基于LTE-A技术无线资源管理的跨层联合博弈

提出了一种在LTE-A(long term evolution advanced,长期演进技术增强)技术下的无线资源管理跨层模型,阐述了模型的基本功能特征。以博弈论为依据,分析了无线网络资源的分配方式,并根据无线网络资源和系统协议栈中各层之间的联系,通过设计跨层结构,使各层博弈的目标统一。提出的理论模型面向多种无线网络资源,涉及多个无线网络协议栈层,实现了无线资源的综合管理以及各层之间的联合优化。     

CDMA蜂窝网中的无线资源管理

本文对CDMA蜂窝网络中的无线资源管理研究作综述。内容包括功率控制、接纳控制、越区切换和无线分调度等方面，并考虑了多种业务下的服务质量。     

第3代移动通信系统中的无线资源管理

文章对第3代移动通信系统中无线资源管理的关键技术进行了论述,包括接纳控制、无线分组调度和功率控制等方面内容.     

下一代通信网络中基于策略机制的无线资源管理

下一代无线通信系统是一种异构的网络体系,集成多种无线接入技术（Radio Access Technology,RAT）的同时提供多种窄带和宽带多媒体业务。这样的网络环境需要先进的RRM方法来处理复杂多变的无线信道、网络资源的动态配置及保障不同特征业务的服务质量（QoS）,给无线资源管理（Radio Resource Management,RRM）带来了巨大的技术挑战。本文通过引入对网络进行策略控制的思想,提出了一种基于策略机制的通用方法,致力于解决下一代异构（heterogeneous）网络中的无线资源管理。文中着重讨论了基于策略机制的网络接入控制、切换,以及基于策略机制的QoS管理,给出了各功能模块的工作原理和通信过程的分析与设计。     

Effective Radio Resource Management for MBMS in UMTS Networks

Broadcast and multicast offer a significant improvement of spectrum utilization, and becomes particularly important where information channels are shared among several users. Mobile cellular environments are expected to evolve with the technological approaches necessary to facilitate the deployment of multimedia services, such as streaming, file download and carousel services. The perspective that video streaming in wireless networks services is an attractive service to end-users has spurred the research in this area. To provide for a video delivery platform in UMTS, the Third Generation Partnership Project (3GPP) addressed this problem with the introduction of the Multimedia Broadcast and Multicast Services (MBMS) in 3GPP Release 6. In this document we analyse several effective radio resource management techniques to provide MBMS, namely, use of non-uniform QAM constellations, multi-code and macro-diversity to guarantee the optimal distribution of QoS depending on the location of mobiles.     

Uplink Low Power Based Radio Resource Management in Wireless Heterogeneous Networks

Wireless Personal Communications - Due to the rapid rise of energy consumption and limited battery power of wireless user equipment (UE), low power communication becomes very important....     

Radio Resource Management in MIMO-OFDM- Mesh Networks: Issues and Approaches

We present a survey on the radio resource management issues in MIMO-OFDM-based infrastructure wireless mesh networks. The major components in radio resource management (i.e., scheduling and admission control) and related research issues are discussed. We review related work in the literature. We propose a game-theoretic model for admission control in IEEE 802.11n-based WMNs using the MIMO-OFDM technology. The proposed scheme uses Q-learning, which is a reinforcement learning algorithm, to gain knowledge on system performance. Then this knowledge is used to determine payoff for the game formulation to obtain the Nash equilibrium for the decision on admitting or rejecting a new connection at a mesh router.     

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 dynami- cally 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 net- work selection, based on the above resource allocation and the pre-defined QoS require- ment, 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 im- prove the resource utilization.     

多小区OFDMA网络中用于有效无线资源分配的ICI管理技术(英文)

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-cel...     

