Semi-distributed Resource Allocation Research Articles

Cross-Layer QoE Optimization for D2D Communication in CR-Enabled Heterogeneous Cellular Networks

Device-to-device (D2D) communication based on cognitive radio (CR) technology can significantly improve the coverage and spectral efficiency. Existing research on D2D communications mainly focus on optimizing the network quality of service in single-tier networks. However, the exponential growth in data traffic has inspired the move from traditional single-tier cellular networks toward heterogeneous cellular networks. Hence, in this paper, we consider a CR-based HetNet coexisting with cognitive D2D pairs and cellular users, where the cellular users are primary users and D2D pairs are secondary users. Considering quality of experience (QoE) is an important metric to quantify and measure quality of experience from the user perspective, we focus on the QoE optimization of the D2D pairs via the BS association, the discrete power control, and the resource block (RB) assignment. To do so, we first formulate the cross-layer optimization problem to maximize the average QoE of the D2D pairs while satisfying the QoE requirements of cellular users. We then propose the centralized resource allocation, namely the genetic algorithm (GA), and semi-distributed resource allocation method, namely Stackelberg game based algorithm, to solve the non-convex optimization problem. The GA is proposed to ensure the maximum achievable QoE with known channel state information (CSI), whereas the Stackelberg game based algorithm is proposed to cope with the strong needs for distributed D2D solutions with only local CSI of each D2D link. Our proposed algorithms can achieve substantial improvement of QoE performance for D2D pairs via increasing the number of RBs.

Semi-Distributed Resource Allocation for Dense Small Cell Networks

Semi-Distributed Resource Allocation for Dense Small Cell Networks

Distributed algorithms for sum rate maximization in multi-cell downlink OFDMA with opportunistic DF relaying

This paper considers a multi-cell orthogonal frequency division multiple access (OFDMA) downlink system with several decode-and-forward (DF) relay stations (RSs) aiding the base station (BS) transmissions. The problem considered is the maximization of the system sum rate with a total power constraint in each cell. An iterative semi-distributed resource allocation (RA) algorithm is first proposed to optimize mode selection (decision whether relaying should be used or not and which relay), subcarrier assignment (MSSA), and power allocation (PA), alternatively. During the MSSA stage, the problem is decoupled into subproblems which can be solved distributively in linear time. During the PA stage, an algorithm based on single condensation and Lagrange duality (SCLD) is designed to optimize PA with the tentative MSSA results. The convergence of the SCLD-based RA algorithm is theoretically guaranteed and an local optimum is reached after convergence. To solve the formulated problem autonomously, a modified iterative water-filling (IWF) algorithm is further proposed. Specifically, each cell autonomously optimizes its own sum rate with the estimated power values of the received interferences from the other cells. An optimum algorithm is proposed to solve the local RA problem in each cell. Through numerical experiments, the convergence of the two proposed algorithms as well as their benefits compared with a centralized algorithm (CA) are illustrated.

Fair Semi-distributed Resource Allocation Scheme over Relay-Enhanced OFDMA Networks

In this paper, we propose a fair semi-distributed resource allocation scheme over relay-enhanced orthogonal frequency-division multiple access (OFDMA) cellular networks. Since the existing works based on the centralized manner require the heavy feedback overhead between a base station (BS) and relay stations (RSs), we design a resource allocation scheme in the semi-distributed manner to reduce the feedback overhead. In the proposed scheme, a frame is divided into subframes and the BS and RSs allocate the subchannel in the dedicated subframe to its associated mobile stations (MSs). In addition, the proposed scheme guarantees fairness among MSs with the throughput-optimal scheduling. Through the simulation, we show that the proposed scheme is effective to guarantee fairness among MSs while it achieves the higher average throughput than the existing opportunistic schemes.

Resource allocation based on integer programming and game theory in uplink multi-cell cooperative OFDMA systems

In this article, we propose a semi-distributed resource allocation framework for the resource optimization in multi-cell uplink cooperative orthogonal frequency division multiplexing systems. Specifically, we model the resource allocation framework as an optimal problem. This optimization problem is divided into two steps. First, using integer programming, we achieve the joint relay selection and subcarrier allocation based on maximizing system sum rate in a centralized way. Second, the distributed power allocation is achieved based on game theory, for cooperative and non-cooperative users, respectively. For cooperative mobile stations, an improved utility is proposed to regulate power allocation in the two time slots. Besides the existence of Nash equilibrium (NE), a new approach for the strict mathematical proof of the uniqueness of NE is proposed. Simulation results demonstrate that the proposed algorithm successfully combines the merits of centralized and distributed framework. It can effectively make use of relays to enhance the sum rate of users as well as achieve the fairness among users.

Semi-Distributed Resource Allocation Based on Multihop Equilibrium for Cellular OFDM-Relay Networks

A semi-distributed resource allocation scheme based on multihop equilibrium is proposed for OFDM-relay networks. This method aims to reduce the amount of feedback information from the relay nodes (RNs). Moreover, it utilizes radio resource by striking an efficient balance between the capacities of the BS-RN link and RN-MS link. Simulation results show that the proposed semi-distributed scheme achieves good performances in terms of throughputs and fraction of satisfied users.