Priority-based bandwidth allocation in heterogeneous wireless network

One of the most important features of the evolving Fourth Generation (4G) wireless communication system is heterogeneous wireless access in which users could connect to several wireless access networks simultaneously. The new feature brings new challenges for the bandwidth allocation (BA) among heterogeneous networks. A non-cooperative bandwidth allocation game (NCBAG) algorithm for heterogeneous wireless networks is proposed in this paper. A BA problem is modeled as a non-cooperative game, and formulated to maximize the total utility of different networks. The existence of Nash equilibrium is verified for the proposed game model. The utility functions are developed for different applications to avoid assigning too much bandwidth to single user. Simulation results show that our proposed scheme can not only achieve high utility, but also reduce the blocking probability within a few steps of iteration.

In this paper, we investigate the bandwidth and power allocation problem in remote radio head cluster (RRHC)-based millimeter wave (mm-wave) massive MIMO heterogeneous cloud radio access networks with limited fronthaul capacity. The coordinated multipoint transmission is applied in each RRHC for cancelling the intra-cluster interference. To avoid the inter-tier interference, distinct bandwidths are allocated to macro base station and RRHs. Following this, we formulate a bandwidth and power allocation optimization problem to maximize the downlink weighted sum rate of the system subject to per-RRHC power and fronthaul capacity constraints, which is a non-convex optimization problem and is difficult to directly solve. Next, we fix the bandwidth allocation and the original problem can be divided into two independent optimization problems, i.e., the weighted sum rate maximization problems of MUs and RRH users, respectively. For the former, the convex optimization technique can be used to solve it. As for the latter, a two-loop iterative algorithm is proposed to deal with it. Specifically, we propose the price-based outer iteration to control the fronthaul capacity and the weighted minimum mean square error-based inner iteration to obtain the power allocation. To this end, a 1-D search method is adopted to find the optimal bandwidth allocation. Finally, numerical results are conducted to verify the effectiveness of the proposed algorithms under different parameters.

This paper presents a dynamic bandwidth allocation scheme for multiple services in heterogeneous networks. A utility function is introduced first, whose parameters are determined by the modified multi-state Analytic Hierarchy Process (AHP) which adapts to different load levels according to dynamic thresholds. Based on this, a bandwidth allocation algorithm is proposed for Constant Bit Rate (CBR) and Variable Bit Rate (VBR) services depending on not only utility fairness among different networks, but also the fairness between new arrival and ongoing services. Simulation results show that the proposed algorithm is effective in guaranteeing both the fairness of the edge users and the network system performance, i.e. keeping low block probability in the wireless network system.

Heterogeneous networks (HetNets) composed of macrocells and small cells are expected to improve the transmission performance of users significantly. Designing efficient resource allocation schemes, specifically, bandwidth allocation and power allocation schemes for HetNets is of particular importance for it may affect user quality of service (QoS) and network performance severely. In this paper, we consider the resource allocation problem of a HetNet composed of a macrocell and a number of femtocells and propose a resource characteristic and user QoS oriented bandwidth and power allocation algorithm for the femto base stations (FBSs) which share spectrum with the macro base station. By taking into account the service requirements of the femto user equipments (FUEs) and the bandwidth resource characteristics of the network, various bandwidth resource allocation schemes are proposed. Particularly, in the case of slightly insufficient bandwidth resource, we propose a bankruptcy game based bandwidth resource allocation algorithm for the FBSs, and solve the bandwidth allocation problem by means of Shapley value method. To stress the tradeoff between data rate and power consumption, we examine the energy efficiency of the FBSs and formulate the power allocation problem as a multi-objective optimization problem with the objectives of maximizing the energy efficiency of all the FBSs. The optimal power allocation strategy can be obtained by solving the optimization problem via ideal point method and generic algorithm. Simulation results demonstrate the efficiency of the proposed algorithm.

Future cellular networks are facing crucial architecture changes to cope with high throughput, energy and cost-efficiency demands. Emerging solutions are small-cells and femto-cells which will coexist with classical macro-cells technology. In these heterogeneous networks, we study the joint service pricing and bandwidth allocation problem at the operator level. Each user selfishly adopts the service that optimizes its satisfaction. The user-level problem is formulated as a general non-atomic game. The Wardrop equilibrium is proven to exist and an analytical expression is provided for arbitrary number of services. The equilibria multiplicity, the influence of pricing and bandwidth allocation policies are investigated numerically.

