Min Sheng

Performance evaluation of modified IEEE 802.11 MAC for multi-channel multi-hop ad hoc network

The IEEE 802.11 multiple access control protocol was modified for use in multi-channel, multi-hop ad hoc network, through the use of a new channel-status indicator. In particular, we have evaluated the improvement due to the multi-channel use. We report in this paper on the results of the throughput per node and the end-to-end delay for the modified IEEE 802.11 protocol for different network sizes. Using these results, we were able to propose a number of throughput scaling laws. Our simulation results show that the throughputs per node with multiple channels for the line and the grid ad hoc network topologies will increase by 47.89%, and by 1.39-163%, respectively, for networks with 16 to 64 nodes, as compared with that of single channel.

D2D Enhanced Heterogeneous Cellular Networks With Dynamic TDD

Over the last decade, the growing amount of uplink (UL) and downlink (DL) mobile data traffic has been characterized by substantial asymmetry and time variations. Dynamic time-division duplex (TDD) has the capability to accommodate to the traffic asymmetry by adapting the UL/DL configuration to the current traffic demands. In this work, we study a two-tier heterogeneous cellular network (HCN) where the macro tier and small cell tier operate according to a dynamic TDD scheme on orthogonal frequency bands. To offload the network infrastructure, mobile users in proximity can engage in device-to-device (D2D) communications, whose activity is determined by a carrier sensing multiple access (CSMA) scheme to protect the ongoing infrastructure-based and D2D transmissions. We present an analytical framework for evaluating the network performance in terms of load-aware coverage probability and network throughput. The proposed framework allows quantification of the effect on the coverage probability of the most important TDD system parameters, such as the UL/DL configuration, the base station density, and the bias factor. In addition, we evaluate how the bandwidth partition and the D2D network access scheme affect the total network throughput. Through the study of the tradeoff between coverage probability and D2D user activity, we provide guidelines for the optimal design of D2D network access.

Energy Efficiency and Spectral Efficiency Tradeoff in Interference-Limited Wireless Networks

This letter investigates the fundamental tradeoff between energy efficiency (EE) and spectral efficiency (SE) for interference-limited wireless networks (IWNs), which is a nonconvex optimization and NP-hard problem. A general algorithm procedure (GAP) embedded with an iterative power allocation algorithm (IPAA) is proposed, which has good performance with the advantages of fast convergence, low complexity and insensitivity to initial values. Simulation results explicitly depict the EE-SE tradeoff curve for IWNs.

Energy Efficiency and Delay Tradeoff in Device-to-Device Communications Underlaying Cellular Networks

This paper investigates the problem of revealing the tradeoff between energy efficiency (EE) and delay in device-to-device (D2D) communications underlaying cellular networks. Considering both stochastic traffic arrivals and time-varying channel conditions, we formulate it as a stochastic optimization problem, which optimizes EE subject to the average power, interference-control, and network stability constraints. With the help of fractional programming and the Lyapunov optimization technique, we develop an algorithm, referred to as the TRADEOFF, to solve the problem. To deal with the nonconvex and NP-hard power allocation subproblem in the TRADEOFF, we adopt the prismatic branch and bound algorithm to find its globally optimal solution, where only a linear programming needs to be solved in each iteration. Thus, the TRADEOFF serves as an important benchmark to evaluate performance of other heuristic algorithms and is usually cost-efficient. The theoretical analysis and simulation results show that the TRADEOFF achieves an EE-delay tradeoff of [O(1/V),O(V)] with V being a control parameter and can strike a flexible balance between them by simply tuning V.

Energy-Efficient Subcarrier Assignment and Power Allocation in OFDMA Systems With Max-Min Fairness Guarantees

In next-generation wireless networks, energy efficiency optimization needs to take individual link fairness into account. In this paper, we investigate a max-min energy efficiency-optimal problem (MEP) to ensure fairness among links in terms of energy efficiency in OFDMA systems. In particular, we maximize the energy efficiency of the worst-case link subject to the rate requirements, transmit power, and subcarrier assignment constraints. Due to the nonsmooth and mixed combinatorial features of the formulation, we focus on low-complexity suboptimal algorithms design. Using a generalized fractional programming theory and the Lagrangian dual decomposition, we first propose an iterative algorithm to solve the problem. We then devise algorithms to separate the subcarrier assignment and power allocation to further reduce the computational cost. Our simulation results verify the convergence performance and the fairness achieved among links, and particularly reveal a new tradeoff between the network energy efficiency and fairness by comparing the MEP with the existing algorithms.

