MODELING RADIO RESOURCE MANAGEMENT IN COGNITIVE RADIO SYSTEM BASED ON OFDMA USING COLORED PETRI NET

Cognitive Radio(CR) system based on Orthogonal Frequency Division Multiple Access(OFDMA),such as Wireless Regional Area Networks(WRAN) and Worldwide Interoperability for Microwave Access(WiMAX),often attempt to improve performance via dynamic radio resource management,which is characterized as concurrent processing of different traffic and nondeterministic system capacity.It is essential to design and evaluate such complex system using proper modeling and analysis tools.In the previous work,most of the communication systems were modeled as Markov Chain(MC) and Stochastic Petri Nets(SPN),which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic.In this paper,we develop an executable top-down hier-archical Colored Petri Net(CPN) model for adaptive OFDMA CR system,and analyze its performance using CPN tools.The results demonstrate that the CPN can model different radio resource manage-ment algorithms in CR Systems,and the CPN tools require less computational effort than Markov model using Matlab,with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed.

Traffic Characteristics Based Dynamic Radio Resource Management in Heterogeneous Wireless Networks

The traffic with tidal phenomenon in Heterogeneous Wireless Networks(HWNs)has radically increased the complexity of radio resource management and its performance analysis.In this paper,a Simplified Dynamic Hierarchy Resource Management(SDHRM)algorithm exploiting the resources dynamically and intelligently is proposed with the consideration of tidal traffic.In network-level resource allocation,the proposed algorithm first adopts wavelet neural network to forecast the traffic of each sub-area and then allocates the resources to those sub-areas to maximise the network utility.In connection-level network selection,based on the above resource allocation and the pre-defined QoS requirement,three typical network selection policies are provided to assign traffic flow to the most appropriate network.Furthermore,based on multidimensional Markov model,we analyse the performance of SDHRM in HWNs with heavy tailed traffic.Numerical results show that our theoretical values coincide with the simulation results and the SDHRM can improve the resource utilization.

ICI Management for Efficient Radio Resource Allocation in Multi-Cell OFDMA Networks

Two Inter-cell Interference (ICI) management algorithms: Primary Interference Balancing (PIB) algorithm and Interfering Bits Loading Avoidance (IBLA) algorithm are proposed for canceling the ICI effects which the existing efficient radio resource allocation algorithms do not consider. The efficient radio resource allocation algorithm, i.e., Pre-assignment and Reassignment (PR) algorithm, obtains the lowest complexity and achieves good throughput performance in single cell OFDMA system. However, in multi-cell multi-sector OFDMA networks, PR algorithm is not applicable because it does not take ICI into consideration. The proposed PIB algorithm balances the number of loading bits for the desired User Equipment (UE) and the major interfering UE, as well as optimizes the SINR performance; meanwhile, IBLA avoids loading certain number of interfering bits which would make SINR unqualified. Simulations confirm the ICI management effectiveness and feasibility of both the proposals.

An autonomic joint radio resource management algorithm in end-to-end reconfigurable system

This paper presents the multi-step Q-learning(MQL)algorithm as an autonomic approach to thejoint radio resource management(JRRM)among heterogeneous radio access technologies(RATs)in theB3G environment.Through the'trial-and-error'on-line learning process,the JRRM controller can con-verge to the optimized admission control policy.The JRRM controller learns to give the best allocation foreach session in terms of both the access RAT and the service bandwidth.Simulation results show that theproposed algorithm realizes the autonomy of JRRM and achieves well trade-off between the spectrum utilityand the blocking probability comparing to the load-balancing algorithm and the utility-maximizing algo-rithm.Besides,the proposed algorithm has better online performances and convergence speed than theone-step Q-learning(QL)algorithm.Therefore,the user statisfaction degree could be improved also.

