A utility-based capacity optimization framework for achieving cooperative diversity in the hierarchical converged heterogeneous wireless networks

A hierarchical convergence mechanism for the heterogeneous wireless communication system via the heterogeneous cooperative relay node is presented in this paper, in which the techniques of cooperative communication and wireless relay are utilized to improve performances of the individual user and the overall converged networks. In order to evaluate the benefits of the proposal, a utility-based capacity optimization framework for achieving the heterogeneous cooperative diversity gain is proposed. The heterogeneous cooperative capacity, relay selection and power allocation theoretical models are derived individually. The joint optimization model for relay selection and power allocation is presented as well. Owing to the computation complexity, the sub-optimal cooperative relay selection algorithm, the sub-optimal power allocation algorithm and the sub-optimal joint algorithm are determined to approach the maximum overall networks' spectrum efficiency. These proposed algorithms are designed in conformance to guarantee the equivalent transmission rates of the different wireless access networks. The simulation results demonstrate that the utility-based capacity model is available for the heterogeneous cooperative wireless communication system, and the proposed algorithms can improve performances by achieving the cooperative gain and taking full advantage of the cross-layer design. Copyright © 2008 John Wiley & Sons, Ltd.     

Performance of Energy-Efficient Cooperative MAC Protocol with Power Backoff in MANETs

This paper presents an energy-efficient cooperative MAC (EECO-MAC) protocol using power control in mobile ad hoc networks. Cooperative communications improve network performance by taking full advantage of the broadcast nature of wireless channels. The power control technique improves the network lifetime by adjusting the transmission power dynamically. We propose the best partnership selection algorithm, which takes energy consumption into consideration for selection of the optimal cooperative helper to join in the transmission. Through exchanging control packets, the optimal transmission power is allocated for senders to transmit data packets to receivers. In order to enhance energy saving, space–time backoff and time–space backoff algorithms are proposed. Simulation results show that EECO-MAC consumes less energy and prolongs the network lifetime compared to IEEE 802.11 DCF and CoopMAC at the cost of delay. Performance improvement offered by our proposed protocol is apparent in congested networks where nodes have low and limited energy.     

Energy-efficient cooperative sensing and transmission in relay-assisted cognitive radio network

An innovative EE-oriented cooperative sensing and transmission scheme in relay-assisted cognitive radio networks,called energy-efficient best-relay cooperative transmission (BCT) was proposed.Based on the BCT scheme,mean energy efficiency (MEE) maximization problem with sensing duration and transmitting power as optimization variables was modeled for fading channels under constraint of minimal secondary outage probability.By virtue of Jensen’s inequality,the original optimization problem was decomposed into two relatively independent subproblems which solved sensing duration and power allocation respectively.And for the two subproblems,an efficient cross iteration based algorithm was proposed to obtain the suboptimal solutions.Both analytical and simulation results demonstrate that the proposals can achieve significantly higher EE while enhancing reliability of secondary transmission remarkably compared to non-cooperation single cognitive transmission schemesin high QoS requirement.     

衰落信道下基于中继选择与功率控制的节能协作通信

In order to save energy and make more efficient use of wireless channel, this article puts forward an energy saving cooperative relaying scheme which actuates the cooperative transmission only when the feedback from the destination indicates failure of the direct transmission. The proposed scheme selects the optimal relay and its corresponding transmission power in each time slot based on channel condition and residual energy with the objective of minimizing energy consumption and extending network lifetime. In the study, the finitestate Markov channel model is used to characterize the correlation structure of channel fading in wireless networks, and the procedure of relay selection and transmission power decision is formulated as a Markov decision process. Numerical and simulation results show that the proposed scheme consumes less energy and prolongs the network lifetime.     

Energy-efficient relay selection and optimal relay location in cooperative cellular networks with asymmetric traffic

Energy-efficient communication is an important requirement for mobile relay networks due to the limited battery power of user terminals. This paper considers energy-efficient relaying schemes through selection of mobile relays in cooperative cellular systems with asymmetric traffic. The total energy consumption per information bit of the battery-powered terminals, i. e. , the mobile station(MS)and the relay, is derived in theory. In the joint uplink and downlink relay selection(JUDRS)scheme we proposed, the relay which minimizes the total energy consumption is selected. Additionally, the energy-efficient cooperation regions are investigated, and the optimal relay location is found for cooperative cellular systems with asymmetric traffic. The results reveal that the MS-relay and the relay-base station(BS)channels have different influence over relay selection decisions for optimal energy-efficiency. Information theoretic analysis of the diversity-multiplexing tradeoff(DMT)demonstrates that the proposed scheme achieves full spatial diversity in the quantity of cooperating terminals in this network. Finally, numerical results further confirm a significant energy efficiency gain of the proposed algorithm comparing to the previous best worse channel selection and best harmonic mean selection algorithms.     

