Dapeng Li

Multipath network coding and multicasting for content sharing in wireless P2P networks: A potential game approach

Abstract Motivated by the popularity of the peer to peer (P2P) content sharing over internet and the development of wireless device to device (D2D) communications, this paper considers the problem of delivering K different contents to D destinations from N sources in wireless networks. Traffic in opposite directions over two wireless hops can utilize the advantage of network coding (NC) in order to decrease the number of transmissions used. We call such coded hops as “NC-links”. On the other hand, the multicast (MC) links can transmit data to several nodes at the same time, also yielding the improvement of the transmissions efficiency. However, there exists a certain level of ambiguity regarding how to coordinate NC and MC to improve the file sharing performance in wireless P2P content distribution systems. Considering both NC and MC gains, we investigate the content traffic splitting using a potential game model. Subsequently, we identify the equilibrium solution to this game and develop a two-level distributed control algorithm that allows each destination to select the source and split the traffic so as to adjust the content traffic based on the potential function in a distributed way. Through theoretical analysis and simulation results, we show that the proposed scheme is stable and effective.

Dynamics of multipath network coding and multicasting in wireless P2P networks

This paper considers the problem of delivering K different contents to D destinations from N sources in wireless networks. Traffic in opposite directions over two wireless hops can utilize the advantage of network coding (NC) in order to decrease the number of transmissions used. We call such coded hops as “NC-links”. On the other hand, the multicast (MC) links can transmit data to several nodes at the same time, also yielding the improvement of the transmissions efficiency. However, there exists a certain level of ambiguity regarding how to coordinate NC and MC to improve the file sharing performance in wireless P2P content distribution systems. Considering both NC and MC gains, we investigate the content traffic splitting using the theory of a potential game and show that there is competition among destinations in order to minimize the total system transmission cost. Subsequently, we identify the equilibrium solution to this game and develop a two-level distributed control algorithm that allows each destination to select the source and split the traffic so as to adjust the content traffic based on the potential function in a distributed way. Through theoretical analysis and simulation results, we show that the proposed scheme is stable and effective.

Energy-efficient power allocation for multi-user MIMO systems with GZI precoding

Summary nTo achieve the energy efficiency (EE) for multi-user multiple-input multiple-output (MU-MIMO) systems with GZI precoding, based on an actual power consumption model, the paper investigates the power allocation (PA) optimization problem with guaranteeing the sum rate for all downlink users and the different rate requirements for different downlink users. For the case of guaranteeing the sum rate for all downlink users, the highly complex optimization problem is firstly reformulated into an equivalent pseudo-convex form to be handled by the Lagrange Multiplier method. Then, it is simplified with reducing 2-dimension PA parameter into 1 dimension. Finally, the closed-form optimal solution is obtained through deriving of complex equations involving the log function. And for the case of guaranteeing the different rate requirements for different downlink users, the concrete numerical solution to the optimization problem is iteratively obtained through convex optimization toolbox in MATLAB. Simulation results validate the efficacy of the proposed optimization scheme. Furthermore, it is illustrated that the proposed optimization algorithm shows more optimal than average PA and antenna selection algorithms.

Energy Efficiency Maximizing with Power Allocation for Multi-user MIMO Systems Based on GZI Precoding

This paper investigates the problem of energy efficiency with power allocation for multi-user MIMO systems. Based on a practical power consumption model, the optimal transmit powers of the MU-MIMO downlink system are derived in the form of analytical expressions in order to maximize energy efficiency with satisfying quality of service requirements. Reducing the dimensions of variables and applying the properties of the Lambert function to solve the equations with the log function, this study solves the highly complicated optimization problem by deliberately manipulating the Lagrange function. Hence, a closed-form solution to the energy efficiency maximization problem for MU-MIMO systems is eventually achieved. Simulation results validate the efficacy of the proposed optimization scheme.

Joint Energy and Spectrum Allocation for Wireless Networks with Renewable Energy Supply Commonality

In this paper, a renewable energy supply commonality wireless network is studied. In the considered model, two BSs buy spectrum from their dedicated spectrum owners and purchase green energy from their common local renewable utility firms to produce resource blocks (RBs) to satisfy stochastic mobile users’ traffic demand and the process is controlled by the wireless network operator. And different BS’s RB consists of different units of renewable energy and spectrum. Toward this end, we use a game theoretic approach to explore the system and present the optimal solution under decentralized decision making. Finally, we provide numerical results to validate the optimal solutions.

Multi-tier ON/OFF Scheduling Algorithm for Small Cell Networks with Renewable Energy

In the future cellular network, densifying the multi-tier heterogeneous cellular network (HetNet) via viral deployment of small cell base stations (SBSs) can increase energy consumption. In order to solve the energy problem in the future, SBSs that rely solely on energy harvesting can be adopted. In this paper, we focus on problem about multi-tier ON/OFF scheduling of SBSs and the goal is to minimize the overall cost of the network, including energy consumption costs and transmission delay costs of a HetNet. Finally, simulation results show, proposed algorithm can improve the overall performance of the network.

Energy-saving cross-layer optimization for multihop cognitive networks

Energy consumption reducing in wireless communications has attracted increasing attention recently. Power control is a key technology for cognitive networks, which can affect energy saving of cognitive network and interfere with primary networks. In this paper, we jointly consider power control in physical layer, scheduling in link layer and routing in network layer to present a cross-layer optimization for power control in multi-hop cognitive network and formulate a mixed integer nonlinear program (MINLP) problem. To solve it, we develop a piece-wise linearization technique to transform the nonlinear term in constraints into the linear one and finally obtain the approximate optimal solution. Simulation results demonstrate the efficacy of the solution procedure and the optimal power control can achieve energy saving.

The join collaborative data offloading and distributed channel selection in wireless networks

Data offloading is a promising technique for mobile terminals (MTs) for conserving energy in wireless networks. This technique enables MTs to support heavy data traffic by offloading computation-intensive tasks to the cloud. However, due to the long transmission up-link, data offloading may lead to unnecessary energy usage. In this paper, we propose a joint collaborative data offloading framework with channel selection for MTs, in which MTs can first form a coalition and then execute data offloading in a cooperative way. We adopt game theory to formulate the problem as a cooperation game. We then prove that the formulated game is a potential game and can achieve Nash equilibrium. A Markov approximation approach is applied to design a distributed channel selection algorithm for the game so that each MT can self-organize into stability without information exchange across the whole network. Analytical and numerical results show that the algorithm is feasible and efficient in comparison to traditional centralized optimization solutions.

Cross-Layer Cooperative Power Control in Heterogeneous Multihop Networks

This paper investigates how to perform optimal cooperative power control for the coexistence of heterogeneous multihop networks. Although power control on the node level in multihop networks is a difficult problem due to its large design space and the coupling relationship of power control with scheduling and routing, we formulate a multiobjective optimization problem for the total power consumption of the two heterogeneous multihop networks with discretized power level. We reformulate the nonlinear constraint (relationship between power and capacity) into the linear one by piecewise linearization procedure and offer an in-depth study of cooperative power control in terms of its optimal power—the minimum power consumption with discretized power level for both heterogeneous multihop networks. Through a novel approach based on adaptive weighted-sum method, we transform the multiobjective optimization problem into a single-objective optimization problem and find the set of Pareto-optimal points iteratively. Using the Pareto-optimal points, we construct the minimum power curve. Using numerical results, we demonstrate that it can save more energy with cooperative power control than the case without cooperative power control.