In this paper, the optimization of network performance to support the deployment of federated learning (FL) is investigated. In particular, in the considered model, each user owns a machine learning (ML) model by training through its own dataset, and then transmits its ML parameters to a base station (BS) which aggregates the ML parameters to obtain a global ML model and transmits it to each user. Due to limited radio frequency (RF) resources, the number of users that participate in FL is restricted. Meanwhile, each user uploading and downloading the FL parameters may increase communication costs thus reducing the number of participating users. To this end, we propose to introduce visible light communication (VLC) as a supplement to RF and use compression methods to reduce the resources needed to transmit FL parameters over wireless links so as to further improve the communication efficiency and simultaneously optimize wireless network through user selection and resource allocation. This user selection and bandwidth allocation problem is formulated as an optimization problem whose goal is to minimize the training loss of FL. We first use a model compression method to reduce the size of FL model parameters that are transmitted over wireless links. Then, the optimization problem is separated into two subproblems. The first subproblem is a user selection problem with a given bandwidth allocation, which is solved by a traversal algorithm. The second subproblem is a bandwidth allocation problem with a given user selection, which is solved by a numerical method. The ultimate user selection and bandwidth allocation are obtained by iteratively compressing the model and solving these two subproblems. Simulation results show that the proposed FL algorithm can improve the accuracy of object recognition by up to 16.7% and improve the number of selected users by up to 68.7%, compared to a conventional FL algorithm using only RF.

Bandwidth allocation and admission control scheme based on Nash bargaining solution for WiMAX systems

A novel multibeam satellite system design is proposed in this paper based on jointly optimizing power and carrier allocation in order to best match the asymmetric traffic requests. This design introduces higher and asymmetric interference levels throughout the coverage. However, both power and bandwidth will be used more efficiently. Even though the problem of power and bandwidth allocation has been addressed in terrestrial wireless communications, it is new in satellite systems and since architecture and channel are different, available results and algorithms are not applicable to satellite payload systems. In this paper we formulate the resource allocation problem as max-min SINR balancing based on the recently introduced axiomatic-based interference model, but in addition, we also optimize the carrier allocation when performing the SINR balancing problem. An analytical solution for the optimal carrier allocation is proposed and we iteratively find the optimal power allocation for each beam. The Shannon (upper bound) and current state-of-the art PHY layer technology: DVB-S2 are proposed to be implemented in order to obtain the gap between them. Simulation results show significant improvements in terms of power gain, spectral efficiency and traffic matching ratio comparing with conventional system, which is designed based on uniform bandwidth and power allocation.

Many studies have shown that Vegas TCP has a better throughput and stability than Reno TCP in homogeneous networks with a single TCP flavor, but performs less well in heterogeneous networks in which two TCP flavors coexist. The progressive behavior of Reno TCP and the conservative behavior of Vegas TCP cause a bias when they are used simultaneously, and thus Vegas TCP fails to obtain a fair share of the bandwidth. This paper examines the origins of this bias and proposes a threshold-based congestion control mechanism designed to alleviate the resulting unfairness problem. The simulation results show that the proposed scheme achieves a higher throughput than the conventional Vegas TCP scheme and preserves the stability of the conventional scheme when used in heterogeneous wired and wireless networks.

Network reliability analyses have received much attention in heterogeneous wireless network performance evaluation during the last few years. In this paper, a method for heterogeneous wireless network reliability evaluation to meet the required levels of heterogeneous wireless network differences of various graph-theoretic connectivity measures is proposed. A concept of heterogeneous wireless network reliability degree is proposed and a heterogeneous wireless network reliability entropy-based method for analyzing the proposed reliability measure is discussed. This method is based on heterogeneous wireless network survivability and stability analyses. Its core is the computation of some heterogeneous wireless network combinatorial invariants. These invariants, once computed, directly provide pure and simple framework for computation of heterogeneous wireless network reliability. We illustrate how a new approach to assessing the performance of in heterogeneous wireless networks. Our results also illustrate how the characteristics of the heterogeneous wireless networks may affect the performance of the different measures. We also present some simulation results.

