Improving densely deployed wireless network performance in unlicensed spectrum through hidden-node aware channel assignment

It is well known that a wireless local area network (WLAN) based on the IEEE 802.11 standard suffers from interference and scalability problems due to the limited number of non-overlapping channels. In order to mitigate the interference problem, channel assignment algorithms has been a popular research topic in recent years. It has been shown that such algorithms can greatly reduce the interference among wireless access points. However, in this paper, we show that previously proposed channel assignment algorithms may lead to an increased number of hidden nodes in dense network deployments. We also show that this can significantly decrease the performance of the network. Furthermore, we present results from experiments showing that the Request to send (RTS)/Clear to send (CTS) mechanism is unable to solve the hidden node problem in infrastructure WLANs, and therefore careful consideration needs to be taken when choosing channel assignment strategies in densely deployed wireless networks. To this end, we propose both a centralized channel assignment algorithm and a distributed channel assignment algorithm. Using a simulation study, we show that the proposed algorithms can outperform traditional channel assignment in densely deployed scenarios, in terms of QoS sensitive VoIP support without compromising the aggregate throughput, and that they are therefore a better performing alternative in such settings.     

A hybrid channel assignment strategy to QoS support of video-streaming over multi-channel ad hoc networks

Currently multi-channel multi-interface ad hoc networks (multi-channel ad hoc networks) have received amount of interest, especially under the context of real-time traffics, such as video applications. Channel assignment is one of the key challenges in multi-channel ad hoc networks. In this paper, based on a representative hybrid channel assignment strategy named as HMCP, a statistic link load based hybrid channel assignment strategy, SLL-HCA, is presented to obtain a better channel assignment metric than that in HMCP. SLL-HCA is based on the HMCP protocol and adopts the statistic link load metric to ensure load balancing in a two-hop neighborhood, and to prevent both the hidden node problem and the exposed node problem. In addition, an enhanced strategy, VE-SLL-HCA, by setting harsher channel assignment conditions and reserving lower interference of routing path for video-streaming traffic than other non-video traffic, is proposed to improve the QoS support of video-streaming over multi-channel ad hoc networks. Simulation results show that SLL-HCA achieves better throughput performance than HMCP in the presence of background traffic including CBR traffic or VBR traffic; and, the PSNR QoS metric for video-streaming is enhanced when using VE-SLL-HCA compared with SLL-HCA and HMCP, which confirms the validity of the proposed strategy for video-streaming traffics. Moreover, the simulation results also indicate that non-video traffic unlikely suffers an unacceptable performance in terms of throughput.     

A topology control approach for utilizing multiple channels in multi-radio wireless mesh networks

We consider the channel assignment problem in a multi-radio wireless mesh network that involves assigning channels to radio interfaces for achieving efficient channel utilization. We present a graph–theoretic formulation of the channel assignment guided by a novel topology control perspective, and show that the resulting optimization problem is NP-complete. We also present an ILP formulation that is used for obtaining a lower bound for the optimum. We then develop a new greedy heuristic channel assignment algorithm (termed CLICA) for finding connected, low interference topologies by utilizing multiple channels. Our evaluations show that the proposed CLICA algorithm exhibits similar behavior and comparable performance relative to the optimum bound with respect to interference and capacity measures. Moreover, our extensive simulation studies show that it can provide a large reduction in interference even with a small number of radios per node, which in turn leads to significant gains in both link layer and multihop performance in 802.11-based multi-radio mesh networks.     

Channel assignment in heterogeneous multi-radio multi-channel wireless networks: A game theoretic approach

Channel assignment is a challenging issue for multi-radio multi-channel wireless networks, especially in a competing environment. This paper investigates channel assignment for selfish nodes in a heterogeneous scenario, in which nodes may have different QoS requirements and thus compete for different channels with unequal bandwidth. The interaction among nodes is formulated as a non-cooperative Multi-radio Channel Assignment Game (MCAG), where Nash Equilibrium (NE) corresponds to a stable channel assignment outcome from which no individual node has the incentive to deviate. The NEs in MCAG are characterized in this paper. Since multiple NEs may exist in this game, it is natural to choose the NE that maximizes the network utility, i.e., the sum of node utilities. It is shown that the optimal NE outcome can be derived by solving an integer non-linear programming problem. Based on some observations on the radio number distribution of NE, we propose a two-stage optimization algorithm to achieve an optimal channel assignment. Finally, computer simulations validate the effectiveness of the proposed algorithm.     

