An Adaptive Distributed Channel Allocation Strategy for Mobile Cellular Networks

A channel allocation algorithm includes a channel acquisition algorithm and a channel selection algorithm. Most of the previous work concentrates on the channel selection algorithm since early channel allocation algorithms simply use a centralized channel acquisition algorithm, which depends on a mobile switching center (MSC) to accomplish channel acquisition. Recently, distributed channel acquisition algorithms have received considerable attention due to their high reliability and scalability. There are two approaches to designing distributed channel acquisition algorithms: search and update. The update approach has shorter acquisition delay and lower call blocking rate, but higher message complexity. On the other hand, the search approach has lower message complexity, but longer acquisition delay and higher call blocking rate. In this paper, we propose a novel distributed channel acquisition algorithm, which is a significant improvement over both approaches. Also, we identify two guiding principles in designing channel selection algorithms and propose an algorithm which has low call blocking rate and low intrahandoff overhead. By integrating the channel selection algorithm into our channel acquisition algorithm, we get a complete distributed channel allocation algorithm. By keeping the borrowed channels, the channel allocation algorithm makes use of the temporal locality and adapts to the network traffic; i.e., free channels are transferred to hot cells to achieve load balance. Simulation results show that our channel allocation algorithm significantly outperforms the search approach and the update approach in terms of call blocking rate, message complexity, and acquisition delay.     

Performance analysis of a threshold based distributed channel allocation algorithm for cellular networks

Rapid advances of the handheld devices and the emergence of the demanding wireless applications require the cellular networks to support the demanding user needs more effectively. The cellular networks are expected to provide these services under a limited bandwidth. Efficient management of the wireless channels by effective channel allocation algorithms is crucial for the performance of any cellular system. To provide a better channel usage performance, dynamic channel allocation schemes have been proposed. Among these schemes, distributed dynamic channel allocation approaches showed good performance results. The two important issues that must be carefully addressed in such algorithms are the efficient co-channel interference avoidance and messaging overhead reduction. In this paper, we focus on our new distributed channel allocation algorithm and evaluate its performance through extensive simulation studies. The performance evaluation results obtained under different traffic load and user mobility conditions, show that the proposed algorithm outperforms other algorithms recently proposed in the literature.     

UpdateSearch: A New Dynamic Channel Allocation Scheme for Mobile Networks That Can Adjust to System Loads

Distributed dynamic channel allocation techniques are an integral part of distributed mobile computing systems where nodes communicate among themselves via wireless radio channels. The channel allocation schemes can be broadly categorized as search based or update based. Search based techniques have low messaging complexity and are suited for high system load and low request rates. On the other hand update based schemes have higher messaging complexity but are more suitable for low system load and high request rates. This paper presents a combined scheme, called UpdateSearch, which provides the advantages of both types of schemes. UpdateSearch is parameterized by the number of channel classes k, 1kn, where n is the total number of channels in the system. The parameter k can be adjusted to control the number of concurrent searches and degree of contention between cells competing for channels in the system. For k=1 and k=n the scheme respectively behaves as basic search and basic update scheme [2]. A simple analytical model is used to compare the performance of UpdateSearch for various values of k with the basic update and search techniques in terms of channel allocation time and number of simultaneous channel selections allowed in the system under different system loading conditions.     

An efficient evolutionary algorithm for channel resource managementin cellular mobile systems

Modern cellular mobile communications systems are characterized by a high degree of capacity. Consequently, they have to serve the maximum possible number of calls while the number of channels per cell is limited. The objective of channel allocation is to assign a required number of channels to each cell such that both efficient frequency spectrum utilization is provided and interference effects are minimized. Channel assignment is therefore an important operation of resource management and its efficient implementation increases the fidelity, capacity, and quality of service of cellular systems. Most channel allocation strategies are based on deterministic methods, however, which result in implementation complexity that is prohibitive for the traffic demand envisaged for the next generation of mobile systems. An efficient heuristic technique capable of handling channel allocation problems is introduced as an alternative. The method is called a combinatorial evolution strategy (CES) and belongs to the general heuristic optimization techniques known as evolutionary algorithms (EAs). Three alternative allocation schemes operating deterministically, namely the dynamic channel assignment (DCA), the hybrid channel assignment (HCA), and the borrowing channel assignment (BCA), are formulated as combinatorial optimization problems for which CES is applicable. Simulations for representative cellular models show the ability of this heuristic to yield sufficient solutions. These results will encourage the use of this method for the development of a heuristic channel allocation controller capable of coping with the traffic and spectrum management demands for the proper operation of the next generation of cellular systems     

