一种基于马尔可夫决策过程的认知无线电网络传输调度方案

该文提出了一种适用于认知无线电网络的跨层传输调度方案,即满足掉包率约束的前提下最小化平均功率消耗。此方案被建模为约束马尔可夫决策过程(MDP)。采用拉格朗日乘子法求解此MDP,并且提出了一种黄金分割乘子搜索法。提出两种简化方法,即状态聚合以及行动集缩减来解决维灾问题。仿真结果显示简化方法对该方案的性能影响很小,且该方案的平均功耗最低。     

比例公平算法在认知无线电中的研究

为了解决传统比例公平算法在认知无线电系统中没有考虑可用频段的时变性和用户的优先级的问题，结合认知无线电系统的实际情况以及频段稳定度的概念修改原有的比例公平调度算法，使其能够适合认知无线电系统资源调度。     

主用户干扰约束下的机会频谱接入感知−传输时隙优化调度

提出一种基于主用户干扰约束的机会频谱接入感知-传输时隙调度优化方案。首先,推导切换机制下认知系统的吞吐量和主用户干扰率,建立感知时间和感知周期联合优化模型;然后,在主用户干扰率和次用户感知质量双重约束下,推导了可最大化认知系统吞吐量的最优感知时间和感知周期的闭合表达式;最后,阐述了时隙优化调度方案并计算了认知系统可获得的最大吞吐量。仿真结果表明,所提出的时隙调度方案可以为认知系统提供更高的吞吐量,并更好地适应主用户干扰率和感知质量约束的变化。     

虚拟化云无线接入网络下基于在线学习的网络切片虚拟资源分配算法

针对现有研究中缺乏云无线接入网络(C-RAN)场景下对网络切片高效的动态资源分配方案的问题,该文提出一种虚拟化C-RAN网络下的网络切片虚拟资源分配算法。首先基于受限马尔可夫决策过程(CMDP)理论建立了一个虚拟化C-RAN场景下的随机优化模型,该模型以最大化平均切片和速率为目标,同时受限于各切片平均时延约束以及网络平均回传链路带宽消耗约束。其次,为了克服CMDP优化问题中难以准确掌握系统状态转移概率的问题,引入决策后状态(PDS)的概念,将其作为一种“中间状态”描述系统在已知动态发生后,但在未知动态发生前所处的状态,其包含了所有与系统状态转移有关的已知信息。最后,提出一种基于在线学习的网络切片虚拟资源分配算法,其在每个离散的资源调度时隙内会根据当前系统状态为每个网络切片分配合适的资源块数量以及缓存资源。仿真结果表明,该算法能有效地满足各切片的服务质量(QoS)需求,降低网络回传链路带宽消耗的压力并同时提升系统吞吐量。     

CR系统中基于微分博弈的功率控制算法

该文针对认知无线电系统动态性的特点,将微分博弈理论应用在认知无线电系统的功率控制中,建立了功率控制的非合作微分博弈模型,提出了一种基于微分博弈的分布式非合作功率控制算法。该算法在满足认知用户平均功率门限和QoS需求的基础上,实现了分布式动态功率控制,获得了反馈纳什均衡解析解。仿真结果表明,该算法可有效控制各认知用户的发射功率,增加系统吞吐量,提高系统性能。     

主用户延时约束下的认知无线电遍历容量研究

针对认知无线电系统中传统的功率限制约束无法保证主用户延时问题,本文提出了一种新的主用户有效容量约束模型,使认知无线电系统在满足认知用户共享频谱需求的同时,使主用户在延时约束下稳定传输。并基于该模型进一步推导了 Rayleigh 衰落环境下认知用户遍历容量下界性能。数值仿真结果显示了提出的约束模型能够保证主用户传输的同时提升认知用户的传输容量。     

认知无线电跨层传输的建模与仿真

将认知无线电(CR)中的跨层传输建模为约束马尔可夫决策过程(MDP),考虑了频谱可用性的变化规律、上层数据的到达过程和信道衰落,提出一种满足掉包率约束的前提下最小化平均功率消耗的方案。采用拉格朗日乘子法对此过程求解,并用2种简化的方法,即状态聚合和行动集缩来解决因状态空间、行动集规模过大引起的收敛速度慢的问题。计算机仿真结果表明,简化方法对该方案的性能影响很小,且该方案的平均功耗最低。     

基于OFDM的协同认知网络跨层资源调度

协同通信与认知无线电是未来移动通信的重要技术。针对基于OFDM的无线协同认知网络中的资源分配问题,该文提出了一种有效的跨层资源调度方案。该调度方案在考虑对主用户所受干扰功率进行控制的前提下,以最大化认知用户超帧中总的传输速率为目标,在调度帧中对各传输帧两阶段的子载波进行最佳配对,并为配对子载波分配最优的发送功率。通过分步求解的方法,该调度方案形成的优化问题得到有效解决。仿真结果表明该资源调度方案使得认知用户传输速率有显著提升,方案的可行性与有效性得到了验证。     