LTE中femtocell的联合信道与功率控制算法

随着LTE中家庭基站的密集部署,会使家庭基站间产生严重的同层干扰,与此同时也会对边缘宏用户产生严重的跨层干扰。针对这两种下行干扰,提出了一种基于图论的信道分配和基于路损的功率控制算法相结合的方案。首先基于图论的知识构建干扰图,通过干扰图进行信道分配,有干扰的小区采用相互正交的信道,降低家庭小区间的同层干扰。然后在保证宏用户和家庭用户QoS的条件下,根据设定的信干噪比(SINR)门限值,设置femtocell干扰标志,并根据信道质量(CQI)设置干扰级别,通过干扰级别进行对应的功率控制,最终达到消除家庭小区对宏用户跨层干扰的目的。仿真结果表明,该算法很好的提高了用户的SINR和吞吐量,同时保证了家庭用户和宏用户的QoS。     

多信道无线Mesh网络信道分配算法

针对无线Mesh网络的带宽容量问题,文章通过使用无线网络干扰协议模型对无线链路的干扰进行量化,利用整数线性规划公式对信道分配问题进行描述,在信道分配的时候,应用目标函数对无线链路的信道分配进行优化,使网络总的干扰权重最小化,在此基础上提出一个信道分配的启发式算法。仿真结果表明,文章提出的算法能提高网络的吞吐量。     

基于任务调度的无线网贪婪信道分配算法

针对无线网络链路干扰问题,综合借鉴多处理器任务调度算法提出了一种贪婪信道分配算法,为所访问的无线网链路甄选出干扰最小的信道,并且证明了本算法的近似比率为2-1/k,其中为k为可用的正交信道数,算法复杂度为O（|E|2）。为了验证本文算法的可行性和有效性,将本文所提出的贪婪算法与随机信道分配算法和按序信道分配算法进行了实验对比。仿真结果表明：本文所提出的贪婪算法的整体性能优于其他两种算法,并且贪婪算法得到的最大干扰和平均干扰归一化值随着可用正交信道数的变化趋势较其他两种算法稳定。从而验证了本文算法能有效的降低链路干扰,一定程度上可以提升网络吞吐量。     

On-line joint QoS routing and channel assignment in multi-channel multi-radio wireless mesh networks

We study the problem of on-line joint QoS routing and channel assignment for performance optimization in multi-channel multi-radio wireless mesh networks, which is a fundamental issue in supporting quality of service for emerging multimedia applications. To our best knowledge, this is the first time that the problem is addressed. Our proposed solution is composed of a routing algorithm that finds up to k but not necessarily feasible paths for each demand and an on-demand channel (re)assignment algorithm that adapts network resources to maintain feasibility of one of the paths. We also study the problem of obtaining an upper bound on the network performance. First, we consider an artificial version of the problem, in which all demands arrive at the same time, and formulate it as a mixed integer linear programming model. To tackle the complexity of the model, it is relaxed that provides a tight upper bound while improves solution time up to 3.0e+5 times. Then, we model the original problem by extending the relaxed model to consider dynamic demands, it leads to a huge model; thus, we develop another model, which is equivalent to the first one and is decomposable. It is broken down by a decomposition algorithm into subproblems, which are solved sequentially. Our extensive simulations show that the proposed solution has comparable performance to the bound obtained from the decomposition algorithm; it efficiently exploits available channels, and needs very few radios per node to achieve high network performance.     

A uplink radio resource allocation scheme for localized SC-FDMA transmission in LTE network

The radio resource allocation is one of the most important issues to achieve effective wireless communication. In Long Term Evolution (LTE) network, single carrier frequency division multiple access (SC-FDMA) is applied as the transmission technology for uplink traffic. Most researches focus on maximizing the system throughput of SC-FDMA under changeable channel condition. However, users may require different quality of services (QoS) for different applications. This paper studies radio resource allocation for QoS users in localized SC-FDMA system. The proposed scheme divides allocation process into matching algorithm and radio resource assignment algorithm. The Gale–Shapley algorithm is applied to find the optimal matching between resource blocks (RB) and user equipment (UE) by considering channel conditions and the desired QoS. Then the resource assignment algorithm heuristically allocates bandwidth to UE by referring the matched RB under the constraint of carrier continuity. This paper modified the Recursive Maximum Expansion (RME) algorithm to effectively assign radio resource for UEs with different bandwidth demands. The performance of our proposed scheme is compared with the modified RME scheme through exhaustive simulations. The video streaming, VoIP, and FTP traffic types were adopted for simulations. Our simulation results show that the proposed scheme achieves better QoS satisfaction and system throughput than the RME-modified scheme.     