ZTE 's WCDMA Radio Resource Management Strategy

WCDMA Radio Resource Management (RRM) controls the allocation and usage of all radio resources. The purpose of RRM is to have optimal coverage and capacity while ensuring the QoS. RRM directly affects the system performance. As the soul of system control, it includes power control, handoff control, load control, admission control, code allocation, etc. This paper introduces the RRM strategy of ZTE's WCDMA equipment.

AN EFFICIENT RADIO RESOURCE MANAGEMENT STRATEGY FOR ADAPTIVE OFDM CELLULAR SYSTEMS

This paper presents an efficient Radio Resource Management (RRM) strategy for adaptive Orthogo-nal Frequency Division Multiplexing (OFDM) cellular systems. In the proposed strategy, only those users who have the same distance from their base stations can reuse a same subcarrier. This can guarantee the received Carrier-to-Interference ratio (C/I) of each subcarrier to be acceptable as required by system planning. Then by employing different modulation scheme on each subcarrier according to its received C/I, system spectral effi-ciency can be gracefully increased. Analytical and simulation results show that the spectral efficiency is im-proved by 40% without sacrificing the Bit Error Rate (BER) performance and call blocking probability and sys-tem capacity of the proposed strategy is better than conventional systems.

Spectrum Resource Management of Cognitive Radio

As the most important technology of CR, the wireless spectrum resource management technology is the key to CR performance improvement. By introducing the concept of resource space to describe wireless spectrum resource management in the field of CR technology, a data system of wireless resource management is formed that covers wireless spectrum resource space, resource grid and available resource atlas. Besides, the corresponding lamination distributional management structure and the resource management database are constructed. The resources description system and the management structure will become the theoretical concept foundation and reference of the CR spectrum resources management technology.

INVESTIGATION OF UPLINK RADIO RESOURCE MANAGEMENT SCHEMES FOR MULTI-SERVICES IN TDD-CDMA SYSTEMS EMPLOYING SMART ANTENNAS

In this paper, a theoretical analysis of Time Division Duplex-Code Division Multiple Access (TDD-CDMA) uplink capacity constraint is presented when employing the smart antenna techniques. The evaluation formulations of capacity and load for multi-services are proposed. In order to maximize the throughput, the objective of optimization is proposed, and an advanced uplink resource management algo-rithm is developed. The proposed algorithm based on the least interference admission control scheme focuses on the maximum throughput for the circuit switched multi-services. The simulation results show that the pro-posed strategy has a significant improvement in throughput when the optimum admission control threshold is set.

RRM空闲态下异系统多小区互操作实现

小区重选作为空闲态下异系统互操作研究领域的重要组成部分,是验证异系统多小区互操作能否实现的重要标志。鉴于此,设计了一种基于TTCN-3(Testing and Test Control Notation version3)的TD-LTE/TD-SCDMA终端RRM(Radio Resource Management)一致性测试小区重选测试例。首先搭建基于TTCN-3的RRM一致性测试平台,此平台具有调试能力强,自动化测试功能,测试环境更加真实,以及灵活的可视化界面等优点,然后基于此平台编写TD-LTE/TD-SCDMA小区重选脚本,最后在平台上顺利运行,验证了基于TTCN-3的异系统多小区之间互操作的可行性。

MIMO系统中连续博弈RRM算法

提出一种基于博弈论的连续博弈无线资源管理算法,将博弈论数学模型应用于多输入-多输出系统无线资源管理中,把其中的参数映射为博弈论数学模型中的“局中人”,将参数变化描述为“局中人”博弈过程.在仿真中,比较该算法与传统联合波束成形及功率控制算法.仿真结果表明,该算法在节省发射功率的同时,可提高输出信干噪比,达到两者最佳均衡.同时可有效克服期望的导引矢量和实际的导引矢量不匹配问题,使天线能准确对准期望用户方向,并能抑制干扰方向的信号,起到“零陷”作用.

