power allocation with the objective of minimizing the total power consumption while satisfying different quality-of-service requirements. A layered architecture is used in which users are first partitioned in different groups on the basis of their channel quality and then channel assignment and transceiver design are sequentially addressed starting from the group of users with most adverse channel conditions. The multi-user interference among users belonging to different groups is removed at the base station using a Tomlinson-Harashima pre-coder operating at user level. Numerical results are used to highlight the effectiveness of the proposed solution and to make comparisons with existing alternatives.Comment: 12 pages, 6 figures, IEEE Trans. Veh. Techno

Resource Allocation for Downlink Multi-Cell OFDMA Cognitive Radio Network Using Hungarian Method

This paper considers the problem of resource allocation for downlink part of an OFDM-based multi-cell cognitive radio network which consists of multiple secondary transmitters and receivers communicating simultaneously in the presence of multiple primary users. We present a new framework to maximize the total data throughput of secondary users by means of subchannel assignment, while ensuring interference leakage to PUs is below a threshold. In this framework, we first formulate the resource allocation problem as a nonlinear and non-convex optimization problem. Then we represent the problem as a maximum weighted matching in a bipartite graph and propose an iterative algorithm based on Hungarian method to solve it. The present contribution develops an efficient subchannel allocation algorithm that assigns subchannels to the secondary users without the perfect knowledge of fading channel gain between cognitive radio transmitter and primary receivers. The performance of the proposed subcarrier allocation algorithm is compared with a blind subchannel allocation as well as another scheme with the perfect knowledge of channel-state information. Simulation results reveal that a significant performance advantage can still be realized, even if the optimization at the secondary network is based on imperfect network information

Adaptive radio resource management schemes for the downlink of the OFDMA-based wireless communication systems

Includes bibliographical references.Due to its superior characteristics that make it suitable for high speed mobile wireless systems OFDMA has been adopted by next generation broadband wireless standards including Worldwide Interoperability for Microwave Access (WiMAX) and Long Term Evolution – Advanced (LTE-A). Intelligent and adaptive Radio Resource Management (RRM) schemes are a fundamental tool in the design of wireless systems to be able to fully and efficiently utilize the available scarce resources and be able to meet the user data rates and QoS requirements. Previous works were only concerned with maximizing system efficiency and thus used opportunistic algorithms that allocate resources to users with the best opportunities to optimize system capacity. Thus, only those users with good channel conditions were considered for resource allocation and users in bad channel conditions were left out to starve of resources. The main objective of our study is to design adaptive radio resource allocation (RRA) algorithms that distribute the scarce resources more fairly among network users while efficiently using the resources to maximize system throughput. Four scheduling algorithms have been formulated and analysed based on fairness, throughputs and delay. This was done for users demanding different services and QoS requirements. Two of the scheduling algorithms, Maximum Sum Rate (MSR) and Round Robin (RR) are used respectively, as references to analyze throughput and fairness among network users. The other two algorithms are Proportional Fair Scheduling (PFS) and Margin Adaptive Scheduling Scheme (MASS)