认知引擎中案例学习模块的设计与实现

学习能力是认知无线电区别于现有电台的最主要特征,研究基于SOAR架构的案例学习功能在已有认知引擎平台中的设计与实现。首先介绍了人工智能开发工具SOAR的基本原理与概念,进而在认知无线电原型系统平台上,设计并实现了基于SOAR架构的,具备案例学习能力的认知学习模块。具备案例学习能力的认知引擎使认知无线电系统具备从以往经验中获取知识的能力,提高了其在未来任务中的决策性能。     

认知无线电中一种基于OFDM技术的频谱资源控制方法研究

随着无线通信技术的迅速发展,频谱资源变得越来越紧张,如何充分利用频谱资源成为热点问题。认知无线电技术是解决这一问题的新方法,而OFDM(正交频分复用)技术灵活的选频方案为实现认知无线电系统提供了良好的平台。文章提出了一种基于OFDM的认知无线电系统,并从三个方面阐述了OFDM技术在认知无线电中是如何实现频谱资源控制的,研究表明OFDM技术进一步提高了认知无线电系统的频谱利用率。     

Capacity in fading environment based on soft sensing information under spectrum sharing constraints

In this paper, the ergodic channel capacity for a secondary user is investigated using soft sensing information about primary user activity in a shared channel under joint peak transmit power and average received interference power constraints for Nakagami-m fading channel. The results of the proposed power adaptation scheme illustrate the effect of communication environment parameters and soft sensing information about primary user activity on the channel capacity of secondary user. In particular, the effect of cross link channel state information to maximize the channel capacity for the power adaptation scheme is emphasized by considering the Lagrangian optimization problem for joint peak transmit power and average interference power constraints. Moreover, the performance of the primary user is also investigated considering the interference of the secondary user to the primary in spectrum sharing environment in terms of transmission rate and average channel capacity.     

基于用户体验质量和系统能耗的异构网络联合接入选择和功率分配策略

为了解决无线网络能耗和用户体验质量的问题,提出了一种应用于异构无线网络环境的基于多目标优化的联合接入选择和功率分配策略。该策略以最小化系统整体能耗和最大化用户平均体验质量为目标,建立了多目标优化联合分配模型,通过差分进化算法得到联合分配模型的最优解集,并结合 TOPSIS 的方法从最优解集中得到折中的联合分配方案。仿真结果表明,本文所提的策略能够有效地降低系统能耗,并提升用户整体的服务体验。     

联合迭代滤波与压扩参数优化的OFDM信号峰平比抑制

针对现有基于压扩变换处理的信号峰平比抑制方法性能单一且参数固定等缺陷,提出一种联合迭代滤波与自适应压扩参数优化的OFDM信号峰平比抑制方案。该方案能够同时对信号的峰平比PAPR和接收端误码率BER性能进行联合优化,并在迭代过程中有效消除因信号幅度畸变所引起的带外频谱再生;所提信号压扩及解压扩函数形式简单,计算复杂度较小;推导并给出了该方案可获得的PAPR抑制增益和BER理论性能界。仿真结果表明,该方案可同时获得较好的信号PAPR抑制、误码率以及带外功率谱性能,并在迭代过程中对压扩参数进行自适应调整,能够有效提高算法的适用灵活性。     

Energy efficiency in wireless cellular networks based on dynamic power allocation

Energy efficiency is increasingly vital for wireless cellular systems due to the limited battery resources of mobile clients. Among previous work, many studies suggest different methods to reduce the transmission power in case of a fixed condition. However, according to the mobility of users and continuous variation of cellular network environment, the traffic load of base station (BS) and the channel state information (CSI) are varying. In this paper, we proposed a dynamic power allocation schedule to assign transmit power to mobile users in the downlink, resulting in optimal energy saving. The novel power allocation scheme was based on the coordination of neighbouring cells. The results showed that the scheme dramatically reduce the average bit error rate (BER) and total tranmitted power of the system, with the improvement of network capacity.     

Rate and Power Optimization Under Received-Power Constraints for Opportunistic Spectrum-Sharing Communication

In this paper, the channel capacity of secondary user is investigated for opportunistic spectrum sharing with primary user in a Rayleigh fading environment. In the proposed communication scenario, on finding transmission opportunities in licensed band, secondary user utilizes the band as long as the interference power inflicted on primary receiver is below the predefined threshold, and adjusts its transmission power and data rate based on the sensing information available from spectrum sensor. In this context, two different adaptation schemes namely adaptive transmission power scheme and adaptive rate and transmission power scheme are investigated under joint peak and average received power constraints at primary receiver for multilevel quadrature amplitude modulation format. The closed form expressions are derived for the ergodic channel capacities of these schemes and numerical results are presented to validate the theoretical results. Moreover, a comparison between channel capacities is given to illustrate the benefit of using soft sensing information under said constraints.