Downlink energy efficiency modeling and optimization with backhaul awareness and interference price in ultra cellular HetNet

The cellular heterogeneous network(HetNet) with ultra dense small cells is called ultra cellular HetNet.The energy efficiency for this network is very important for future green wireless communications.The data rates and power consumptions for three parts(i.e.,macro cells,small cells,and mixed backhaul links) in ultra cellular HetNet are jointly formulated to model downlink energy efficiency considering the active base stations(BSs) and inactive BSs.Then,in order to decrease the downlink co-channel interference,the interference price functions are also jointly set up for the three parts in ultra cellular HetNet.Next,energy efficiency optimization iterative algorithm scheme using the fractional programming and Lagrangian multiplier with constraints for density of ultra dense small cells and fraction of mixed backhaul links is presented with interference pricing.The convergence and computation complexity are also proved in this scheme.The numerical simulations finally demonstrate convergence behavior of the proposed algorithm.By comparison,some conclusion can be drawn.Maximizing energy efficiency of system is lower as the density of small cell is high.The effect on maximizing energy efficiency with interference price outperforms that without interference price.And the energy efficiency increases as the fraction of mixed backhaul links is higher because of more power consumption in the microwave backhaul links.     

Energy-Efficient Cooperative Transmission in Heterogeneous Wireless Networks with QoS Constraint

Heterogeneous wireless network is an effective scheme to improve both the spectrum efficiency and energy efficiency of cellular system. However, interference limits the performance of such heterogeneous wireless network seriously. Hence cooperative decision making, i.e., cooperative transmission is necessary. In this paper, we develop an energy-efficient scheme for cooperative transmission in heterogeneous wireless networks with QoS constraint. Since too much signaling is needed for absolutely centralized cooperation, which is infeasible in practical system, partly cooperation is considered in this paper. We first formulate the problem as a two-stage Stackelberg game. In the first stage, an energy-efficient transmission scheme for macrocell users (MUE) is proposed based on the interference state of the MUEs. In the second stage, after obtaining the SINR and target SINR of the MUEs, the femtocell base stations update their beamformers and optimize the transmission power individually through a non-cooperative game, the existence and uniqueness of the Nash equilibrium is proved. Then an iterative algorithm is proposed to obtain the Stackelberg equilibrium. Simulation results show the performance gain of the proposed scheme.     

Energy efficiency based joint cell selection and power allocation scheme for HetNets

Heterogeneous networks (HetNets) composed of overlapped cells with different sizes are expected to improve the transmission performance of data service significantly. User equipments (UEs) in the overlapped area of multiple cells might be able to access various base stations (BSs) of the cells, resulting in various transmission performances due to cell heterogeneity. Hence, designing optimal cell selection scheme is of particular importance for it may affect user quality of service (QoS) and network performance significantly. In this paper, we jointly consider cell selection and transmit power allocation problem in a HetNet consisting of multiple cells. For a single UE case, we formulate the energy efficiency of the UE, and propose an energy efficient optimization scheme which selects the optimal cell corresponding to the maximum energy efficiency of the UE. The problem is then extended to multiple UEs case. To achieve joint performance optimization of all the UEs, we formulate an optimization problem with the objective of maximizing the sum energy efficiency of UEs subject to QoS and power constraints. The formulated nonlinear fractional optimization problem is equivalently transformed into two subproblems, i.e., power allocation subproblem of each UE-cell pair, and cell selection subproblem of UEs. The two subproblems are solved respectively through applying Lagrange dual method and Kuhn–Munkres (K-M) algorithm. Numerical results demonstrate the efficiency of the proposed algorithm.     

认知无线传感器网络中能耗有效的协作频谱感测算法

提出了一种新的认知无线传感器网络中能耗有效的协作频谱感测算法。首先,为了降低分布式传感节点的能耗,假定传感节点的瞬时信噪比和平均信噪比已知,分析频谱感测节点的能耗与最优检测门限值之间的数学模型。然后,结合感测节点选择和判决门限设定理论,研究基于判决节点选择的有效协作频谱感测方案。理论分析和仿真结果表明,算法有效地降低了认知传感器网络的节点总能耗,提高了能耗效率。     

Selection Cooperation in Heterogeneous Cooperative Networks

Selection cooperation is an attractive cooperative strategy for wireless networks due to its simplicity and efficiency. In this paper, we consider a heterogeneous cooperative network consisting of different kinds of nodes with low-cost radios where the activities of one kind of nodes are triggered by the other kinds of nodes. This is a common scenario for many networks, such as wireless sensor networks. By exploiting the transmission relationship between heterogeneous nodes, we propose a selection cooperation protocol where inducing nodes can cooperate with the following nodes after their own transmissions for improving the communication reliability of the latter nodes. Through performance analysis, we show an interesting feature that the diversity-multiplexing tradeoff of the proposed protocol does not rely on the best relay selection method and the protocol always achieves the full diversity gain. We further develop an energy-efficient best relay selection method based on power control where the power consumption is minimized without decreasing the full diversity order. Simulation results demonstrate the good performance of the protocol and the remarkable energy reduction of the proposed best relay selection method.     

