认知异构蜂窝网络中改进蜉蝣算法的资源分配策略

针对认知异构蜂窝网络中上行链路资源分配的优化问题,提出认知异构蜂窝网络中改进离散蜉蝣算法的资源分配算法。认知异构蜂窝网络模型中,考虑用户层间干扰和带外干扰引入功率控制策略控制发射功率来干扰抑制,基于用户服务质量（QoS）需求和干扰阈值约束,最大化能量效率为优化目标,利用改进离散蜉蝣算法优化求解得出最优分配方案。引入不完全Gamma和Beta分布函数的动态自适应权重、黄金正弦位置更新策略,提升蜉蝣算法的收敛速度和搜索能力。仿真实验表明,基于接收SINR的闭环功率控制动态调整用户端的发射功率,能有效抑制用户间的干扰,GSWBMA求解资源分配问题具有良好的寻优效率和收敛性能,有效提升系统能量效率和用户传输速率,保证用户QoS需求。     

分层异构网络中基于斯坦克尔伯格博弈的资源分配算法

分层异构网络中家庭基站与宏基站之间往往存在干扰,如何分配资源以获得高谱率和高容量、保证用户性能一直是研究的重点。为了解决这个问题,本文提出了一种异构蜂窝网络中基于斯坦克尔伯格博弈的家庭基站与宏基站联合资源分配算法,算法首先基于图论的分簇算法对家庭基站和宏用户进行分簇和信道分配,以减少家庭基站之间的同层干扰和家庭基站层与宏蜂窝网络的跨层干扰;然后建立了联合家庭基站发射功率以及宏用户接入选择的斯坦克尔伯格博弈,推导出达到纳什均衡时的家庭基站发射功率的表达式,并据此为宏用户选择合适的接入策略。仿真结果表明,该算法能够有效地提高宏用户的信干噪比（SINR）,家庭用户的性能也得到改善。      

基于改进图着色的D2D资源分配和功率控制

针对蜂窝网络中D2D（Device-to-Device）用户复用蜂窝信道带来的同频干扰问题,提出了一种基于改进图着色的资源分配和功率控制算法。首先通过构建干扰图和候选集进行用户之间干扰关系建模,并定义指数型累积因子改进图着色算法,为D2D用户分配蜂窝信道;再采用基于信干噪比的闭环功率控制算法动态调整D2D用户发射功率,减小由于信道复用产生的干扰。仿真结果表明,与现有算法相比,所提算法能够有效提升系统吞吐量和D2D用户接入率,实现信道资源的合理分配。     

基于硬件损伤的异构网络鲁棒安全资源分配算法

针对多蜂窝多用户异构网络中收发机处信号畸变、用户信息泄露和传输中断等问题,该文提出一种基于硬件损伤的异构网络鲁棒安全资源分配算法。考虑小蜂窝用户最小安全速率约束、小蜂窝基站最大发射功率约束和宏用户干扰功率约束,建立了基于有界信道不确定性的能效最大化资源分配模型。基于Dinkelbach法、最坏准则法和连续凸近似理论,将原非凸资源分配问题等价转换为凸优化问题,并利用拉格朗日对偶算法得到解析解。仿真结果表明,与现有算法相比,所提算法具有较好的能效和鲁棒性。     

一种基于OFDM的多用户认知无线电系统联合资源分配算法

针对频谱共享环境,研究了采用OFDM调制方式的多用户认知无线电系统中,综合考虑自身发射功率约束与主用户干扰功率约束的资源分配问题.基于最大化认知用户和速率的优化目标,给出了连续比特条件下最优的多水位注水功率分配表达式;针对更实际的整数比特要求情况,通过基于相对增益因子RG的子信道选择机制与每个认知用户内多约束的贪婪比特与功率分配策略,来最大限度地提高频谱利用率.仿真结果表明:联合的子信道、功率与比特分配算法在不同的参数设置下均达到了良好的性能,在不影响主用户通信的前提下有效地提高了认知系统的频谱利用率.     