ICRN功率分配与中继选择联合优化

针对工业认知无线电网络中出现的无线干扰和冲突严重,特别是工业现场的金属环境和移动特性造成多径与阴影衰落,从而使得传输可靠性难以保证的问题,引入感知信道概率及信道可用度概念,提出一种联合优化中继选择与功率分配的算法。该算法给出3种认知中继选择方案,分别是信道增益最大准则、最近准则及调和平均准则,并在源节点和所选中继节点之间进行最优功率分配,以最小化网络中断概率。仿真结果表明,与平均功率分配算法相比,所提算法能更好地降低系统中断概率,提高传输可靠性。     

基于最优连通功率控制的WSNs跨层路由优化算法

针对非连通区域节点空洞效应和热点区域节点间通信干扰导致的路由服务质量（QoS）下降问题,提出了一种基于最优连通功率控制的无线传感器网络（WSNs）跨层路由优化算法。算法采用自适应最优连通功率控制策略,在避免路由空洞产生和保证网络连通性条件下,降低热点区域节点数据转发竞争干扰;通过位置信息、剩余能量和干扰等级的跨层信息交互,动态选取最优转发节点,提高网络整体性能。仿真实验表明：算法能够提高路由（QoS）、优化网络生命周期和降低热点区域通信干扰。     

基于DQN的超密集网络能效资源管理

小基站的密集随机部署会产生严重干扰和较高能耗问题,为降低网络干扰、保证用户网络服务质量（QoS）并提高网络能效,构建一种基于深度强化学习（DRL）的资源分配和功率控制联合优化框架。综合考虑超密集异构网络中的同层干扰和跨层干扰,提出对频谱与功率资源联合控制能效以及用户QoS的联合优化问题。针对该联合优化问题的NP-Hard特性,提出基于DRL框架的资源分配和功率控制联合优化算法,并定义联合频谱和功率分配的状态、动作以及回报函数。利用强化学习、在线学习和深度神经网络线下训练对网络资源进行控制,从而找到最佳资源和功率控制策略。仿真结果表明,与枚举算法、Q-学习算法和两阶段算法相比,该算法可在保证用户QoS的同时有效提升网络能效。     

Price-based interference avoidance game in the Gaussian interference channel

This paper considers a distributed interference avoidance problem employing frequency assignment in the Gaussian interference channel(IC).We divide the common channel into several sub-channels and each user chooses one sub-channel for transmission in such a way that the total interference in the IC is minimum.This mechanism named interference avoidance in this paper can be modeled as a competitive game model.And a completely autonomous distributed iterative algorithm called distributed interference avoidance algorithm(DIA)is adopted to achieve the Nash equilibrium(NE)of the game.Due to the self-optimum,the DIA is a sub-optimal algorithm.Therefore,through introducing an optimal compensation(or price)into the competitive game model,we successfully develop a compensation-based game model to approximate the optimal interference avoidance problem.Moreover,an optimal algorithm called iterative optimal interference avoidance algorithm(IOIA)is proposed to reach the optimality of the interference avoidance scheme.We analyze the implementation complexity of the proposed algorithm which is only O(N),with N standing for the number of users in the IC.We also give the proof on the convergence of the proposed algorithm.The performance upper bound and lower bound are derived for the IOIA algorithm.The simulation results show that the IOIA does reach the optimality under the condition of interference avoidance mechanism.     

On the end-to-end flow allocation and channel assignment in multi-channel multi-radio wireless mesh networks with partially overlapped channels

The performance of wireless mesh networks (WMNs) can be improved significantly with the increase in number of channels and radios. Despite the availability of multiple channels in several of the current wireless standards, only a small fraction of them are non-overlapping and many channels are partially overlapped. In this paper, we formulate the joint channel assignment and flow allocation problem for multi-channel multi-radio WMNs as a Mixed Integer Linear Program (MILP). Unlike most of the previous studies, we consider the case when both non-overlapped and partially overlapped channels are being used. We consider an objective of maximizing aggregate end-to-end throughput and minimizing queueing delay in the network, instead of the sum of link capacities, since the traffic characteristics of a multi-hop WMN are quite different from a single hop wireless network. Our static channel assignment algorithm incorporates network traffic information, i.e., it is load aware. Our formulation takes into consideration several important network parameters such as the transmission power of each node, path loss information, the signal to interference plus noise ratio at a node, and the frequency response of the filters used in the transmitter and receiver. We show by simulations that our MILP formulation makes efficient use of the spectrum, by providing superior channel assignments and flow allocations with the addition of partially overlapped channels, without the use of any additional spectrum. We also justify the need to consider alternative objective functions such as, minimizing average queueing in the network. We also propose a polynomially bounded heuristic algorithm to scale the proposed algorithm to bigger network topologies.     