Efficient Radio Resource Management in Integrated WLAN/CDMA Mobile Networks

The complementary characteristics of wireless local area networks (WLANs) and wideband code division multiple access (CDMA) cellular networks make it attractive to integrate these two technologies. How to utilize the overall radio resources optimally in this heterogeneous integrated environment is a challenging issue. This paper proposes an optimal joint session admission control scheme for multimedia traffic that maximizes overall network revenue with quality of service (QoS) constraints over both WLANs and CDMA cellular networks. WLANs operate under IEEE 802.11e medium access control (MAC) protocol, which supports QoS for multimedia traffic. A cross-layer optimization approach is used in CDMA networks taking into account both physical layer linear minimum mean square error (LMMSE) receivers and network layer QoS requirements. Numerical examples illustrate that the network revenue earned in the proposed joint admission control scheme is significantly more than that when the individual networks are optimized independently.     

Hybrid Radio Resource Management with Co-scheduling for Relay Extended OFDMA Networks

Wireless Personal Communications - In orthogonal frequency division multiple access networks buffer aided non-transparent in-band half duplex decode and forward relay nodes aim to improve coverage...     

Resource Allocation for OFDMA Based Cognitive Radio Networks with Arbitrarily Distributed Finite Power Inputs

The existing works on resource allocation for OFDMA based cognitive radio networks are based on the assumption of Gaussian inputs whereas in practical systems the inputs are taken from a set of finite symbol alphabets. This paper considers a system with arbitrarily distributed finite power inputs and solve the resource allocation problem by employing the relationship between mutual information and minimum mean-square error. To protect the primary users’ links, constraint on interference power of the secondary users (SUs) is imposed. In OFDMA based CR networks, a tone can be assigned to one SU at most (exclusivity constraint), due to which the resource allocation problem becomes combinatorial and its solution becomes prohibitively difficult.In this paper, first, the exclusivity constraint on tones allocation is relaxed, the problem is convexified and an optimal solution is derived that provides an upper bound on the system performance. Then, an integer tone allocation and optimal power allocation (ITA–OPA) algorithm is developed that guarantees the assignment of each tone to a single SU with close-to-optimal performance. Finally, keeping in view the complexity of the optimal solution and ITA–OPA algorithm, a low-complexity suboptimal algorithm is devised that accounts for exclusive tone assignment. Simulation results show that the suboptimal algorithm also achieves near-optimal performance. The proposed algorithms outperforms the algorithms that assume Gaussian inputs.     

Distributed Spectrum Sensing Using Radio Environment Maps in Cognitive Radio Networks

Wireless Personal Communications - Ever increasing development of wireless devices and wireless networks have increased the value of spectral space. Many efforts have been conducted to increase...     

OFDM认知无线电系统中分布式资源分配

针对多用户的OFDM认知无线电系统,提出了一种适合于混合业务的分布式资源分配新算法.该算法以最大化系统容量为目标,将资源分配问题建模为非凸优化问题,并通过拉格朗日对偶理论将原问题分解为若干个独立的子问题,通过对子问题的求解可以获得最优的子载波分配和功率分配.同时,根据认知用户业务分组中不同的业务类型授予其不同的权重因子,确保资源分配结果能够满足各认知用户的QoS.仿真结果表明,该算法不仅提高了系统容量,而且还保证了资源分配的公平性和用户的QoS,且算法复杂度不高.     

Fuzzy Neural Control for Economic-Driven Radio Resource Management in Beyond 3G Networks

Joint radio resource management (JRRM) is the envisaged process aimed at optimizing the radio resource usage of wireless systems to satisfy the requirements of both the network operators and the users in the context of future generation wireless networks. In particular, this paper proposes a two-layered JRRM framework to improve the efficiency of multiradio and multioperator cellular scenarios. On the one hand, the intraoperator JRRM relies on fuzzy neural mechanisms with economic-driven reinforcement learning techniques to exploit radio resources within a single-operator domain. Microeconomic concepts are included in the proposed approach so that user profile differentiation can be considered when making a JRRM decision. On the other hand, interoperator JRRM enables subscribers to obtain service through other operators, if the home operator network is blocked. Simulation results in a number of different scenarios show that interoperator agreements established in a cooperative scenario benefit both the operators and users, which enables efficient load management and increased operator revenue.      