基于Message Passing的认知无线电快速资源分配

针对多用户的OFDM认知无线电系统上行链路,提出一种基于Message Passing的分布式快速资源分配算法。该算法以认知系统总发射功率最小化为优化目标,综合考虑了认知用户对授权用户的干扰、总发射功率预算以及认知用户之间的比例公平性等约束条件,将资源分配分为子信道分配与功率分配相继2个步骤,构建资源分配的因子图,通过在节点间迭代地传递信息直至最终完成分布式的资源分配。分析和仿真结果表明,该算法在保证系统通信性能及资源分配公平性的前提下降低了系统总发射功率,并且运算效率得到了明显提升。     

异构蜂窝网络中基于能效的非正交多址接入下行功率分配算法

该文针对应用非正交多址接入(NOMA)技术的异构蜂窝网络,在考虑层间层内干扰的情况下,提出一种能效最大化的功率分配算法。该算法主要包括两部分,一部分为子信道内用户功率分配因子的求解,主要利用差分优化的方法,迭代求解。另一部分为子信道间的功率分配,主要利用凹凸程序法将原有的非凸问题简化为可解的凸问题,最后利用拉格朗日求解法得出功率最优解。仿真结果表明该算法有良好的迭代性,且新算法表明利用NOMA技术得到的系统能效较利用正交技术得到的系统能效提高了至少44%以上。     

基于能效的NOMA蜂窝车联网动态资源分配算法

在支持车与车直接通信(V2V)的非正交多址接入(NOMA)蜂窝网络场景下,针对V2V用户与蜂窝用户的干扰以及NOMA准则下的功率分配问题,该文提出一种基于能效的动态资源分配算法。该算法首先为了保证V2V用户的时延及可靠性同时满足蜂窝用户的速率需求,联合考虑子信道调度、功率分配和拥塞控制,建立了最大化系统能效的随机优化模型。其次,利用李雅普诺夫随机优化方法,通过控制可接入数据量保证队列稳定性以避免网络拥塞,并根据实时网络负载状态动态地进行资源调度,设计一种次优化子信道匹配算法获得用户调度方案,进一步,利用凸优化理论和拉格朗日对偶分解方法得到功率分配策略。最后,仿真结果表明,该文算法可以满足不同用户的服务质量(QoS)需求,并在保证网络稳定性前提下提高系统能效。     

基于能量采集异构蜂窝网络的功率分配算法研究

针对能量采集异构蜂窝网络,由于能量到达和信道状态的随机性导致离线功率分配算法只能取得理论最优,本文提出了一种在线功率分配算法.算法在每个时隙开始时,基站控制器通过能量判别选出满足开启条件的小蜂窝基站,然后采用基于拉格朗日乘子的两层迭代算法对所选择的小蜂窝基站分配发射功率,能够实际最大化系统在每个时隙的能效.仿真表明在满足基站开启条件的情况下,所提算法可以为密集异构网络提供更高的能量效率.该算法适用于信道状态和能量状态不可预测的网络.     

面向用户体验的多小区混合非正交多址接入网络资源分配方法

该文研究了多小区混合非正交多址接入(MC-hybrid NOMA)网络的资源分配。为满足异构用户的服务体验,以最大化全网综合平均意见评分(MOS)累加和为目标,考虑基站选择、信道接入和功率资源分配的联合优化问题,该文提出一种用户、基站和信道3方的2阶段转移匹配算法,并根据用户MOS进行子信道功率优化。仿真结果表明所提多小区混合NOMA网络资源分配方案能有效提升全网用户服务体验和公平性。     

一种femto-macro异构网络多业务资源公平管理算法

摘要：针对毫微微蜂窝（femtocell）网络中多种业务（固定速率业务和可变速率业务）环境下如何公平分配毫微微蜂窝基站（femtocell base station, FBS）资源的问题,提出了一种基于比例公平算法的femto-macro异构网络资源分配算法。该算法以基于比例公平法则的可变速率用户的吞吐量为优化目标,并以每个用户的服务质量（quality of service, QoS）、FBS的下行传输总功率和宏蜂窝（macrocell）用户的跨层同频干扰门限值为约束组成优化问题。在上述资源分配最优化问题为凸优化问题的基础上,采用对偶分解算法进行求解。仿真结果表明,提出的算法在保证不同用户 QoS 的同时,不仅能够有效地公平分配资源给可变速率用户,而且降低了macrocell用户受到来自FBS的跨层同频干扰。     

