基于改进遗传算法的C-RAN网络动态无线资源分配

针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(Remote Radio Head,RRH)选择、子载波分配和RRH功率分配三个维度进行研究.首先,根据传统的C-RAN系统传输模型和QoS约束在时变业务环境下建立了以发射功率为变量,以吞吐量最大为优化目标的优化问题;然后,基于改进的遗传算法,将原优化方案转变为通过优化RRH选择、子载波分配和RRH功率分配来达到提高系统吞吐量的目的;最后,将改进的遗传算法与其他智能算法在种群规模变化下进行了时间复杂度对比.实验结果表明,所提算法具有较低时间复杂度,所提资源分配方案下的平均吞吐量增益为17％.     

云接入网络中基于容量最大化的射频拉远头选择算法设计

不同于传统的LTE-Advanced网络,云接入网络(C-RAN)通过前程链路将复杂数据处理从射频拉远头(RRH)转移至基带单元池(BBU Pool)。然而,由于C-RAN前程链路容量有限,系统总吞吐量并不一定能显著提升。在本文中,我们通过优化RRHs选择实现吞吐量的最大化。更准确地说,本文在前程容量约束条件下设计了一种选择活动RRHs集的优化算法,以实现系统容量的最大化。此外,本文分别推导了低信噪比（Low SNR）与高信噪比(High SNR)下,选择RRHs数目的渐进最优的闭合表达式。仿真结果表明,比起其他方案,本文所提出的RRH选择方案能够在有限的前程容量限制与任意给定RRHs数量下,有效实现吞吐量的提升。      

Spectral and energy efficient cognitive radio‐aided heterogeneous cellular network with uplink power adaptation

In future heterogeneous cellular networks, cognitive radio compatible with device to device communication technique can be an aid to further enhance system spectral and energy efficiency. The unlicensed smart devices (SDs) are allowed to detect the available licensed spectrum and utilise the spectrum resource which is detected as not being used by the licensed users. In this work, we propose such a system and provide comprehensive analysis of the effect of selection of SDs' frame structure on the energy efficiency, throughput and interference. Moreover, uplink power control strategy is also considered where the licensed users and SDs adapt the transmit power based on the distance from their reference receivers. The optimal frame structure with power control is investigated under high‐signal‐to‐noise ratio (SNR) and low‐SNR network environments. The impact of power control and optimal sensing time and frame length, on the achievable energy efficiency, throughput and interference are illustrated and analysed by simulation results. It has been also shown that the optimal sensing time and frame length which maximizes the energy efficiency of SDs strictly depends on the power control factor employed in the underlying network such that the considered power control strategy may decrease the energy efficiency of SDs under very low‐SNR regime. Copyright © 2016 John Wiley & Sons, Ltd.     

Adaptive Energy Detection Based Solution for Fronthaul Problem in C-RAN

It hasbeen anticipated that the fifth generation (5G) wireless systems will deliver an efficient growth of the energy and spectral efficiency. To accomplish these goals, centralized radio access networks (C-RAN) is presented as the advanced wireless access networks paradigm with centralized baseband units (BBUs) and remote radio heads (RRHs). Although it is affected by Common Public Radio Interface (CPRI) limitations which requires high bandwidth for existing BBU/RRH interfaces. Moreover, the fronthaul links the BBU and RRH. But CPRI limits the deployment of C-RAN for fronthaul networking due to its fixed-rate fronthaul interface which transmit CPRI streams even in the absence of traffic load. However, this causes data transmission inefficient. So, the classical fronthauling method demands high bandwidth and the failure of fronthaul will cause losing a very high bandwidth. The purpose of this paper is to develop energy detection (ED) based algorithm which permits the secondary users to use the channel without interfering the primary users, so that the bandwidth in the fronthaul can be used in an efficient manner. A dynamic threshold with noise uncertainty based ED algorithm is proposed in this paper. It compares the fixed threshold with dynamic threshold by comparing probability of detection with probability of false alarm. Finally, by using this proposed algorithm, it can be concluded that performance of the probability of detection improves even with the presence of noise uncertainty.     

