TD-SCDMA无线网络利用率分析与提升

目前TD-SCDMA网络发展趋于成熟阶段,经过四期工程建设已基本达到城市全覆盖、郊县有覆盖的基本覆盖需求,已可以大规模发展新用户和迁移GSM用户减轻2G网压力。本文对TD-SCDMA系统网络利用率的统计、评估等进行了专门的研究,同时研究了在保障用户使用感知度和不影响网络KPI基础上,如何通过合理优化手段和营销策略,挖掘网络潜力,提高TD-SCDMA网络的投资收入比。

GSM网引入无线网络利用率后的容量规划和设备配置方法

首先介绍了无线网络利用率的概念,接着讨论了无线网络利用率的理想取值范围。在引入无线网络利用率的概念后,给出了计算GSM基站配置、BSCA接口配置的方法,最后又提出了提高无线网络资源利用率的有效措施。

浅谈BSC划分方法

主要介绍BSC划分的方法、需要考虑的因素及BSC入网割接需要考虑的问题,并通过工程实例来说明BSC区域划分方法。

Non-dominated sorting quantum particle swarm optimization and its application in cognitive radio spectrum allocation

In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.

Adaptive Spectr um Decision Method for Heterogeneous Cognitive Radio Networks

To improve spectrum utilization and minimize interference to Primary User (PU), an adaptive spectrum decision method is proposed for Secondary User (SU), while taking traffic load balancing and spectrum heterogeneity into consideration. Long-term statistics and current sensing results are integrated into the proposed decision method of spectrum access. Two decision methods, namely probability based and sensing based, are presented, compared and followed by performance analysis in terms of delay. For probability based spectrum decision, Short-Time-Job-First (STJF) priority queuing discipline is employed to minimize average residual time and theoretical conclusion is derived in a novel way. For sensing based decision we treat the interrupted service of SU as newly incoming and re-decision process is initialized to find available spectrum in a First-Available-First-Access (FAFA) fashion. Effect of sensing error in PHY layer is also analyzed in terms of extended average residual time. Simulation results show that, for relatively low arriving rate of SU traffic, the proposed spectrum decision method yields at least a delay reduction of 39.5% compared with non-adaptive method. The proposed spectrum decision can significantly improve delay performance even facing sensing errors, which cause performance degeneration to both PU and SU.

A Survey of Security Issues in Cognitive Radio Networks

In the last decade,cognitive radio(CR) has emerged as a major next generation wireless networking technology,which is the most promising candidate solution to solve the spectrum scarcity and improve the spectrum utilization.However,there exist enormous challenges for the open and random access environment of CRNs,where the unlicensed secondary users(SUs) can use the channels that are not currently used by the licensed primary users(PUs) via spectrum-sensing technology.Because of this access method,some malicious users may access the cognitive network arbitrarily and launch some special attacks,such as primary user emulation attack,falsifying data or denial of service attack,which will cause serious damage to the cognitive radio network.In addition to the specifi c security threats of cognitive network,CRNs also face up to the conventional security threats,such as eavesdropping,tampering,imitation,forgery,and noncooperation etc..Hence,Cognitive radio networks have much more risks than traditional wireless networks with its special network model.In this paper,we considered the security threats from passive and active attacks.Firstly,the PHY layer security is presented in the view of passive attacks,and it is a compelling idea of using the physical properties of the radio channel to help provide secure wireless communications.Moreover,malicious user detection is introduced in the view of active attacks by means of the signal detection techniques to decrease the interference and the probabilities of false alarm and missed detection.Finally,we discuss the general countermeasures of security threats in three phases.In particular,we discuss the far reaching effect of defensive strategy against attacks in CRNs.

ARROW-WTCP:A fast transport protocol based on explicit congestion notification over wired/wireless networks

An explicit congestion notification (ECN)-based distributed transport protocol,ARROW-WTCP (AcceleRate tRansmission towards Optimal Window size TCP for Wireless network),was proposed.The ARROW-WTCP enables feasible deployment of ARROW-TCP from wired to wireless networks by providing a joint design of source and router algorithms.The protocol obtains the actual capacity of the wireless channel by calculating the queue variation in base station (BS) and adjusts the congestion window by using the feedback from its bottleneck link.The simulation results show that the ARROW-WTCP achieves strong stability,max-min fairness in dynamic networks,fast convergence to efficiency without introducing much excess traffic,and almost full link utilization in the steady state.It outperforms the XCP-B (eXplicit Control Protocol Blind),the wireless version of XCP,in terms of stability,fairness,convergence and utilization in wireless networks.

Survivable Routing Protocol for Green Wireless Mesh Networks Based on Energy Efficiency

This paper proposes a new Energyefficient Survivable Routing Protocol(ESRP)based on solar energy and wind mixed for power supply in green wireless mesh networks(WMNs).The ESRP combines hop penalty strategy and flooding delaying strategy to improve the performances of traditional routing protocol.This paper uses QualNet to simulate and verify the performances of proposed ESRP.Compared with the traditional routing protocol,the simulation results show that the energy utilization of ESRP is more efficient by 13%.At the same time,ESRP is more load-balanced to postpone the appearance of the first energy depletion node and reduce the number of energy depletion nodes,and thus it effectively improves network survivability.

Hierarchical Cognition Cycle for Cognitive Radio Networks

Cognitive radio(CR) can bring about remarkable improvement in spectrum utilization.Different cognition cycles have been proposed in recent years.However,most of the existing works only emphasize functional or operational aspects of cognition cycle,regardless of other indispensable aspects and the connection between them.To deal with the emerging situation of "data rich,information vague,knowledge poor" in cognitive radio networks(CRNs),we propose the hierarchical cognition cycle(HCC) as a new transdisciplinary research field in this paper.HCC investigates a fundamental problem,which is how to manage available resources in the complex environment to meet various demands in CRN.A comprehensive theoretical framework of HCC is established in terms of the core,the essence loop,the function loop,the operation loop,and the external loop of HCC.The reduction of uncertainty in CRN is studied and several new metrics in HCC are defined.Furthermore,a few research challenges ahead are presented as well.

Energy Efficiency-Based Decision Making in Cognitive Radio Networks

As a constraint for smart devices,energy consumption has attract people's attention for a long time period. How to get higher resource utilization with less energy consumption is a challenge for cognitive radio networks. Secondary users have to participate in spectrum sensing at the cost of energy and access idle spectrum without interfering primary users. However,not all participating secondary users can access idle spectrum. How to ensure the participation users access spectrum efficiently with a larger probability is an urgent problem to be solved. We propose an Energy Efficiency-based Decision Making(EEDM) for cognitive radio networks,which fully considers residual energy and probability of obtaining spectrum resources. Simulation and analysis show that the proposed scheme can maximize proportion of allocated users under the premise of ensuring the accuracy of spectrum sensing,then balance users' energy consumption and access efficiency,so as to effectively improve the utilization of spectrum resources.