Dynamically adaptive channel reservation scheme for cellular networks

In personal communications networks (PCN) supporting network-wide handoffs, new and handoff requests compete for connection resources in both mobile and backbone networks. Forced call terminations due to handoff call blocking are generally more objectionable than new call blocking. In general, most of the previously proposed schemes for radio channel allocation in cellular networks reduce handoff call blocking probability substantially at the expense of increasing the new call blocking probability by giving higher priority to handoff calls over new calls in admission control. This reduces the total admitted traffic and results in inefficient utilization of wireless channels. The tradeoff between the new and handoff calls blocking probabilities should be defined on importance basis. In this paper, we propose a performance metric equation that makes a trade off between the two probabilities depending on the network preferences. Using this equation, we study the performance of various proposed channel reservation schemes. Also in this paper, a new dynamically adaptive channel reservation scheme (DACRS) is developed and compared with other schemes proposed in the literature. The DACRS assigns handoff-reserved channels to new calls depending on the locality principle in which the base station with the help of location estimation algorithms in the mobile location center predicts the position of the mobile terminal. Eventually, the DACRS is designed to improve channel utilization while satisfying the QoS of the calls. As will be shown analytically and through simulation, the DACRS outperforms current reservation schemes and results in more statistical gain, and powerful channel utilization.     

Distributed allocation and dynamic reassignment of channels in UAV networks for wireless coverage

Providing wireless coverage to users using Unmanned Aerial Vehicles (UAVs) encounters two major challenges: deployment and channel allocation. To this end, solutions to both issues are proposed in this paper. An overloaded UAV attempts to acquire more channels by performing channel bonding/aggregation followed by requesting its chosen peers to move closer for load sharing. The proposed channel reallocation schemes minimize interference caused by channel reassignments, or change in network topology. The simulation results show that when employing these schemes, more data is served with reduced discontinuous service time and efficient usage of limited battery power.     

Optimal prioritized channel allocation in cellular mobile systems

Under the cutoff priority discipline, the optimal prioritized channel allocation problem is formulated, which minimizes the weighted average blocking probability of handoff calls while ensuring the prespecified grade of service for new calls and the co-channel interference constraints. We use the concept of pattern to deal with the problem more conveniently. Using Lagrangean relaxation and subgradient optimization techniques, we obtain high-quality solutions with information about their deviations from true optimal solutions. Computational experiments show that our method works very well.Scope and PurposeChannel allocation is one of the most important problems in the design of cellular mobile systems. Since the number of cells of forthcoming networks will increase rapidly, this problem will be of even greater importance in the future. In cellular mobile systems, a new channel should be assigned by the new base when a call enters an adjacent cell. It provides continuation of ongoing calls as the user travels across cell boundaries, and is called handoff. The handoff call is forced to terminate before completion if there are no channels available in the new cell. However, in many practical situations, the blocking of a handoff call attempt is critical since it will result in a disconnection of the call in the middle of conversation. Thus, for reducing the blocking probability of handoff calls, several algorithms based on the cutoff priority scheme have been introduced in the literature. In the cutoff priority scheme, priority is given to handoff calls by exclusively reserving some channels called guard channels for them. In this article, we formulate a prioritized channel allocation problem under the cutoff priority scheme in general multicell environments, and suggest an efficient algorithm to solve that problem.     

WMN中的干扰避免部分重叠信道分配算法

针对无线mesh网络(wireless mesh networks,WMN)中存在的信道干扰问题,提出一种基于部分重叠信道(partially overlapping channels,POC)的负载平衡且干扰避免的信道分配算法。通过基于Huffman树的通信接口分配方法连接邻居节点的接口;根据网络干扰情况,对链路进行迭代信道分配,使用静态链路调度保证网络连接;利用启发式算法优先为重要程度较高的链路分配无干扰时隙,对链路调度进行优化。仿真结果表明,在具有混合流量的WMN中,所提算法可以显著提升网络吞吐量,降低网络干扰与平均丢包率,改善网络性能。     

