Multiuser multi-input multi-output orthogonal frequency division multiple access (MIMO-OFDMA) is regarded as an important technology for increasing the flexibility and efficiency of wireless communication systems. A well-behaved resource allocation strategy is crucial for the performance of such systems. In this paper, we systematically study the allocation problem from a game theory perspective for the multiuser downlink broadcast channel. First, we investigate the application of the Nash and Kalai-Smorodinsky bargaining games to a general resource allocation problem and propose algorithms to find the corresponding solutions. Then we apply the general solutions to the special case where spatial block diagonalization is combined with time-sharing to multiplex a subset of the users on every subcarrier. To reduce the computational complexity, a framework for simplifying the resulting algorithms is also given. Numerical results and analysis are provided to compare the performance of the different resource allocation methods.

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Applying Bargaining Solutions to Resource Allocation in Multiuser MIMO-OFDMA Broadcast Systems

The traditional proportional fair scheduling algorithm can only provide users with limited fairness while the channel is changing. To solve this problem and enhance the fairness between users, an adaptive proportional fair scheduling algorithm for LTE (Long term Evolution) system is proposed. It adjusts the scheduling priority according to individual user's channel condition. The proposed algorithm provides a good trade-off between capacity and fairness, and the simulation results show the validity.

Adaptive pf scheduling algorithm in LTE cellular system

In the subcarrier and power allocation schemes in Multi-Input Multi-Output and Orthogonal Frequency Division Multiple Access (MIMO-OFDMA) systems, only equal fairness among users has been considered and no scheme for proportional data rate fairness has been considered. In this paper, a subcarrier, bit and power allocation scheme is proposed to maximize the total throughput under the constraints of total power and proportional data rate fairness among users. In the proposed scheme, joint subchannel allocation and adaptive bit loading is firstly performed by using singular value decomposition (SVD) of channel matrix under the constraint of users' data throughput requirements, and then adaptive power loading is applied. Simulation results show that effective performance of the system has been improved as well as each throughput is proportionally distributed among users in MIMO-OFDMA systems.

Resource Allocation Scheme in MIMO-OFDMA System for User's Different Data Throughput Requirements

OFDM can provide frequency diversity gain for point-to-point communications over frequency-selective slow fading channel. Recent works show that OFDM may also form a flexible and efficient multiple access method, which is often referred to OFDMA. However, the user outage probability and the optimal frequency diversity gain in OFDMA systems are not known. In this paper, random bipartite graph is used to model and analyse the multi-user subcarrier allocation problem over frequency-selective slow fading channels. Our aim is to minimize the user outage probability as well as guarantee fairness by dynamic allocating various subcarrier to each user. An optimal subcarrier allocation algorithm, which we shall refer to as the Hungarian method with random vertices rotation, is introduced to achieve these objectives. A simple but effective approximation equation for user outage probability is then derived. It is shown that the optimal frequency diversity gain in OFDMA system is the same as the point-to-point OFDM system. In particular, the frequency diversity gain does not decay as the number of users increases.

Achieving High Frequency Diversity with Subcarrier Allocation in OFDMA Systems

In the conventional subcarrier and power allocation schemes in multi-input multi-output and orthogonal frequency division multiple access (MIMO-OFDMA) systems, only equal fairness among users has been considered, and no scheme for proportional data rate fairness is considered. In this paper, subcarrier and power allocation criterion is proposed to maximize the total throughput under the constraints of total power and proportional data rate fairness among users. In the proposed scheme, subchannel allocation is firstly performed by using singular value decomposition (SVD) of channel matrix under the constraint of users' data throughput requirements, and then adaptive bit and power loading is applied. Simulation results show that total throughput is increased as well as each throughput is proportionally distributed among users in MIMO-OFDMA systems.

This paper investigates the performance of a Weighted Proportional Fair (WPF) based resource allocation algorithm for future Multi-User (MU) Mulitple-Input Mulitple-Output (MIMO) Orthogonal Frequency-Division Multiple-Access (OFDMA) systems with frequency-selective broadband channels. In future networks algorithms should be designed to allocate the system's resources (time, frequency, space and power) in a manner that exploits multi-user diversity and ensures each user is treated fairly. The proposed algorithm extends the original Proportional Fair (PF) scheme, which was designed for single-antenna single-carrier systems, to the MIMO-OFDMA downlink such that individiual user's Quality of Service (QoS) requirements are satisfied in terms of requested bit-rate and bit error rate (BER). Monte Carlo simulation results indicates that extending the algorithm to a frequency-and space-division network produces the desirable characteristics of a fair and efficient algorithm.

Fairness Based Resource Allocation for Multi-User MIMO-OFDM Systems

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Fairness Based Resource Allocation for Multi-User MIMO-OFDM Systems