Pseudo-handover based subchannel and power adaptation scheme for interference mitigation in OFDMA two-tier femtocell networks

In the two-tier femtocell network,a central macrocell is underlaid with a large number of shorter range femtocell hotspots,which is preferably in the universal frequency reuse mode.This kind of new network architecture brings about urgent challenges to the schemes of interference management and the radio resource allocation.Motivated by these challenges,three contributions are made in this paper:1) A novel joint subchannel and power allocation problem for orthogonal frequency division multiple access (OFDMA) downlink based femtocells is formulated on the premise ofminimizing radiated interference of every Femto base station.2) The pseudo-handover based scheduling information exchange method is proposed to exchange the co-tier and cross-tier information,and thus avoid the collision interference.3) An iterative scheme of power control and subchannel is proposed to solve the formulated problem in contribution 1),which is an NP-complete problem.Through simulations and comparisons with four other schemes,better performance in reducing interference and improving the spectrum efficiency is achieved by the proposed scheme.     

A preset threshold based cross-tier handover algorithm for uplink co-channel interference mitigation in two-tier femtocell networks

This paper considers the co-channel interference mitigation problem and proposes a preset threshold based cross-tier handover algorithm for uplink co-channel interference mitigation in two-tier femtocell networks. The proposed cross-tier handover algorithm introduces a preset threshold cross-tier handover policy, which takes into account both the time-to-stay (TTS) of a macrocell user equipment (MUE)/femtocell user equipment (FUE) in a femtocell/the macrocell, and the received signal to interference plus noise ratio (SINR) at a femtocell access point (FAP)/the macrocell base station (MBS) in making a cross-tier handover decision for an MUE/FUE. A cross-tier handover decision is made by comparing the TTS of an MUE/FUE in a femtocells/the macrocell and the SINR at a FAP/the MBS with a preset TTS threshold and different SINR thresholds. The objective of the preset threshold based cross-tier handover algorithm is to increase the received SINR at the MBS/FAPs and thus improve the network performance. The performance of the proposed cross-tier handover algorithm with the minimum power transmission and the optimal power transmission is analyzed, respectively. Numerical results show that the proposed preset threshold based cross-tier handover algorithm can significantly improve the network performance in terms of the outage probability, user sum rate, and network capacity.     

Distributed Resource Allocation for Femtocell Networks: Regret Learning with Proportional Self-belief

Femtocell networks promise improvement in network quality and performance for dense wireless networks, but will suffer from inter-cell interference if resource management is not properly employed. This paper presents distributed joint resource allocation (sub-channel and power) to address co- and cross-tier interference issues in two-tier heterogeneous femtocell networks. Due to uncoordinated nature of femtocell base stations (HeNB) deployment, the interactions among self-interested HeNBs are formulated using game-theoretical tools. Then, we designed individual utility function for every HeNB in order to enforce cooperative behaviour among HeNBs as well as to avoid cross-tier interference towards macrocell user equipments within HeNB coverage. Based on the designed utility function, we propose a fully distributed adaptive learning algorithm with a proportional self-belief concept that can lead to correlated equilibrium with fast and decisive convergence. Finally, performance analysis on the proposed algorithm done in simulated environment showed positive results indicating improvements in terms of co- and cross-tier interference mitigation as compared to generic regret-based learning scheme and utility functions.     

双层无线异构网络下行干扰抑制方法研究

针对引入家庭基站技术的双层无线异构网络中存在严重的跨层和同层干扰的问题,提出了一种基于伪随机子信道选择的干扰抑制方案。该方案首先通过干扰随机化抑制跨层干扰,然后利用干扰图计算最大可选择伪随机序列个数抑制同层干扰。通过对比传统干扰抑制方案,验证了该方案能更有效地抑制系统干扰,提高系统吞吐量。     

Outage performance of downlink communications in cognitive-based two-tier networks: cooperative and non-cooperative femtocells