一种基于有限信道的能量高效节点调度机制

在低负载、低功耗无线传感器网络中,节点状态切换的能量消耗因为用于数据传输的能量较小而变得不可忽略。针对此问题,提出了结合多信道技术与时分多路访问( TDMA)技术的节点调度算法。该算法设计了基于接收端的连续时隙分配策略以减少节点状态切换次数,并且在可用无线信道有限的约束条件下,提出了信道分配与时隙调整机制,实现了时隙重用并最小化有限信道约束对优化节点状态切换次数的影响。仿真实验结果表明,当可用无线信道数为3~5时,算法能够有效地改善节点能量效率。当可用无线信道数大于3之后,算法能够获得优化的数据汇聚时间。     

Predictive channel reservation for handoff prioritization in wireless cellular networks

In wireless cellular networks, a roaming mobile station (MS) is expected to move from one cell to another. In order to ensure that ongoing calls are not dropped while the owner mobile stations roam among cells, handoff calls may be admitted with a higher priority than newly generated calls. Predictive channel reservation (or pre-reservation) schemes allow the reservation of a channel for an ongoing call in an adjacent cell before its owner MS moves into that cell, so that the call is sustained when the MS moves into the adjacent cell. Pre-reservations are made when the MS is within some distance of the new cell boundary. This distance determines the area in which the MS can make channel reservations. In this paper, we study the effect of the pre-reservation area size on handoff performance in wireless cellular networks. Our studies show that if the reserved channels are strictly mapped to the MSs that made the corresponding reservations, as we increase the pre-reservation area size, the system performance (in terms of the probability that the handoff calls are dropped) improves initially. However, beyond a certain point, the performance begins to degrade due to a large number of false reservations. The optimal pre-reservation area size is closely related to the traffic load of the network and the MSs’ mobility pattern (moving speed). We provide an analytical formulation that furthers understanding with regard to the perceived behavior in one-dimensional networks (in which all cells are along a line).With the objective of improving handoff performance and alleviating this sensitivity to the area size, we propose an adaptive channel pre-reservation scheme. Unlike prior pre-reservation methods, the key idea in our scheme is to send a channel pre-reservation request for a possible handoff call to a neighboring cell not only based on the position and orientation of the owner MS, but also as per its speed towards the target cell. The newly proposed scheme uses GPS measurements to determine when channel pre-reservation requests are to be made. Simulation results show that the adaptive channel pre-reservation scheme performs better in all typical scenarios than a previously proposed popular pre-reservation method that does not take mobility into account.     

异构网中基于改进蝙蝠算法的动态CRE偏置选择

Macrocell和Femtocell的两层蜂窝网络中的用户位置在空间和时间上具有很大的随机性,给资源分配和干扰管理带来许多挑战。为了适应这种随机性的资源分配,提高同频组网中下行异构蜂窝网络的小区边缘用户的通信速率,更好地实现负载均衡效果,提出了一种基于改进蝙蝠算法来实时动态设置Femtocell小区范围扩展偏置值（CRE）的方案,来缓解宏基站高热点负载压力,提高网络容量,从而用户合理选择接入不同基站,使功率资源得到合理利用,达到负载均衡的目的。仿真结果表明,与现有方案相比,该方案在保证Macrocell通信性能的情况下,提高了小区边缘数据速率及能效,实现了更好的负载均分效果。     

Satisfying demands in a multicellular network: A universal power allocation algorithm

Power allocation to satisfy user demands, in the presence of large number of interferers (in a multicellular network), is a challenging task. Further, the power to be allocated depends upon the system architecture, for example upon components like coding, modulation, transmit precoder, rate allocation algorithms, available knowledge of the interfering channels, etc. This calls for an algorithm via which each base station in the network can simultaneously allocate power to their respective users so as to meet their demands (whenever they are within the achievable limits), using whatever information is available of the other users. The goal of our research is to propose one such algorithm which in fact is universal: the proposed algorithm works from a fully co-operative setting to almost no co-operation and or for any configuration of modulation, rate allocation, etc. schemes. The algorithm asymptotically satisfies the user demands, running simultaneously and independently within a given total power budget at each base station. Further, it requires minimal information to achieve this: every base station needs to know its own users demands, its total power constraint and the transmission rates allocated to its users in every time slot. We formulate the power allocation problem in a system specific game theoretic setting, define system specific capacity region and analyze the proposed algorithm using ordinary differential equation (ODE) framework. Simulations further confirm the effectiveness of the proposed algorithm. We also demonstrate the tracking abilities of the algorithm.     

