Jinming Hu

Energy-Efficient Resource Reuse Scheme for D2D Communications Underlaying Cellular Networks

This letter investigates energy-efficient downlink resource reuse strategies for device-to-device (D2D) communications underlying cellular networks. We aim to maximize the total energy efficiency of all D2D links while guaranteeing the quality of service of cellular users (CUs) and the power requirements for both base station and D2D links. Based on the analysis of the characteristics of optimal joint power control and D2D-CU matching strategy, we propose an energy-efficient iterative algorithm for D2D communications. Simulation results show that the proposed energy-efficient downlink resource reuse strategy achieves higher energy efficiency of D2D communications than existing schemes.

Distributed Power Control for D2D Communications Underlaying Cellular Network Using Stackelberg Game

In this paper, a Stackelberg game based power control framework is proposed for interference coordination among device-to-device (D2D) communications and spectrum-sharing cellular networks. The cross-tier interference from D2D communications is controlled by the cellular base station (CBS) through setting a price for the shared subchannels. Based on the cross-tier interference price, each D2D pair adaptively updates its power strategy subsequently. A distributed power control algorithm with limited coordination among D2D pairs is proposed and guaranteed to converge to a Karush- Kuhn-Tucker (KKT) point of the optimization problem at D2D pairss side by introducing a new co-tier price factor. At the CBSs side, a price update algorithm is designed ably according to cross-tier interference measurement. Simulation results show that the proposed algorithms can achieve higher sum rate for D2D communications when compared with that of the non-cooperative power allocation algorithm.

Energy efficient resource allocation in timesharing multiuser systems with hybrid energy harvesting transmitter

An energy efficient resource allocation scheme in timesharing multiuser system with a hybrid energy harvesting transmitter is studied in this paper. Specially, the operation energy of system is supplied by constant energy and energy harvesting, which harvests energy from external environment. Our goal is to maximize the energy efficiency of timesharing multiuser systems by considering jointly allocation of transmission time and power control in an off-line manner. The original nonconvex objective function is transformed into convex optimization problem via the fractional programming approach. Then, we solve the convex problem by Lagrange dual decomposition method. Simulation results show that the proposed energy efficient resource allocation scheme has a better performance than the scheme which decomposes optimization problem into two parts (power allocation, time allocation) to solve iteratively.

Optimal Energy-Efficient Transmission in Multiuser Systems with Hybrid Energy Harvesting Transmitter

This paper considers the optimal energy-efficient transmission policy in time-sharing multiuser systems with a hybrid energy harvesting transmitter. The system operation energy is supplied by a constant energy source which is driven by a non-renewable resource and an energy harvester which harvests energy from its surrounding environment. Our goal is to maximize the energy-efficient transmission of multiuser systems considering the allocation of power and transmission time jointly in an off-line manner. The original nonconvex objective function is transformed into convex optimization problem via the fractional programming approach. Furtherly, we solve the convex problem by Lagrange dual decomposition method. Simulation results show that the proposed energy-efficient transmission policy has a better performance than the transmission policy which decomposes optimization problem into two parts (power allocation, time allocation) to solve iteratively.

A novel two-stage dynamic spectrum sharing scheme in cognitive radio networks

In order to enhance the efficiency of spectrum utilization and reduce communication overhead in spectrum sharing process, we propose a two-stage dynamic spectrum sharing scheme in which cooperative and non-cooperative modes are analyzed in both stages. In particular, the existence and the uniqueness of Nash Equilibrium (NE) strategies for noncooperative mode are proved. In addition, a distributed iterative algorithm is proposed to obtain the optimal solutions of the scheme. Simulation studies are carried out to show the performance comparison between two modes as well as the system revenue improvement of the proposed scheme compared with a conventional scheme without a virtual price control factor.

Downlink cross-tier interference pricing and power control in OFDMA HetNets

Deploying smallcell networks achieves great spatial reuse at the cost of severe cross-tier interference from concurrent transmission. This paper addresses the downlink cross-tier interference pricing and power control for orthogonal frequency division multiple access (OFDMA) heterogeneous Networks (HetNets), where a macrocell underlaid with several femtocells.We assume that the macrocell protects its transmission by pricing the interference on each orthogonal subchannel and each femtocell base station (FBS) determines the power allocation strategy accordingly.Then, a Stackelberg game is used to formulate the mentioned model. Existence and uniqueness of the Stackelberg equilibrium (SE) are analyzed. In addition, a distributed interference pricing and power update algorithm (DIPPU) with guaranteed convergency is proposed to achieve the SE. Simulation results validate the proposed algorithm and show its fast convergence. Due to the non-cooperative manner, the proposed scheme can approach the cooperative scheme in terms of capacity of femtocells with reduced communication overhead effectively.

Blind Carrier and Sampling Frequency Offsets Estimation in OFDM System

This paper considers the blind estimation of the carrier frequency offset (CFO) and sample frequency offset (SFO) in orthogonal frequency division multiplexing (OFDM) system. Conventional methods require periodically transmitted pilot tones in frequency domain or identical training symbols in preamble. To achieve a blind estimation scheme, a joint maximum-likelihood (ML) estimator is proposed by applying another FFT within one symbol duration. Its simplified closed-form solution is then derived to reduce computational complexity. Theoretical analysis and simulation results confirm that the proposed low-complexity scheme achieves almost the same performance as ML estimation and outperforms other blind methods.

Distributed power and resource allocation for weighted sum energy-efficiency maximization in OFDMA smallcell network

In this paper, we investigate the problem of maximizing the weighted sum energy efficiency (WS-EE) in downlink OFDMA smallcell network. To solve the problem in a distributed manner and reduce the complexity, we decompose the resource blocks (RBs) allocation and the power control into two subproblems. For the subproblem of RBs allocation, the optimal RBs allocation strategy is obtained based on rate maximization given any feasible network power profile. For the subproblem of power control, a novel distributed pricing based algorithm is developed with limited inter-smallcell coordination. Specifically, each smallcell base station (SBS) updates its current interference information and broadcasts it to the other SBSs. With this collected information, the optimal power control strategy of each SBS is derived. Simulation results show that the proposed algorithm outperforms the existing algorithms in terms of the WS-EE.

Power allocation and receive antenna selection algorithm in multi-cell cooperative networks

In this paper, system throughput and user fairness for single-antenna user based on zero-forcing precoding are investigated with total power constraint (TPC) and per antenna power constraint (PAPC), respectively. By analyzing fairness of users signal to noise ratios (SNRs), the closed-form solution of fairness is obtained, and the tradeoff between system throughput and user fairness is presented. For multiple-antenna user, receive antenna selection (RAS) by maximizing channel norm is exploited to greatly reduce computational complexity. Simulation results show that different power constraints have a significant impact on system throughput and user fairness, and the throughput by considering user fairness decreases compared to that by considering maximum system throughput.

Stackelberg bargaining-based allocation for multi-source relay networks

In this paper, multi-source single-relay power allocation in cooperative wireless networks is considered. We model the interaction among sources and relay as a Stackelberg bargaining game. A new price function is defined which sets a different price for different sources, then a relay power allocation scheme based on a distributed algorithm is derived. Simulation results show the proposed solution could effectively realize the goal of relay power reasonable allocation.