Joint Power-Frequency-Time Resource Allocation in Clustered Wireless Mesh Networks

QoS provisioning for Wireless Mesh Networks (WMN) is a very desirable objective, since it requires great thoughtfulness, scalability and thoroughfull analysis. In this paper, numerical and statistical analysis of packet-level resource allocation with effective QoS provisioning for WMS approach is being introduced. Power allocation, packet scheduling, subcarrier allocation, and QoS support are investigated and analyzed in combined Karush-Kuhn-Tucker (KKT)-driven and a genetic algorithm (GA)-based approach, that achieves a desired balance between time complexity and system performance.

Wireless mesh networking has trans pired as a gifted technology for potentialbroadband wireless access. In a communication network, wireless mesh network plays a vital role in transmission and are structured in a mesh topology. The coordination of mesh routers and mesh clients forms the wi reless mesh networks which are routed through the gateways.Wireless mesh networks uses IEEE 802.11 standards and has its wide applications broadband home networking and enterprise networking deployment such as Microsoft wireless mesh and MIT etc. A profes sional Qos provisioning in intra cluster packet level resource allocation for WMN approach takes power allo cation, sub carrier allocation andpacket scheduling. This approach combines the merits of aKarush-Kuhn-Tucker (KKT) algorithm and a genetic algorithm (GA) based approach. The KKT algorithm uses uniform power allocation over all the subcarriers, based on the optimal allocation criterion. The genetic algorithm is used to generate useful solutions to optimization and search problems and it is also used for search problems. By combining the intrinsic worth of both the approaches, it facilitates effective QOS provisioning at the packet level. It is conclude d that, this approach achieves a preferred stability between system implementation and computational convolution.

Wireless Mesh Network (WMN) is recently emerged network having robustness. It supports clients to communicate with different types of networks, Internet etc which provides a better service to next generation. It consists of mesh routers and mesh clients. These mesh routers are minimal mobile and mesh clients are totally mobile. The protocols of Ad hoc network are used in WMN. These protocols assume that every node is mobile. But as the mesh routers are minimal mobile or not mobile, the protocols brings overhead for the mesh routers. Our task is to relieve mesh routers using ad hoc network protocol from the overhead and define a better protocol which will fit in WMN efficiently. To do so, we've found that the existing architecture of WMN is needed to be changed slightly. We have proposed a new architecture for Wireless Mesh Network. In our proposal WMN is relieved from overhead being caused by using ad hoc network protocol. Our architecture use unicasting technique in lieu of broadcasting technique for route discovery as well as route maintenance. We will first describe the overview of WMN, its existing architecture. Later we will go to our proposed architecture.

In multi-channel wireless mesh networks (WMNs), it is significantly important to achieve efficient channel utilization. The channel assignment problem, which investigates how to seek a proper mapping between available channels and network interface cards (NICs) on mesh routers (MRs), is attracting more and more attention from the research community. However, most proposed channel assignment approaches assume that NICs are evenly placed on the MRs, and its amount is also pre-determined. Due to the non-uniform distribution of WMN traffic, the equal interface placement will inevitably cause that the bottleneck MRs suffer from NIC shortage, and MRs with less load only have a low utilization of NICs. Hence, in order to improve network performance and reduce network cost, interface placement should be considered carefully in the process of planning a WMN. In this paper, we investigate the joint interface placement and channel assignment problem, i.e., how to appropriately place NICs on MRs and assign channels to them. We first formulate the problem as a mixed integer linear programming (MILP) model, which aims to minimize the total number of NICs while satisfying logical link, link bandwidth, link interference and traffic demand constraints. Then, we propose an MILP-based heuristic algorithm, using iterated local search to obtain sub-optimal solutions efficiently. Finally, we conduct simulation experiments to compare the heuristic solutions with the optimal solutions, and the results show that our proposed heuristic algorithm can achieve good sub-optimal solutions. Moreover, the simulation results also demonstrate that the algorithm can be well applied in large-scale WMNs where the optimal solutions cannot be obtained, and can perform well under different traffic demands.

In multicarrier nonorthogonal multiple access (MC‐NOMA) systems, resource allocation for user rate fairness is an inherent challenge due to the huge difference in channel conditions among different users. As the general case of proportional fairness, proportional rate constraint is usually adopted in resource allocation optimization problems to ensure that achievable rates of users are distributed proportionally according to a set of arbitrarily predefined portion. In this article, we investigate joint subcarrier and power allocation in MC‐NOMA systems under proportional rate constraints. The formulated resource allocation optimization problem belongs to a mixed integer nonlinear programming (MINLP) problem due to its binary subcarrier allocation variables and nonaffine equality constraints. By introducing an auxiliary variable in proportional rate constraints and substituting power variable with rate variable, we convert this nonconvex problem into a convex optimization problem and solve it by using Karush‐Kuhn‐Tucker (KKT) conditions and the dual decomposition method. Based on the optimal solutions, we divide the resource allocation process into two phases, that is, subcarrier allocation and power allocation, and develop an optimal subcarrier allocation solution based resource allocation algorithm (OSSRA). Furthermore, we also propose a heuristic algorithm, referred to as proportional rate constrained subcarrier allocation algorithm (PCSAA), as a benchmark. Numerical results show that, substantial gains can be achieved by OSSRA over the existing work and the traditional orthogonal multiple access (OMA) schemes in terms of both sum rate and user fairness. Besides, PCSAA has better user fairness performance than OSSRA.