混合网络数据动态交换时隙再分配方法仿真

现有的混合网络数据动态交换时隙再分配方法,存在时延较大、时隙利用率较低等问题,提出基于WCDMA和数据链的交换时隙再分配方法,去除信道中的干扰信号,补偿由于数据传输造成的信号衰弱,通过信道的信干比估计,完成对信道的处理。当前分配时隙资源不能满足信息发送所需时,会在固定时隙内,周期性的发送时隙再分配消息给混合网络单元,并提出所需时隙资源,根据时隙动态分配方法,定制出混合网络时隙分配表,通过定制的时隙分配表,实现对混合网络数据动态交换的时隙再分配。仿真结果表明,所提方法能够在低时延、高时隙利用率的情况下,实现对混合网络数据动态交换时隙的再分配。     

异构分层无线网络中基于业务和逗留时间的动态流量均衡算法

在异构分层无线网络中使用有效的流量均衡技术,可以给更多的移动用户提供服务。现有的流量均衡算法主要针对同种无线网络,因而不能直接用于异构无线网络。本文提出了一种适用于异构无线网络的基于业务和逗留时间的动态流量均衡算法,该算法首先根据移动模型计算移动用户在小区内的逗留时间,然后基于小区呼叫到达率和重叠覆盖小区的流量状态来确定一个周期内转移的非实时性呼叫数量,最后依据逗留时间门限值将重负载小区中满足条件的呼叫转移到轻负载的重叠覆盖小区中。为降低切换呼叫掉线率,还对异构网间的呼叫切换策略做了改进。仿真实验结果表明．本算法在新呼叫阻寒率和切换呼叫掉线率等性能指标上比传统方法有显著提高．     

基于多对一Gale-Shapley算法的D2D通信资源分配

针对D2D通信复用异构蜂窝网络上行信道产生的干扰问题和频谱资源优化问题进行研究,提出一种基于多对一Gale-Shapley算法的D2D通信资源分配方案。本方案允许多个D2D用户共享一个蜂窝用户信道资源,通过设置信干噪比（SINR）门限保证用户的通信服务质量（QOS）。根据信道分配情况,构建D2D用户和信道的偏好列表,最大化系统总容量。仿真结果表明,该方案收敛较快,复杂度较低,能够有效保证用户的通信服务质量,系统总容量接近最优解。本研究为实现D2D用户和蜂窝用户的频谱资源共享,提高频谱利用率提供了一种有效方案。     

Resource management policies in GPRS systems

In this paper we consider the problem of resource management in GSM/GPRS cellular networks offering not only mobile telephony services, but also data services for the wireless access to the Internet. In particular, we investigate channel allocation policies that can provide a good tradeoff between the QoS guaranteed to voice and data services end users, considering three different alternatives, and developing analytical techniques for the assessment of their relative merits. The first channel allocation policy, voice priority, gives priority to voice in the access to radio channels; we show that this policy cannot provide acceptable performance to data services, since when all the channels are busy with voice connections, data services perceive long intervals of service interruption. The second channel allocation policy is called R-reservation; it statically reserves a fixed number of channels to data services, thus drastically improving their performance, but subtracting resources from voice users, even when these are not needed for data, thus inducing an unnecessary performance degradation for voice services. The third channel allocation policy is called dynamic reservation; as the name implies, it dynamically allocates channels to data when necessary, using the information about the queue length of GPRS data units within the base station. A threshold on the queue length is used in order to decide when channels must be allocated to data. Numerical results show that the dynamic reservation channel allocation policy can provide effective performance tradeoffs for data and voice services, with the additional advantage of being easily managed through the setting of the threshold value.     