无线自组网MAC层和网络层节能策略

无线自组网固有的分布式、自组织特性使得它具有更多的特殊性,对无线自组网络的设计也提出了更多的挑战。针对无线自组网协议设计中的节能技术进行综述,通过分析无线网络数据传输中能量消耗模型,得出节能设计的基本准则,然后分别对媒体访问控制层和网络层的节能策略进行介绍,给出各自进行节能设计的思路。最后指出无线自组网络的节能策略设计需要综合网络通信协议的各层的特点进行跨层设计。     

基于合作中继的OFDM蜂窝网络的QoS感知资源调度算法

针对基于中继的OFDM蜂窝网络,该文考虑具有不同QoS要求的混合业务场景,引入合作传输机制,提出了一种基于合作中继的QoS感知资源调度算法,解决了合作中继节点选取,子载波分配以及功率控制等问题。以最大化系统效用为目标,在考虑QoS业务的速率要求与基站功率约束的同时,针对中继结构引入了中继节点的功率约束。为降低计算复杂度,将原非线性组合优化问题分解为子载波分配与功率控制两个子问题。仿真结果表明,该文所提算法在能量节约、系统效用,吞吐量等性能方面都有显著优势。     

OFDMA中继网络动态节能子载波、比特和功率联合分配策略(英文)

To reduce energy consumption while maintaining users’ Quality of Service (QoS) in Orthogonal Frequency Division Multiplex Access (OFDMA) relay-enhanced networks, an adaptive energy saving subcarrier, bit and power allocation scheme is presented. The optimal subcarrier, bit and power allocation problems based on discrete adaptive modulation and coding scheme have been previously formulated for relay-enhanced networks, and have been reformulated into and solved by integer programming in optimization theory. If the system still has a surplus of subcarriers after resource allocation, we carry out Band- width Exchange (BE) to enable more subcarriers to participate in transmission to save energy. In addition, as the relay selection scheme is closely linked with resource allocation, a heuristic energy saving relay selection scheme is proposed. Simulation results indicate that the proposed algorithm consumes less energy when transmitting the same number of bits than greedy energy saving schemes, although its spectrum efficiency is worse.     

Toward green 5G heterogeneous small-cell networks: power optimization using load balancing technique

The overwhelming demand for data by an ever-increasing number of users is a great challenge wireless cellular networks are faced with. One potential solution to this issue is deploying a massive number of small cells (SCs) in the existing macro network. As SC overlay has a big role in the future wireless networks that can overcome the data traffic upsurge at little power cost, heterogeneous network (HetNet) has been viewed as a promising technology for 5G networks that extends cell coverage, improves network capacity and offloads the network traffic from the macro cell (MC) to the SCs. However, the hyper-dense SCs and their uncorrelated operation raise an important question about the joint power consumption of the macro base station (MBS) and the small base stations (SBSs) in the HetNet since the aggregate power consumption of the dense SBSs cannot be ignored. Recently, the SC sleeping technique has become a hot topic for saving energy in HetNets. To minimize power consumption in HetNets, we propose three algorithms to dynamically adapt the operation of the SBSs to active/sleep (on/off) for non-uniform user distribution in the HetNet. We investigate the general optimal power minimization problem for HetNet that requires relatively high computational complexity. Taking into account the additional increase of the traffic load brought to the MBS, a key design principle of the proposed algorithms is to switch off the SBSs gradually based on their locations, user densities in their coverage areas or the highest power that can be saved by switching some of them off, respectively. Then, we enhance the mathematical framework to make the analysis more realistic by considering the offloading between the SCs and the MBS that occurs when the traffic load exceeds SCs’ capacity. In this paper, based on the fact that user densities of SCs and MC change with time, we model the traffic on the European traffic profile and portray the power consumption of the HetNet throughout the day. Simulation results show that by applying SC sleeping and our proposed algorithms, the HetNet can save about 20% power daily. The performances of our proposed algorithms are close to that of the optimal algorithm and their computational complexities are remarkably lower.     