The wireless mesh network is emerging as a promising technology in providing economical and scalable broadband Internet accesses to communities. The backbone of the wireless mesh network consists of mesh routers, which connect each other in an ad hoc manner via wireless links. The presence of backbone mesh routers and utilization of multiple channels and interfaces allow the wireless mesh network to have better capacity than that of the infrastructure-free ad hoc network formed by mesh clients directly. A special type of the mesh routers, referred to as gateway nodes, is capable of Internet connection, and other mesh routers and associated terminal clients have to access the Internet through the gateway nodes. In this paper, we present the analytically traceable stochastic models to characterize the average delay and throughput performance in wireless mesh networks. We model the forwarding mesh routers as an open queuing network. The analytical model takes into account the mesh router density, the random packet arrival process, the degree of locality of traffic and the collision avoidance mechanism of the IEEE802.11 DCF random access MAC. Our simulation results suggest that the analytical results are quite accurate, which can provide valuable insights in system performance and an effective guideline for the scalable design and optimization in wireless mesh networks.

The resource allocation of Orthogonal Frequency Division Multiple Access (OFDMA) is one of the core issues in the next generation mobile systems. The improvement in the performance and quality of service (QoS) of communication systems is relying upon the efficient utilization of the available communication resources. The resource allocation of the OFDMA systems is mainly depends on both power and subcarrier allocations of each user for different operation scenarios and channel conditions. This paper proposes and applies Firefly Pack Algorithm (FPA) to find the optimal or near optimal power and subcarrier allocations for OFDMA systems. It takes into consideration the power and subcarrier allocations constrains, channel and noise distributions, distance between users equipments and base station, user priority weight to approximate the most of the variables, constrains, and parameters that encounter in the OFDMA systems. Four important cases for the number of subcarriers and users are addressed, simulated, and analyzed with employing the FPA algorithm under specific operation scenarios to meet the standard specifications. The results demonstrate that FPA is an effective algorithm in finding the optimal or near optimal for both subcarrier and power allocation.

An infrastructure wireless mesh network (WMN) is a hierarchical network consisting of mesh clients, mesh routers and gateways. Mesh routers constitute a wireless mesh backbone, to which mesh clients are connected as a star topology, and gateways are chosen among mesh routers providing Internet access. In this paper, the throughput capacity of infrastructure WMNs is studied. For such a network with Nc randomly distributed mesh clients, Nr regularly placed mesh routers and Ng gateways, assuming that each mesh router can transmit at W bits/s, the per-client throughput capacity has been derived as a function of Nc , Nr , Ng and W . The result illustrates that, in order to achieve high capacity performance, the number of mesh routers and the number of gateways must be properly chosen. It also reveals that an infrastructure WMN can achieve the same asymptotic throughput capacity as that of a hybrid ad hoc network by choosing only a small number of mesh routers as gateways. This property makes WMNs a very promising solution for future wireless networking.

Resource allocation and admission control algorithm based on non-cooperation game in wireless mesh networks

In this paper, the problem of subcarrier allocation, and power allocation is addressed in an OFDM-based two-tier femto-cell network comprising of a conventional macro-cell and multiple femto-cells. The macro-cell users near the femto-cell causes significant interference to the femto-cell users as well gets interfered by the femto-cell transmissions. We present a subcarrier and power allocation method in underlay femto-cell network while keeping the total interference to macro-cell users under acceptable levels. We maximize the multiple femto-cell users throughput by jointly allocating subcarriers to users within a femto-cell, and also power allocation, under the constraints of cross-tier interference between macro-cell and multiple femto-cells as well as interference among femto-cells. Then, based on this subcarrier and power allocation the performance of the two-tier network is analysed with capacity as the performance metric.

Providing physical-layer security for mobile users in future broadband wireless networks is of both theoretical and practical importance. In this paper, we formulate an analytical framework for resource allocation in a downlink OFDMA-based broadband network with coexistence of secure users (SU) and normal users (NU). The problem is formulated as joint power and subcarrier allocation with the objective of maximizing average aggregate information rate of all NU's while maintaining an average secrecy rate for each individual SU under a total transmit power constraint for the base station. We solve this problem in an asymptotically optimal manner using dual decomposition. Our analysis shows that an SU becomes a candidate competing for a subcarrier only if its channel gain on this subcarrier is the largest among all and exceeds the second largest by a certain threshold. Furthermore, while the power allocation for NU's follows the conventional water-filling principle, the power allocation for SU's depends on both its own channel gain and the largest channel gain among others. We also design a suboptimal algorithm to reduce the computational cost. Numerical studies are conducted to evaluate the performance of the proposed algorithms in terms of the achievable pair of information rate for NU's and secrecy rate for SU at different power consumptions.