Toward the Energy Efficiency of Resource Allocation Algorithms for OFDMA Downlink MIMO Systems

The problem of the simultaneous multi-user resource allocation algorithm in orthogonal frequency division multiple access (OFDMA) based systems has recently attracted significant interest. However, most studies focus on maximizing the system throughput and spectral efficiency. As the green radio is essential in 5G and future networks, the energy efficiency becomes the major concern. In this paper, we develop four resource allocation schemes in the downlink OFDMA network and the main focus is on analyzing the energy efficiency of these schemes. Specifically, we employ the advanced multi-antenna technology in a multiple input-multiple output (MIMO) system. The first scheme is based on transmit spatial diversity (TSD), in which the vector channel with the highest gain between the base station (BTS) and specific antenna at the remote terminal (RT) is chosen for transmission. The second scheme further employs spatial multiplexing on the MIMO system to enhance the throughput. The space-division multiple-access (SDMA) scheme assigns single subcarrier simultaneously to RTs with pairwise “nearly orthogonal” spatial signatures. In the fourth scheme, we propose to design the transmit beamformers based on the zero-forcing (ZF) criterion such that the multi-user interference (MUI) is completely removed. We analyze the tradeoff between the throughput and power consumption and compare the performance of these schemes in terms of the energy efficiency.     

Energy efficiency comparison between distributed and co‐located MIMO systems

Energy efficiency (EE) is becoming more and more important in future wireless communications because of limited battery power in mobile terminals. In this paper, we compare EE of the distributed MIMO (D‐MIMO) and co‐located MIMO (C‐MIMO) in uplink systems. Taking into account both circuit and transmit power, we derive an analytical expression for EE of D‐MIMO and C‐MIMO systems in a composite Rayleigh‐lognormal channel. What is more, an optimization algorithm is proposed to get the optimal EE values while satisfying given spectral efficiency requirement for both D‐MIMO and C‐MIMO systems. Simulation results show that D‐MIMO systems are more energy effective than C‐MIMO systems when considering the realistic systems, and the optimal EE can be obtained by the proposed algorithm while satisfying given spectral efficiency requirement. Copyright © 2012 John Wiley & Sons, Ltd.     

Genetic algorithm‐based content distribution strategy for F‐RAN architectures

Fog radio access network (F‐RAN) architectures provide markedly improved performance compared to conventional approaches. In this paper, an efficient genetic algorithm‐based content distribution scheme is proposed that improves the throughput and reduces the transmission delay of a F‐RAN. First, an F‐RAN system model is presented that includes a certain number of randomly distributed fog access points (F‐APs) that cache popular content from cloud and other sources. Second, the problem of efficient content distribution in F‐RANs is described. Third, the details of the proposed optimal genetic algorithm‐based content distribution scheme are presented. Finally, simulation results are presented that show the performance of the proposed algorithm rapidly approaches the optimal throughput. When compared with the performance of existing random and exhaustive algorithms, that of the proposed method is demonstrably superior.     

Dynamic theoretic proactive caching placement game for energy saving in H‐CRAN

Edge caching is an effective feature of the next 5G network to guarantee the availability of the service content and a reduced time response for the user. However, the placement of the cache content remains an issue to fully take advantage of edge caching. In this paper, we address the proactive caching problem in Heterogeneous Cloud Radio Access Network (H‐CRAN) from a game theoretic point of view. The problem is formulated as a bargaining game where the remote radio heads (RRHs) dynamically negotiate and decide which content to cache in which RRH under energy saving and cache capacity constraints. The Pareto optimal equilibrium is proved for the cooperative game by the iterative Nash bargaining algorithm. We compare between cooperative and noncooperative proactive caching games and demonstrate how the selfishness of different players can affect the overall system performance. We also showed that our cooperative proactive caching game improves the energy consumption of 40% as compared with noncooperative game and of 68% to no‐game strategy. Moreover, the number of satisfied requests at the RRHs with the proposed cooperative proactive caching scheme is significantly increased.     

下一代协作式无线接入网的网络架构及性能

伴随着网络扁平化的趋势,下一代的无线接入网逐渐向分布式方向发展,基以协作的方式进行无线资源优化配置来提高空口的频谱效率。无线接入网通过基带资源聚合等手段,可以极大地提升基站设备的利用效率同时更有效地利用机房空间,满足低成本建设与维护网络的要求。     

Joint impact of sensing time and SPRF parameter on the performance of a continuous energy harvesting cooperative cognitive radio network

Joint impact of sensing time and signal power raise factor is studied for an improved energy detector–based energy harvesting cooperative cognitive radio network. All the cognitive radio nodes harvest energy either from radio frequency resources or from non–radio frequency resources. The probability density function of harvested energy from both the sources is exponentially distributed. Novel theoretical expressions for harvested energy and throughput are derived. Impact of several sensing parameters and a device constraint on the outage is studied. Optimal values of sensing time and signal power raise factor parameter pair are estimated for maximum harvested energy and maximum throughput. Energy efficiency of the network is also evaluated, and impact of sensing time on it is indicated.     