非对称协作通信中的时变功率分配算法

针对反射、散射影响下的非对称无线协作通信网络,提出了一种时变功率分配(Time Variant Power Allocation, TVPA)算法。根据无线协作网络中,各节点之间信道条件实时变化且不对称的特点,在信号传输过程中对信源节点和中继节点的发送信号功率进行优化分配。借助信道编码定理,将系统错误概率最小的非凸优化问题转化为最大化系统容量的凸优化问题来解。与固定功率分配(Fixed Power Allocation, FXPA)算法和平均功率分配(Average Power Allocation, AVPA)算法相比,该算法能充分利用无线信道的时变特性,重新分配功率以降低系统错误概率。在多种网络模型中的仿真结果表明,准静态瑞利衰落信道下,相比于FXPA算法,TVPA算法可获得多达5.5dB的比特错误概率性能增益。随着网络质量的进一步改善,该性能优势也逐步增大。      

传感器网络簇间通信自适应节能路由优化算法

提出了一种用于无线传感器网络簇间通信的自适应节能路由优化算法。网络中以总体通信能耗最小为首要原则建立端到端之间的路由,并对簇间通信提出了一种优化算法,使得簇首之间相互通信时,可以在直接、中继以及协作3种不同方式中自适应地选择最节能的通信方式。所提出的路由算法可确保源节点与基站通信过程中选择到最优或次优的节能路由,并可降低由于通信覆盖盲区造成的通信中断的概率。仿真结果表明,与其他传感器网络路由算法相比,所提出的路由算法在相同吞吐量和误码率前提下每一轮都消耗更少的能量,并且在不同的节点密度下都可有效地延长网络的生命周期和工作时间。     

Multi-hop routing with cooperative transmission: a cross-layer approach

Cooperative diversity techniques have received a lot of attention recently due to their ability to provide spatial diversity in fading wireless environment without the requirement of implementing multiple antenna on the same device. It increases link reliability, provides higher capacity, reduces transmit power, and extends transmission range for the same level of performance and modulation rate. In this paper, we study the achievable gain of cooperative communications from a wireless cross-layer point of view in multi hop networks. We propose two routing algorithms applicable for wireless ad hoc networks. First, we propose an edge node based on a greedy cooperative routing (ENBGCR) algorithm, where we modify the geographic routing algorithm to incorporate the cooperative transmission and extend the coverage range of the nodes. The main objective of ENBGCR algorithm is to minimize the number of hops that messages transverse to reach their destination. Then the energy-efficient cooperative routing algorithm is proposed to minimize the end-to-end total transmission power subject to end-to-end target data rate. Simulation results for both algorithms show that the proposed strategies have great improvement in terms of delay and power saving respectively for the same quality of service requirement as compared to traditional algorithms.     

Neural network optimization for energy-optimal cooperative computing in wireless communication system

Thanks to the rapidly development of optimization algorithm, more energy can be saved in the communication system when executing an application. In recent years, allocating limited resources in a cooperative manner to maximize energy efficiency in emerging sensor networks has attracted a lot of attention. In this paper, a one-layer projection neural network subject to linear equalities and bound constraints is introduced and applied in mobile wireless sensor network to make it energy-efficient by reasonably allocating local and remote data sizes when processing an application within a certain period of time. Firstly, an optimal partition to minimize the total energy consumption of the local and helper sensor nodes is proposed. Then, the neural network model is described and the optimality and convergence of the proposed model are analyzed. Finally, some simulation results are given to show that the proposed algorithm is very effective to solve the energy efficient cooperative computing.     

Optimal power‐aware relay placement for cooperative wireless sensor networks

We study the problem of optimizing the symbol error probability (SEP) performance of cluster‐based cooperative wireless sensor networks. Recent studies in literature show that an efficient relay selection protocol based on simple geographical information of the nodes to execute cooperative diversity can significantly improve the SEP performance at the destination of such networks. As well, similar line of research on optimal power allocation (for the source and relay nodes) can be found in literature. However, to achieve the best SEP performance at the destination of a cooperative wireless sensor network, joint optimization of power allocation and relay placement should be accomplished. To this aim, we reformulate the SEP of a multi‐hop cooperative communication in a general form and optimize transmitted power level and relay placement simultaneously. This analysis is developed for both amplify‐and‐forward and decode‐and‐forward relaying protocols. Simulation results demonstrate that the proposed joint optimization can effectively improve the SEP performance of the network. Copyright © 2013 John Wiley & Sons, Ltd.     

Research on energy-efficient physical-layer secure transmission mechanism in decode-and-forward cooperative networks

The maximization problem of secure energy efficiency (EE) in decode-and-forward relay networks was investigated considering the power and energy constraints in physical-layer secure transmission.An iterative algorithm for power allocation was proposed based on fractional programming and DC (difference of convex functions) programming.This algorithm jointly allocated power for source and relay nodes to achieve energy-efficient secure transmission,subject to the peak power constraint of each node and the minimum secrecy rate requirement of the system.Simulation results demonstrate that the propose algorithm can improve the secure EE significantly compared with the conventional secrecy rate maximization strategy.