Multiuser orthogonal frequency division multiplexing (OFDM) is a very promising multiple access technique to efficiently utilize limited RF bandwidth and transmit power in wideband transmission over multipath fading channels. When a wideband spectrum is shared by multiple users in multiuser OFDM-based systems, different users may experience different fading conditions at all subcarriers. Each user is assigned a subset of all subcarriers by some allocation algorithm. Thus, multiuser diversity can be achieved by adaptively adjusting subcarrier, bit, and power allocation depending on channel status among users at different locations (Wong et al., 1999a). In (Wong et al., 1999a), Wong applies a Lagrangian optimization technique and an iterative algorithm to solve the subcarrier, bit and power allocation problem. The suboptimal scheme for the NP-hard joint optimization problem is decoupled into two steps while it has a high computational complexity. A sub-optimal algorithm has been proposed to solve a related problem (Wong et al., 1999b). In (Wong et al., 1999b), Wong presents a real-time subcarrier allocation (SA) algorithm. It is a two-phase algorithm, including the constructive initial assignment (CIA) and the subcarrier swapping steps. The initial subcarrier allocation algorithm needs to pre-determine the numbers of subcarriers for each user before the allocation process starts. The performance of the SAbased algorithm will be compared in the simulation. In (Kim et al., 2006), Kim shows that the allocation problem in (Wong et al., 1999a) can be transformed into an integer programming (IP) problem. The branch-and-bound algorithm (Wolsey, 1998) can be employed to find the optimal solution of the allocation problem which has exponential computational complexity in the worse cases. We utilize the approach to obtain the optimal solution as the performance bound for comparison. Evolutionary algorithms (EA) are used to solve extremely complex search and optimization problems which are difficult to solve through simple methods. EAs are intended to provide a better solution, as it is based on the natural theory of evolution. Evolutionary algorithm (EA)-based schemes have been applied to solve subcarrier, bit, and power allocation problems (Wang et al., 2005) (Reddy et al., 2007) (Reddy & Phora, 2007) (Pao & Chen, 2008). In general, chromosomes can be designed with binary, integer, or real representation. The chromosome lengths are related to the number of subcarriers. Each element in the chromosome is a subcarrier allocated to a user. In this research, a subset of subcarriers can be assigned to one user depending upon the availability of subcarriers at a particular time

Wireless mesh networks (WMNs) have recently evoked much research attention as a novel technology for last-mile broadband Internet access. When designing a WMN, gateway placement is significant for it determines the total network throughput. To address this problem, a novel gateway placement approach is proposed in this paper, in which three objectives are optimized, i.e. the number of gateways, the average MR (mesh router)-GW (gateway) hop count and the variance of gateway load. The gateway placement problem is modeled as a multiple objective linear program first, and then a two-stage load balanced gateway placement algorithm is proposed. The first stage is weight-based greedy gateway selection, and the second stage is load balanced MR attachment. Simulation results show that the algorithm behaves similarly compared with existing approaches in both number of gateways and average MR-GW hop count, while achieving better load balance.

Cognitive Radio (CR) technology constitutes a promising approach to increase the capacity of Wireless Mesh Networks (WMNs). Using this technology, Mesh Routers (MRs) and the attached Mesh Clients (MCs) are allowed to opportunis- tically transmit on the licensed band, but under the constraint not to interfere with the Primary Users (PUs) of the spectrum. Thus, the effective deployment of CR- WMNs require that each MR must be able to: sense the current spectrum, select an available PU-free channel and perform the spectrum handoff to a new channel in case of PU arrival on the current one. How to coordinate these actions in the optimal way which maximizes the performance of the CR-WMNs while minimizing the interference to the PUs constitutes an open research issue in CR systems. In this paper, we propose an adaptive spectrum scheduling and allocation scheme which allows a MR to identify the best schedule of (i) when to sense the current channel, (ii) when to transmit, (iii) when to perform a spectrum handoff. Due the large number of parameters involved, we propose Reinforcement Learning (RL) techniques to allow a MR to learn by itself the optimal balance between spectrum sensing-exploitation- exploration actions based on network feedbacks coming from the MCs. We perform extensive simulations which confirm the adaptivity and efficiency of our approach in terms of increased throughput when compared with non-learning based schemes for CR-WMNs.

In this paper, we compare the performance attained by several scheduling policies when the resource allocation is performed in a per-user or in a per-frequency resource ordering. We test the capability of both approaches to deal with the quality of service (QoS) provisioning in a multi-service scenario in a mobile OFDMA network. We probe that the comparative performance of these two approaches depends on the actual scheduling policy, under a certain power and subcarrier allocation (PSA) algorithm that efficiently controls the inter-cell interference (ICI).