Relative degree adaptive flooding broadcast algorithm for ad hoc networks

Broadcasting has been widely used in mobile Ad hoc networks as a communication means to disseminate information to all reachable nodes. Because radio signals are likely to overlap with others in a geographical area, straightforward broadcasting by flooding becomes very costly and results in serious redundancy, contention and collision, to which we refer as the broadcast storm problem. In this paper we propose the Relative Degree Adaptive flooding Broadcast (RDAB) algorithm for Ad hoc networks to efficiently reduce the broadcast overhead in the network. Based on the current situation of the network and the degree of the nodes, RDAB calculates the relative degree of the nodes, decides which nodes need to re-transmit and which nodes only need to receive. The higher the neighbor nodes relative degree, the more uncovered nodes it can cover, hence these nodes can be selected to re-transmit broadcasting packets in the networks. We analyze the reliability and the validity of the RDAB algorithm to prove that the RDAB algorithm is a valid flooding broadcast algorithm. Simulation results show that the RDAB strategy outperforms the Ordinary Flooding Broadcast Method (OBM) and the Multipoint Relaying (MPR) protocol for Ad hoc networks.

Green Communications with Network Cooperation: A Concurrent Transmission Approach

This letter investigates the benefits of concurrent transmission from the perspective of green communications. A concurrent transmission scheme under the metric of bit-per-joule, modeled as a constrained optimization problem, is proposed to split traffic flow among multiple networks. The threshold of the traffic splitting starting point and the optimal rate allocation of each flow are derived to maximize the system energy efficiency. The results demonstrate that our scheme can save significant power and improve the energy efficiency.

Pricing-Based Multiresource Allocation in OFDMA Cognitive Radio Networks: An Energy Efficiency Perspective

Both the orthogonal frequency-division multiple access (OFDMA) and cognitive radio (CR) technologies offer great flexibility and feasibility for future green wireless communications. In this paper, an energy-efficient multiresource-allocation scheme is proposed for OFDMA CR networks (CRNs) with multiple secondary transmitters (STs). To maximize the energy efficiency (EE) and guarantee the primary transmitters (PTs) quality-of-service (QoS) requirement, a linear pricing technique is employed to handle both the inter-ST coupling (the spectrum competition among STs) and intra-ST coupling (the correlation between the available transmit power and assigned subchannels for each ST). Furthermore, a distributed algorithm is devised to harvest the multiresource and multiuser gains, and the multiresource allocation is transformed to 1-D pricing-factor profile searching. Simulation results demonstrate that the proposed strategy brings higher EE. Additionally, by adjusting the pricing factors, a different performance can be achieved by the STs with different priorities.

Performance Evaluation of Modified IEEE 802.11 MAC for Multi-Channel Multi-Hop Ad Hoc Networks

In this paper, the IEEE 802.11 multiple access control (MAC) protocol was modified for use in multi-channel, multi-hop ad hoc networks through the use of a new channel-status indicator. In particular, in the modified protocol, the RTS/CTS dialogue is exchanged on the common access control channel and data packets are transmitted on a selected traffic channel. We have evaluated the improvement due to the multi-channel use and we report in this paper on the results of the per-node throughput and the end-to-end delay for different network sizes. Using these results, we were able to propose a number of per-node throughput scaling laws. Our simulation results show that the per-node throughput with multiple channels for the fully connected, the line, and the grid ad hoc network topologies increases by 90% to 253%, by 47%, and by 139% to 163%, respectively, for networks with 16 to 64 nodes, as compared with that of a single channel.

Energy Efficiency and Delay Tradeoff for Time-Varying and Interference-Free Wireless Networks

In this paper, we investigate the fundamental tradeoff between energy efficiency (EE) and delay for time-varying and interference-free wireless networks. We formulate the problem as a stochastic optimization model, which optimizes the system EE subject to network stability and the average and peak transmit power constraints. By adopting the fractional programming theory and Lyapunov optimization technique, a general and effective algorithm, referred to as the EE-based dynamic power allocation algorithm (EE-DPAA), is proposed. The EE-DPAA does not require any prior knowledge of traffic arrival rates and channel statistics, yet yields an EE that can arbitrarily approach the theoretical optimum achieved by a system with complete knowledge of future events. Most importantly, we quantitatively derive the EE-delay tradeoff as [O(1/V),O(V)] with V as a control parameter for the first time. This result provides an important method for controlling the EE-delay performance on demand. Simulation results validate the theoretical analysis on the EE-delay tradeoff, as well as show the adaptiveness of the EE-DPAA.