C-RAN：面向绿色的未来无线接入网演进

 在高速发展的移动业务和日趋激烈的竞争环境下,移动运营商面临着多方面的挑战：高额的能耗、高涨的建设和运维成本、紧张的频谱资源、快速增长的业务流量以及日趋严峻的成本压力。为解决这些挑战并追求未来可持续的增长,根据现网条件和技术进步的趋势,提出了面向绿色演进的新型无线接入网构架C-RAN。C-RAN是基于集中化处理(Centralized),协作式无线电(Cooperative Radio)和实时云计算构架(Real-time Cloud Infrastructure)的无线接入网构架, 集中式基带处理可以大大减少覆盖同样区域所需基站的数量;面向协作的无线远端模块和天线可以提高系统频谱效率;基于开放平台的实时云型基础设施和基站虚拟化技术可以降低成本,共享处理资源,减少能源消耗,提高基础设施利用率。这些特点能够很好地解决移动运营商所面临的上述挑战,并满足营收和未来移动互联网业务同步发展要求。     

Sensing throughput trade‐off for an energy efficient cognitive radio network under faded sensing and reporting channel

The trade‐off between sensing time and throughput is investigated in the context of an energy‐efficient cognitive radio network considering both the sensing and reporting channels are Rayleigh faded, while the existing literature considered the fading in sensing channel only. In this paper, such a trade‐off is re‐examined under Rayleigh faded sensing as well as reporting channel. Novel analytical expressions for overall detection probability and false alarm probability are developed under such scenario. The performance is investigated in terms of detection probability, false alarm probability, throughput and energy efficiency of the network for different sensing parameters such as sensing time, number of samples, sensing channel signal‐to‐noise ratio and reporting channel signal‐to‐noise ratio. Our analysis shows that the quality of the reporting channel significantly affects the trade‐off performance of the network. Copyright © 2015 John Wiley & Sons, Ltd.     

Throughput and energy performance of TCP on a wideband CDMA air interface

In this paper, we present a study on the performance of TCP, in terms of both throughput and energy consumption, in the presence of a wideband CDMA radio interface typical of third generation wireless systems. The results show that the relationship between throughput and average error rate is largely independent of the network load, making it possible to introduce a universal throughput curve, empirically characterized, which gives throughput predictions for each value of the user error probability. Furthermore, the study of the energy efficiency shows the possibility to select an optimal power control threshold to maximize the trade‐off between throughput and energy, thereby potentially achieving very significant energy gains. Copyright © 2001 John Wiley & Sons, Ltd.     

Energy Efficiency Architecture Design for Heterogeneous Cellular Networks

Heterogeneous cellular networks (HetNets) have emerged as a new promising paradigm to further enhance capacity, where multiple types of low power smallcells are overlaid in a high power macrocell. They provide more opportunities to explore the potential cognition and cooperation diversities to improve the spectral efficiency. On the other hand, energy efficiency is a critical performance metric, which deserves more attention from academia, industry, and standardization, in particular, in scenarios where smallcells are densely deployed. In this paper, a systematic architecture is presented to efficiently utilize network resources and thus improve the overall energy efficiency. The architecture is referred to as OCRT because it combines a multi‐tier energy efficiency considerations of operators, core networks, radio access networks and terminals (e.g., OCRT). Furthermore, a corresponding triply‐cycle‐based functional structure is proposed for the OCRT to make various interactions between the corresponding functional entities clear. An implementation scheme of OCRT based on cognitive information interaction cycle and an energy efficiency‐aware protocol is presented. Finally, a use case of the presented OCRT green design is provided for energy efficiency optimization in a cognition‐and‐cooperation‐characterized HetNet. Copyright © 2015 John Wiley & Sons, Ltd.     

A joint sensing and transmission power control policy for RF energy harvesting cognitive radio networks

We consider a radio frequency energy harvesting cognitive radio network in which a secondary user (SU) can opportunistically access channel to transmit packets or harvest radio frequency energy when the channel is idle or occupied by a primary user. The channel occupancy state and the channel fading state are both modeled as finite state Markov chains. At the beginning of each time slot, the SU should determine whether to harvest energy for future use or sense the primary channel to acquire the current channel occupancy state. It then needs to select an appropriate transmission power to execute the packet transmission or harvest energy if the channel is detected to be idle or busy, respectively. This sequential decision‐making, done to maximize the SU's expected throughput, requires to design a joint spectrum sensing and transmission power control policy based on the amount of stored energy, the retransmission index, and the belief on the channel state. We formulate this as a partially observable Markov decision process and use a computationally tractable point‐based value iteration algorithm. Section 5 illustrate the significant outperformance of the proposed optimal policy compared with the optimal fixed‐power policy and the greedy fixed‐power policy.     