This article focuses on the problem of bandwidth allocation to users of Cloud data centers. An interesting approach is to use advance bandwidth reservation. Such systems usually assume all requests demand either bandwidth-guarantee (BG) or time-guarantee (TG), but not both. Hence the solutions are tailored for one type of requests. A BG request demands guarantee on bandwidth; whereas a TG request demands guarantee on time for transfer of data of specified volume. We define a new model that allows users to not only submit both kinds of requests, but also specify flexible demands. We tie up the problem of bandwidth allocation with differential pricing, that gives discounts to users based on the flexibility in their requests. We propose a two-phase, adaptive and flexible bandwidth allocator (A-FBA) that, in one phase admits and allocates minimal bandwidth to dynamically arriving user requests, and in another phase, allocates additional bandwidth for accepted requests maximizing revenue. The problem formulated in first phase is <inline-formula><tex-math>${\cal NP}$</tex-math></inline-formula> -hard, while the second phase can be solved in polynomial time. We show that, in comparison to a traditional deterministic model, the A-FBA not only increases the number of accepted requests significantly, but also does so by generating higher revenues.

As many access technologies develop, more and more heterogeneous wireless networks appear around us. In this case, when whole mobile networks move from the visiting network to another, the handoff attracts the attentions especially. The exited handoff methods with network mobility merely extended the scheme of handoff in MIPv6 or integrated the exited methods into the uniform scheme but it can not make the good effect to really and truly solve the fast and smooth (packet lossless) handoff in heterogeneous wireless networks. In this paper, the fast handoff scheme is given and it provides Multi-Mobile Router (MMR) with a vicinage table to keep information about their vicinages access router. Using this method, it performs the Fast Handoff with network mobility effectively in heterogeneous wireless networks. In addition, we introduce the new entity TCS (temporary control server) to manage MMR procedure in order to complete fast handoff and reduce the power consumption of MMR. By analysis and simulations, we demonstrate that fast handoff scheme has the better performance than Basic NEMO.

SummaryWe investigate the problem of joint downlink wireless backhaul bandwidth (WBB) and power allocation in heterogeneous cellular networks (HCNs). A WBB partitioning scheme is considered, which allocates the whole bandwidth between the macrocell and small cells for data transmission and backhauling. We formulate an optimization problem to maximize the weighted sum logarithmic utility function by jointly optimizing WBB portion and fronthaul power allocation of each base station with consideration of the backhaul capacity limitation on each small cell. In order to solve this joint optimization problem, we propose a hierarchical two‐level approach and decompose the original problem into two independent subproblems: the WBB allocation at the macrocell base station (MBS) and the power allocation at both the MBS and small cell base stations (SBSs). Accordingly, the optimal WBB portion and power allocation solutions are obtained, respectively. Furthermore, we develop a distributed algorithm to implement the joint WBB and power allocation. Numerical results verify the effectiveness of the proposed approach and analyze the impact of the weighted coefficient and backhaul capacity limitation on the network performance. In addition, significant performance gains can be achieved by the proposed approach over the benchmark.

The progressive adaptability of today’s mobile communication services and the prompt progressions in the mobile phones industry have steered to a remarkable development in the wireless market capacity. Notwithstanding the incessant advancement in the radio access technologies to manage with that growth. However, many remaining challenges, i.e., inefficient allocation and management of wireless network resources in Heterogeneous Wireless Networks (HWNs) when using the modern cellular mobile communications radio access technologies such as Wireless Local Area Network (WLAN)/Wi-Fi, Long-TERA Evolution (LTE) and Fifth Generation (5G)) still continue and needs to be addressed. This problem emanates from the enormous number of users sharing these resources, random distribution of wireless channels, scarceness of the wireless spectral resources, and the dynamic behavior of generated traffic. Therefore, this paper solves the identified problem by designing an Efficient Resource Allocation (ERA) algorithm to address the inefficient allocation of available resources versus quality of service (QoS) challenges. The obtained simulation results demonstrate the effectiveness of the proposed model to meet the objectives subject to limitations and constraints compared to other published works. On average, the proposed ERA algorithm, Joint Power Bandwidth Allocation (JPBA) algorithm, and Dynamic Bandwidth Allocation (DBA) algorithm have shown 98.9%, 85%, 81% throughput performance, respectively at a time interval of 100s.

Heterogeneous wireless networks give rise to a multi-radio access environment which becomes crucial for load balancing to avoid network congestion and providing high quality services to maximize radio resource utilization. To this end, a joint power and bandwidth allocation with QoS support algorithm is proposed using convex optimization method in this letter. The algorithm achieves the goal of the total system capacity maximization, while efficiently satisfying the minimum rate constraint of delay-constraint service traffic and proportional fairness of best-effort service traffic. The simulation results show that the proposed algorithm significantly outperforms the existing scheme in QoS guarantee.