Femtocell deployment, which is a promising approach to the coverage and capacity improvement of indoor communications, suffers from cross-tier interference. Therefore to make the femtocell technology practical this issue needs to be addressed appropriately. One serious type of cross-tier interference occurs in downlink communication, in which a macrocell user is located far from its macro base station. In this setup, the communication of the adjacent femto access points with their users makes the macrocell user experience a low SINR. This paper considers this scenario and shows how cognitive-enabled femto access points can cope with cross-tier interference. More precisely, we compute the outage probability of macro users in a two-tier network when femto access points use the energy detection-based spectrum sensing technique to find the unoccupied frequency subband. To improve the outage probability of macro users, we also study the effectiveness of cooperation among neighbor femto access points. In all cases, the analytical expressions are validated by computer simulations which confirm the accuracy of the used approximations.

     

Analysis of subchannel reusable probability and capacity for frequency-reused femtocell networks under frequency partitioning strategy

Femtocell is a promising technology to improve network performance with low-power and cost-beneficial small base stations.However,the interference-limited reality in femtocell networks makes interference and resource management the key to achieving the benefits of femtocell networks.In this paper,the following contributions are made step by step:first,on the basis of the interference temperature model (ITM) in cognitive radio (CR) technique and the network architecture of the third generation partnership project (3GPP) long term evolution advanced (LTE-A),the problem model of optimizing the capacity of the femtocell-reused subchannel is established under the frequency partitioning strategy,jointly considering the average interference constraint and the instantaneous interference constraint.Second,utilizing the convex theory,optimal power allocation of the femtocell-reused subchannel is derived.Third,under Rayleigh fading channel,closed-form expressions of the subchannel reusable probability and capacity are derived.At last,numerical results are conducted to confirming our analytical results,which could provide theoretical guidance for frequency resource allocation of femtocell network deployments.     

Handling interference in self-organizing femtocell networks through frequency-polarization diversity

The next generation heterogeneous networks are expected to offer higher data-rate and better QoS to the customers by leveraging smaller cells like femtocells and making use of orthogonal frequency division multiple access. However, uncoordinated dense deployment of femtocells in macrocell network pose unique challenges involving cross-tier interference and resource management which results in significant degradation of the system performance. As part of addressing these challenges for the successful integration of both technologies, this paper proposes the deployment of a self-organizing femtocell network that employs an opportunistic smart frequency reuse technique –cross polarized complementary frequency allocation (CPCFA). It exploits the frequency and polarization diversity to mitigate interference in two-tier femto-macro networks. In this work, a strategy combining the adoption of reverse frequency allocation and orthogonal polarized transmission is analyzed as a potential solution for maximizing spectral efficiency and minimizing interference in the existing heterogeneous networks. Focus of the current work is on downlink transmission where the traffic is high and the deployment of femtocell is more beneficial. The results of analytic and simulation studies prove that CPCFA increases the scope for an easily implementable, remarkable opportunity in the context of two-tier femto-macro network that can substantially increase the system capacity as well as cell coverage without additional network complexities.     

Stackelberg game for backhaul resource allocation in the two-tier LTE femtocell networks

As one promising technology for indoor coverage and service offloading from the conventional cellular networks, femtocells have attracted considerable attention in recent years. However, most of previous work are focused on resource allocation during the access period, and the backhaul involved resource allocation is seriously ignored. The authors studied the backhaul resource allocation in the wireless backhaul based two-tier heterogeneous networks （HetNets）, in which cross-tier interference control during access period is jointly considered. Assuming that the macrocell base station （MBS） protects itself from interference by pricing the backhaul spectrum allocated to femtocells, a Stackelberg game is formulated to work on the joint utility maximization of the macrocell and femtocells subject to a maximum interference tolerance at the MBS. The closed-form expressions of the optimal strategies are obtained to characterize the Stackelberg equilibriums for the proposed games, and a backhaul spectrum payment selection algorithm with guaranteed convergence is proposed to implement the backhaul resource allocation for femtocell base stations （FBSs）. Simulations are presented to demonstrate the Stackelberg equilibrium （SE） is obtained by the proposed algorithm and the proposed scheme is effective in backhaul resource allocation and macrocell protection in the spectrum-sharing HetNets.