Distributed channel assignment algorithms for 802.11n WLANs with heterogeneous clients

As the latest IEEE 802.11 standard, 802.11n applies several new technologies, such as multiple input multiple output (MIMO), channel bonding, and frame aggregation to greatly improve the rate, range and reliability of wireless local area networks (WLANs). In 802.11n WLANs, access points (APs) are often densely deployed to provide satisfactory coverage. Thus nearby APs should operate at non-overlapping channels to avoid mutual interference. It is challenging to assign channels in legacy 802.11a/b/g WLANs due to the limited number of channels. Channel assignment becomes more complex in 802.11n WLANs, as the channel bonding in 802.11n allows WLAN stations (APs and clients) to combine two adjacent, non-overlapping 20MHz channels together for transmission. On the other hand, IEEE 802.11n is backward compatible, such that 802.11n clients will coexist with legacy clients in 802.11n WLANs. Legacy clients may affect the performance of nearby 802.11n clients, and reduce the effectiveness of channel bonding. Based on these observations, in this paper, we study channel assignment in 802.11n WLANs with heterogeneous clients. We first present the network model, interference model, and throughput estimation model to estimate the throughput of each client. We then formulate the channel assignment problem into an optimization problem, with the objective of maximizing overall network throughput. Since the problem is NP-hard, we give a distributed channel assignment algorithm based on the throughput estimation model. We then present another channel assignment algorithm with lower complexity, and aim at minimizing interference experienced by high-rate, 802.11n clients. We have carried out extensive simulations to evaluate the proposed algorithms. Simulation results show that our algorithms can significantly improve the network throughput of 802.11n WLANs, compared with other channel assignment algorithms.     

无线Mesh网中具有QoS保障的MAC算法

(中南民族大学电子信息工程学院,武汉 430074)     

智能配电网通信多信道调度策略

为了有效提高基于无线传感网的配电网服务质量,进一步增强配电网中数据实时性,减少延迟,提出了一种基于优先级的多信道调度策略。首先,根据实时的信道链路状态信息,提出了基于最小跳数生成树的链路路由算法（LB-MHST）,克服了无线射频干扰,保证智能电网的服务质量;然后,针对配电网中不同数据包对于延迟要求的不同,考虑了数据优先级传输,有效地提高了感知节点的数据传输效率,进一步满足了配电网中的QoS性能要求。实验结果表明,与最小跳数生成树（MHST）算法相比,尤其是在多信道延迟感知传输中,提出算法在单信道、8信道和16信道时分别将高负载流量延迟性能提高了12%,15.2%和18%。     

Links organization for channel assignment in multi-radio wireless mesh networks

It is one key issue in the wireless mesh networks to provide various scenarios such as multimedia and applications. Links in the network can be organized and assigned to orthogonal channels so as to minimize the co-channel interference. In this paper we focus on the channel assignment problem for links in the mesh networks and aim at minimizing the overall network interference. The problem is proved to be NP-hard. We have first formulated an approach based on the Particle Swarm Optimization (PSO) algorithm which can be used to find the approximate optimized solution in small-size networks and as a baseline that other algorithms can be compared with. We also have proposed a centralized heuristic as well as a distributed heuristic algorithm for the channel assignment problem. Extensive simulation results have demonstrated that our schemes have good performance in both dense and sparse networks compared with related works.     

Distributed power adjustment based on control theory for cognitive radio networks

In this paper, we propose two power adjustment methods for cognitive radio networks. In the first algorithm, the transmitter derives the transmission power with PID control in order to satisfy the QoS constraints in secondary networks. The derived transmission power is compared with a constraint condition in order to avoid the interference with primary networks, and then the actual transmission power is decided. Because the constraint condition affects the performance of our proposed method significantly, we propose an effective update algorithm. On the other hand, the second algorithm is based on model predictive control (MPC). In this method, the decision of transmission power is formulated as quadratic programming (QP) problem and the transmission power is derived directly with the constraint condition. We evaluate the performances of our proposed methods with simulation and compare the proposed methods with the distributed power control (DPC) method. In numerical examples, we show that our proposed methods are more effective than the existing method in some situations. We also prove analytically that the interference with primary networks can be avoided with probability one by using our proposed method if each transmitter has the information about every channel gain.     

Interference management for rate-constrained moving relay node in a heterogeneous network

Cooperative communication via a moving relay node （MRN） helps resolve both the poor quality of service （QoS） and limited battery-capacity problems of cell-edge vehicle user equipment （VUE）. This paper investigates the performance of MRNs in a heterogeneous network （HetNet）. MRNs as well as other small cells are expected to coexist in a complex manner. In such a HetNet, the inter-cell interference may degrade the expected improvement of MRNs, especially at the cell-edge. In this paper, we investigate the impact of intercell interference on the performance of MRNs. To alleviate this impact, we first formulated a general optimization problem for which it is intractable to find a global optimal solution. To have a practical solution with low computational complexity, we used a practical interference management algorithm that aimed to ensure that every MRN achieved its required minimum-rate while maximizing total network throughput. In the simulations, the proposed algorithm was observed to improve both the QoS and fairness of MRNs. Numerical results demonstrate that the proposed algorithm can offer an efficient trade-off between the performance of both the victim MRNs and aggressing femtocells.