Energy‐Connectivity Tradeoff through Topology Control in Wireless Ad Hoc Networks

In this study, we investigate topology control as a means of obtaining the best possible compromise between the conflicting requirements of reducing energy consumption and improving network connectivity. A topology design algorithm capable of producing network topologies that minimize energy consumption under a minimum‐connectivity constraint is presented. To this end, we define a new topology metric, called connectivity efficiency, which is a function of both algebraic connectivity and the transmit power level. Based on this metric, links that require a high transmit power but only contribute to a small fraction of the network connectivity are chosen to be removed. A connectivity‐efficiency‐based topology control (CETC) algorithm then assigns a transmit power level to each node. The network topology derived by the proposed CETC heuristic algorithm is shown to attain a better tradeoff between energy consumption and network connectivity than existing algorithms. Simulation results demonstrate the efficiency of the CECT algorithm.     

Throughput and delay limits of chirp spread spectrum‐based IEEE 802.15.4a

The IEEE 802.15.4 standard is designed to provide a low‐power, low data rate protocol offering a high reliability. As an amendment to this standard, IEEE 802.15.4a introduces new options for physical layer to enable precision ranging. In this work, we analyzed the theoretical throughput and delay bounds of the unslotted version of chirp spread spectrum PHY‐based 802.15.4a. The formulae for transmission between one sender and one receiver for an ideal channel with no transmission errors are given. The throughput and delay bounds are derived for different frequency bands and data rates. Additionally, to measure spectral utilization, we measured the bandwidth efficiency for both the standards. We also compared our results with IEEE 802.15.4. The comparative analysis concludes that the performance of 802.15.4a exceeds 802.15.4 in terms of throughput and delay. The analytical results of throughput are verified by computer simulations. Copyright © 2011 John Wiley & Sons, Ltd.     

基于带缓存的云接入网络最优能效设计

在云接入网络(Cloud-RAN)中,现有工作大多假定射频拉远头(RRH)不具备缓存功能。然而下一代通信网络具有以内容为中心的特性,因此在Cloud-RAN中考虑带缓存的RRHs也变得有必要。该文考虑在Cloud-RAN中有效设计缓存方案,并通过资源分配有效减轻前程链路负担。假设系统采用正交频分多址接入(OFDMA)技术,通过联合优化子载波(SC)分配,RRH选择与传输功率,最小化系统下行总功耗,并通过拉格朗日对偶分解转化非凸问题,获得最优分配方案。仿真结果表明,比起其它缓存方案,该文提出的优化算法可以有效地提升系统能效,满足未来通信需求。     

LTE系统中基于负载的能量有效性调度策略

针对绿色通信中如何能在保证一定服务质量的前提下降低能量消耗这一关键问题,根据带宽交换能量的思想,综合考虑系统吞吐量和用户间公平性,提出了LTE 下行传输中基于负载的资源调度策略,通过降低频谱效率换得能量效率的提高,以达到节能的目的。仿真结果表明,所提的两个算法在满足用户速率要求的同时都能在很大程度上降低发射功率,且保证了用户间的公平性。     

Dynamic and location‐based power allocation mechanism for inter‐cell interference mitigation in 5G heterogeneous cellular network

In this paper, a dynamic and location‐based power allocation mechanism is proposed which could be adopted at both macrocell (MC) and overlaid fixed/mobile small cells (SCs) to mitigate inter‐cell interference (ICI) effects in heterogeneous cellular networks (HetCNs). The proposed Dynamic Power Allocation based on User Location (DPAUL) mechanism allows both MCs and deployed fixed/mobile SCs to dynamically allocate transmit power to its serving base stations (BSs) based on the location of a user in the cell. The paper illustrates the mitigation of dynamic downlink interferences occurring due to the mobility of SCs and users. The mobility of cell and its users is analyzed by introducing the Cell‐User mobility (CUM) model in the network. The proposed DPAUL mechanism is compared with the authors' other ICI mitigation techniques: Dynamic Fixed Region Cooperation (DFRC) and Dynamic Power Allocation Mechanism (DPAM). The network metrics Sumrate, User throughput, Energy‐efficiency, and Outage probability are investigated with allocation of sub 6 GHz and mmWave spectrums at MCs and fSCs/mSCs, respectively.