通信-感知-计算-存储深度融合下的无线资源管控

为满足多样化应用与极致性能需求,6G网络将提供通信、感知、计算与存储的融合服务,实现无缝泛在连接、全域精准感知的愿景。围绕通感算存深度融合下无线资源管控研究,首先简要介绍了通感算存融合网络的产生背景和无线资源管控研究现状,并对通感算存深度融合的灵活组网架构构建与关键技术进行了阐述。进一步地,为实现通感算存深度融合下的多域资源高效管控,对移动边缘计算网络和通感一体化网络的无线资源管控关键技术进行了分析讨论,并在此基础上探讨了通信、感知、计算与存储融合下的无线资源管控相关技术难点。

一种通用的Beyond 3G Multi-Radio接入架构

下一代移动通信网(Beyond 3G)是多种无线接入(Multi-Radio)共存的融合网络.如何有效集成异构无线网络,优化使用全部的无线资源是B3G研究领域内关键课题之一.在分析目前多种异构无线网络整合方案的基础上,借鉴欧洲IST 6th框架中Multi-Radio接入架构的基本思想,考虑在链路层实现异构无线网络之间的整合,从而提出一种通用B3G Multi-Radio接入架构模型,该模型可以无缝融合多种无线接入技术、有效利用全网无线资源.

A New Fairness-Oriented Packet Scheduling Scheme with Reduced Channel Feedback for OFDMA Packet Radio Systems

In this paper, we propose a flexible and fairness-oriented packet scheduling approach for 3GPP UTRAN long term evolution (LTE) type packet radio systems, building on the ordinary proportional fair (PF) scheduling principle and channel quality indicator (CQI) feedback. Special emphasis is also put on practical feedback reporting mechanisms, including the effects of mobile measurement and estimation errors, reporting delays, and CQI quantization and compression. The performance of the overall scheduling and feedback re-porting process is investigated in details, in terms of cell throughput, coverage and resource allocation fairness, by using extensive quasistatic cellular system simulations in practical OFDMA system environment with frequency reuse of 1. The performance simulations show that by using the proposed modified PF ap-proach, significant coverage improvements in the order of 50% can be obtained at the expense of only 10-15% throughput loss, for all reduced feedback reporting schemes. This reflects highly improved fairness in the radio resource management (RRM) compared to other existing schedulers, without essentially com-promising the cell capacity. Furthermore, we demonstrate the improved functionality increase in radio re-source management for UE’s utilizing multi-antenna diversity receivers.

基于DSA与JRRM联合的无线网络资源分配方法

为了实现不同运营商运营的异构网络的无线资源的有效分配,提出了一种基于动态频谱接入(DSA)与联合无线资源管理(JRRM)联合的无线通信频谱资源分配方案。该方案可实现DSA方法和JRRM方法的特性互补,同时将博弈论引入到资源分配的决策过程中,利用夏普里值模型使参与博弈的各方的收益达到最大化。通过与DAS方法及JRRM方法的比较和无线网络通信负载的模拟实验分析表明,此方案改进了无线资源利用率。

A Hybrid Offline-Online Approach to Adaptive Downlink Resource Allocation Over LTE

Radio resource management mechanisms in current and future wireless networks is expected to face an enormous challenge due to the ever increasing demand for bandwidth and latency sensitive applications on mobile devices. This is because an optimal resource allocation scheme which attempts to multiplex the available bandwidth in order to maximize Quality of service(QoS), will pose an exponential computational burden at eNodeB. In order to minimize such computational overhead, this work proposes a hybrid offline-online resource allocation strategy which effectively allocates all the available resources among flows such that their QoS requirements are satisfied. The flows are firstly classified into priority buckets based on real-time criticality factors. During the offline phase, the scheduler attempts to maintain the system load within a pre-specified safe threshold value by selecting an appropriate number of buckets. This offline selection procedure makes use of supervisory control theory of discrete event systems to synthesize an offline scheduler. Next, we have devised an online resource allocation strategy which runs on top of the offline policy and attempts to minimize the impact of the inherent variability in wireless networks. Simulation results show that the proposed scheduling framework is able to provide satisfactory QoS to all end users in most practical scenarios.