OFDMA techniques in multicellular networks with total frequency reuse

Orthogonal frequency division multiple access (OFDMA) techniques are investigated in this paper. Five subchannel allocation algorithms are analysed and their performance in a multicellular environment is evaluated with simulations. Four schemes of lower complexity, suitable for the early deployment of wireless systems, are compared with a more computationally demanding scheme with respect to their blocking probability, loading factor and offered bit rate. The channel condition of each carrier is calculated and its knowledge is used for power controlled adaptive modulation, as an essential feature of the OFDMA technique. The general radio resource management process is divided into two steps: in the first step a base station allocates carriers to users while in the second step the modulation and power levels for each allocated carrier are defined.The simulation results demonstrate that a wireless system in its early deployment phase (up to 15–30% blocking probability) can employ simple OFDMA techniques capable of achieving high throughput. Furthermore, it is demonstrated that two of the proposed lower complexity schemes, (those based on cell coordination), offer good performance gain for higher data rate services. Nevertheless, these schemes achieve relatively lower gains with adaptive modulation, when compared with the techniques which exploit interference averaging or adaptive interference mitigation.     

Using Cellular Probabilistic Self-Organizing Map in Borrowing Channel Assignment for Patterned Traffic Load

The fast growing cellular mobile systems demand more efficient and faster channel allocation techniques. Borrowing channel assignment (BCA) is a compromising technique between fixed channel allocation (FCA) and dynamic channel allocation (DCA). However, in the case of patterned traffic load, BCA is not efficient to further enhance the performance because some heavy-traffic cells are unable to borrow channels from neighboring cells that do not have unused nominal channels. The performance of the whole system can be raised if the short-term traffic load can be predicted and the nominal channels can be re-assigned for all cells. This paper describes an improved BCA scheme using traffic load prediction. The prediction is obtained by using the short-term forecasting ability of cellular probabilistic self-organizing map (CPSOM). This paper shows that the proposed CPSOM-based BCA method is able to enhance the performance of patterned traffic load compared with the traditional BCA methods. Simulation results corroborate that the proposed method delivers significantly better performance than BCA for patterned traffic load situations, and is virtually as good as BCA in the other situations analyzed.     

Cross-Layer prioritized H.264 video packetization and error protection over noisy channels

Video transmission over wireless channels is affected by channel-induced packet losses. Distortion due to channel errors can be alleviated by applying forward error correction. Aggregating H.264/AVC slices to form video packets with sizes adapted to their importance can also improve transmission reliability. Larger packets are more likely to be in error but smaller packets require more overhead. We present a cross-layer dynamic programming (DP) approach to minimize the expected received video distortion by jointly addressing the priority-adaptive packet formation at the application layer and rate compatible punctured convolutional (RCPC) code rate allocation at the physical layer for prioritized slices of each group of pictures (GOP). Some low priority slices are also discarded to improve protection to more important slices and meet the channel bit-rate limitations. We propose two schemes. Our first scheme carries out joint optimization for all slices of a GOP at a time. The second scheme extends our cross-layer DP-based approach to slices of each frame by predicting the expected channel bit budget per frame for live streaming. The prediction uses a generalized linear model developed over the cumulative mean squared error per frame, channel SNR, and normalized compressed frame bit budget. The parameters are determined over a video dataset that spans high, medium and low motion complexity. The predicted frame bit budget is used to derive the packet sizes and corresponding RCPC code rates for live transmission using our DP-based approach. Simulation results show that both proposed schemes significantly improve the received video quality over contemporary error protection schemes.     

A cross-layer optimization framework for joint channel assignment and multicast routing in multi-channel multi-radio wireless mesh networks

Existing literature on multicast routing protocols in wireless mesh networks (WMNs) from the view point of the links involved in routing are divided into two categories: schemes are aimed at multicast construction with minimal interference which is known as NP hard problem. In contrast, other methods develop network-coding-based solutions with the main objective of throughput maximization, which can effectively reduce the complexity of finding the optimal routing solution from exponential to polynomial time. The proposed framework in this paper is placed in the second category. In multi-channel multi-radio WMNs (MCMR WMNs), each node is equipped with multiple radios, each tuned on a different channel. In this paper, for the first time, we propose a cross-layer convex optimization framework for joint channel assignment and multicast throughput maximization in MCMR WMNs. The proposed method is composed of two phases: in the first phase, using cellular learning automata, channels are assigned to the links established between the radios of the nodes in a distributed fashion such that the minimal interference coefficient for each link is provided. Then, the resultant channel assignment scheme is utilized in the second phase for throughput maximization within an iterative optimization framework based on Lagrange relaxation and primal problem decomposition. We have conducted many experiments to contrast the performance of our solution against many representative approaches.