     

Investigation on outage capacity of spectrum sharing system using CSI and SSI under received power constraints

In this paper, we have investigated the outage capacity of secondary user for opportunistic spectrum sharing under the joint peak and average received power constraints for Rayleigh fading environment. Under this communication scenario, on detecting the licensed primary user inactive, the secondary unlicensed users transmit data/information in the licensed frequency band such that no or minimum interference may be experienced by the primary user. The soft sensing information (SSI) and secondary user’s channel state information is used to obtain the closed form expressions for the ergodic and outage capacity using truncated channel inversion with fixed rate technique under the joint peak and average received power constraints. Numerically simulated results are provided to demonstrate the improvement in outage capacity of secondary user under the proposed spectrum sharing scheme. Moreover, the proposed scheme is also compared with other conventional spectrum sharing schemes to illustrate the benefits of SSI and received power constraints on the outage capacity of secondary user.

     

Performance improvements of HCCA scheduling in V2R environments

This paper addresses the issue of real‐time data transmission in vehicles to roadside environment by the hybrid coordination function controlled channel access (HCCA) scheme with Institute of Electrical and Electronics Engineers 802.11p protocol. The HCCA is one of the medium access protocols specified in 802.11p standard, which uses a polling scheme similar to the point coordination function to provide a reliable QoS. In this paper, we improve the HCCA polling scheme and design a new data transmission scheduling method. We also prepared a mathematical model to systematically evaluate the performance of the HCCA in terms of average delay. Moreover, we analyze the factors that could impact the average delay, throughput, and packet loss rate as well. The simulation results are compared with the original scheme specified in the standard. The simulation results demonstrate that the proposed delay model could estimate the average delay of the HCCA with a high precision, whereas the proposal of the enhancement of the HCCA has lower delay, lower loss rate, and higher throughput than the one specified in the standard. Copyright © 2013 John Wiley & Sons, Ltd.     

Neighbors’ interference situation-aware power control scheme for dense 5G mobile communication system

The next generation mobile communication (5G) systems is targeting very high data rate by deploying more number of small cells, but this deployment results in high cross-tier interference because of using the same frequency band. To solve this challenge, an efficient power control scheme is desired specially for the case of uplink scenario. Thus, to solve this challenge, we propose the neighbors’ interference situation-aware uplink power control (IA-ULPC) scheme to reduce the cross-tier interference. In this scheme, we consider the interference situation of the neighbor cells while controlling the power of the users. Moreover, we also derive the target signal-to-interference and noise-ratio (\(P_0\)) equation to dynamically adjust it based on the neighbors’ base station interference situation. We compare the performance of the proposed IA-ULPC with the conventional fractional power control scheme (C-FPC). The extensive system-level simulations are carried out to prove the validity of the proposed IA-ULPC scheme which almost doubles the user average throughput and also decreases the interference around 20% in dense two-tier heterogeneous network environment as compared to C-FPC.     

一种基于无线电环境地图的路由优化机制

设计认知无线网络路由算法时,需要兼顾主用户保护与路由性能两个方面。为了提高认知无线网络中次用户之间路由的端到端性能,提出了基于无线电环境地图的路由优化机制,该机制中无线电环境地图能够为次用户提供主用户保护有关的无线电环境数据。首先,无线电环境地图根据次用户的数据请求将各授权频段的可用概率与功率控制相关信息反馈到该次用户;其次,次用户可以计算出与上一跳次用户之间的链路稳定性以及传输时延;最后,目的次用户通过计算每条路由的端到端吞吐量的期望值,然后选取期望值最大的一条路由。仿真结果表明,该路由机制在平均分组投递率、平均端到端吞吐量、平均端到端时延方面均优于对比路由算法。     

Co‐tier downlink interference management in dense femtocell networks

With the adoption of long‐term evolution standard for 4G mobile communications, the deployment of femtocell base stations (FBSs) to cope with the surging traffic in mobile wireless communication is becoming increasingly popular. However, with the random installation of FBSs, the problem of interference among FBSs is still a challenge. In this paper, assuming the presence of a femtocell management system that can control and coordinate the densely deployed FBSs, a novel power backoff scheme is proposed that determines the appropriate transmit power of each FBS so that the interference is reduced. Simulation results for randomly deployed FBSs in an environment with shadowing using MATLAB are provided, showing that our proposed methods can effectively mitigate the co‐tier downlink interference while improving the system capacity in a densely deployed femtocell network with shared spectrum use. Quantitatively, the average interference is reduced by roughly 90% to 100% of dBm, and the average capacity is increased by more than 80%. These results attest to the effectiveness of the proposed scheme.