Priority-Based Resource Allocation for Downlink OFDMA Systems Supporting RT and NRT Traffics

Efficient radio resource management is essential in Quality-of-Service (QoS) provisioning for wireless communication networks. In this paper, we propose a novel priority-based packet scheduling algorithm for downlink OFDMA systems. The proposed algorithm is designed to support heterogeneous applications consisting of both real-time (RT) and non-real-time (NRT) traffics with the objective to increase the spectrum efficiency while satisfying diverse QoS requirements. It tightly couples the subchannel allocation and packet scheduling together through an integrated cross-layer approach in which each packet is assigned a priority value based on both the instantaneous channel conditions as well as the QoS constraints. An efficient suboptimal heuristic algorithm is proposed to reduce the computational complexity with marginal performance degradation compared to the optimal solution. Simulation results show that the proposed algorithm can significantly improve the system performance in terms of high spectral efficiency and low outage probability compared to conventional packet scheduling algorithms, thus is very suitable for the downlink of current OFDMA systems.

An efficient resource optimization scheme for D2D communication

With the rapid development of wireless technologies,wireless access networks have entered their Fifth-Generation(5G)system phase.The heterogeneous and complex nature of a 5G system,with its numerous technological scenarios,poses significant challenges to wireless resource management,making radio resource optimization an important aspect of Device-to-Device(D2D)communication in such systems.Cellular D2D communication can improve spectrum efficiency,increase system capacity,and reduce base station communication burdens by sharing authorized cell resources;however,can also cause serious interference.Therefore,research focusing on reducing this interference by optimizing the configuration of shared cellular resources has also grown in importance.This paper proposes a novel algorithm to address the problems of co-channel interference and energy efficiency optimization in a long-term evolution network.The proposed algorithm uses the fuzzy clustering method,which employs minimum outage probability to divide D2D users into several groups in order to improve system throughput and reduce interference between users.An efficient power control algorithm based on game theory is also proposed to optimize user transmission power within each group and thereby improve user energy efficiency.Simulation results show that these proposed algorithms can effectively improve system throughput,reduce co-channel interference,and enhance energy efficiency.

面向6G的用户为中心网络研究综述

与第5代移动通信网络(5G)相比,第6代移动通信网络(6G)有望引入新的性能指标和应用方案,如全球覆盖、更高的频谱/能源/成本效率、更高的智能和安全水平。用户为中心网络(UCN)将成为实现6G的关键推动者,因为其突破了传统基站为中心网络并与信息产业的新兴技术形成了有效融合。该文将从物理层的信道估计和预测、网络上层的性能分析以及链路层的无线资源管理等方面综述这一新型网络的研究现状。首先,讨论和分析UCN的概念和总体网络架构;其次,总结UCN网络中信道估计预测方法、性能分析策略和无线资源管理(RRM)方案;最后,在广泛的调研基础上,探讨UCN网络中的开放性问题,为今后的研究方向提供思路。此综述旨在使读者快速而全面地了解UCN的当前技术状况,从而吸引更多的研究人员进入这一领域。

基于BP和RBF神经网络的C-V2X无线资源管理

为了提升蜂窝车联网(Cellular Vehicle-to-Everything,C-V2X)资源复用的有效性和降低终端间的干扰,提出通过神经网络对未来时刻车流量的预测辅助无线资源管理方案。依据车载单元(On Board Unit,OBU)与路侧单元(Road Side Unit,RSU)间的车联网消息,获取RSU覆盖区域内各时刻的车流情况,分别采用BP(Back Propagation)神经网络和RBF(Radial Basis Function)神经网络进行短时交通流预测。RSU根据预测结果进行自适应分簇,簇间复用相同资源,簇内进行资源池的划分,RSU覆盖内的OBU在划分的资源池中选择发送资源,从而减少终端间的干扰,并保证热点区域车辆拥有更多的资源。仿真结果表明,在道路交通拥塞的场景下,所提方案的数据包接收率较标准中的方案提升14%,较典型文献方案提升10%,保证了通信的可靠性。