On Time-Frequency Resource Leasing in Cognitive Radio Networks

In this work, we introduce a new spectrum leasing based cognitive radio for OFDM-based primary/secondary networks. More precisely, we propose a new leasing scheme both in time and frequency domains in a network composed of a primary transmission and some secondary (cognitive) users forming a cooperative relay network. In the proposed scheme, the primary user decides to lease a part of its available resources (time and frequency) to a selected set of relays, with the aim of increasing its link reliability. The selected relays use a part of the leased resources for relaying the primary signal, and in counterpart, they are allowed to exploit the rest of the frame for their own data transmission. By defining appropriate cost functions, the proposed algorithm decides whether it is of advantage for the primary user to cooperate with the relay network or not. Moreover, if cooperation is advantageous for the primary network, the algorithm selects the optimal amount of the time-frequency resources (number of OFDM symbols and subcarriers) that are involved in the cooperation process. Simulation results show that by using the proposed relaying scheme, both primary and secondary (relay) networks can take advantage in terms of achievable data rates compared to classical leasing systems.     

TD-SCDMA系统无线资源管理

随着移动通信的普及和规模的扩大，移动业务逐步走向多元化，需要在有限的无线资源的条件下，最大限度地提高无线资源利用率。通过动态信道分配（DCA）技术，TD—SCDMA系统资源分配的灵活性和高的频谱利用率可以得到充分体现。具体实施时DCA可以分为慢速DCA和快速DCA两类。慢速DCA可根据系统干扰受限的先验知识、负荷情况，对系统载频和时隙进行占用优先级划分，完成呼叫接入控制；快速DCA可根据对专用业务信道或共享业务信道通信质量监测的结果，自适应地对资源单元进行调配和切换，以保证业务质量。快速DCA中，基于可移动边界DCA方案与传统的固定边界DCA方案比较，能更好地利用资源，丢包率也较小。     

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。     

认知无线网络中一种基于匹配和干扰量化的LTE-A上行资源共享机制

认知无线网络中基于OFDMA的次系统(SS)与LTE-A主系统(PS)以重叠方式共享频谱的问题越来越受到学术界重视,该文关注上述场景中的资源分配和干扰避免问题。该问题的困难在于资源分配子问题中带耦合干扰的功率分配问题是NP-难的。为了满足研究场景提出的时延约束,该文将提出两阶段资源分配算法：子载波分配阶段的最大权匹配方法和功率分配阶段的干扰量化分配方法,简记为MQRA算法。理论分析和仿真结果表明,该文提出的MQRA算法能够很好地平衡性能和复杂性,并适用于LTE-A主系统下的频谱共享问题。     

Routing in Distributed Cognitive Radio Networks: A Survey

Cognitive Radio Networks (CRNs) have been receiving significant research attention recently due to their ability to solve issues associated with spectrum congestion and underutilization. In a CRN, unlicensed users (or Secondary Users, SUs) are able to exploit and use underutilized licensed channels, but they must evacuate the channels if any interference is caused to the licensed users (or Primary Users, PUs) who own the channels. Due to the dynamicity of spectrum availability in CRNs, design of protocols and schemes at different layers of the SU’s network stack has been challenging. In this article, we focus on routing and discuss the challenges and characteristics associated with it. Subsequently, we provide an extensive survey on existing routing schemes in CRNs. Generally speaking, there are three categories of challenges, namely channel-based, host-based, and network-based. The channel-based challenges are associated with the operating environment, the host-based with the SUs, and the network-based with the network-wide SUs. Furthermore, the existing routing schemes in the literature are segregated into three broad categories based on the relationship between PUs and SUs in their investigation, namely intra-system, inter-system, and hybrid-system; and within each category, they are further categorized based on their types, namely Proactive, Reactive, Hybrid, and Adaptive Per-hop. Additionally, we present performance enhancements achieved by the existing routing schemes in CRNs. Finally, we discuss various open issues related to routing in CRNs in order to establish a foundation and to spark new interests in this research area.