Kinda Khawam

A Network-Assisted Approach for RAT Selection in Heterogeneous Cellular Networks

When several radio access technologies (e.g., HSPA, LTE, WiFi, and WiMAX) cover the same region, deciding to which one mobiles connect is known as the Radio Access Technology (RAT) selection problem. To reduce network signaling and processing load, decisions are generally delegated to mobile users. Mobile users aim to selfishly maximize their utility. However, as they do not cooperate, their decisions may lead to performance inefficiency. In this paper, to overcome this limitation, we propose a network-assisted approach. The network provides information for the mobiles to make more accurate decisions. By appropriately tuning network information, user decisions are globally expected to meet operator objectives, avoiding undesirable network states. Deriving network information is formulated as a semi-Markov decision process (SMDP), and optimal policies are computed using the Policy Iteration algorithm. Also, and since network parameters may not be easily obtained, a reinforcement learning approach is introduced to derive what to signal to mobiles. The performances of optimal, learning-based, and heuristic policies, such as blocking probability and average throughput, are analyzed. When tuning thresholds are pertinently set, our heuristic achieves performance very close to the optimal solution. Moreover, although it provides lower performance, our learning-based algorithm has the crucial advantage of requiring no prior parameterization.

Network-Centric Joint Radio Resource Policy in Heterogeneous WiMAX-UMTS Networks for Streaming and Elastic traffic

The convergence of wireless networks is a key solution to deal with the ever-increasing need for bandwidth. In this compound radio environment, users can use concurrently diverse services through multiple RATs. In this paper, we consider a heterogeneous network where cells include two co-localized Radio Access Technologies (RAT): WiMAX and UMTS. The predominance of these systems in nowadays mobile networks underlines the relevance of our choice. We consider the downlink channel for both RATs and two service classes: streaming and elastic traffic. We propose a Joint Radio Resource Management (JRRM) algorithm responsible of routing every arriving user to one of the two RATs, while taking into account the load of each RAT, the spatial distribution of already accepted users, the location of the newly admitted user, and its influence on global performance. In a study based on the Semi Markov Decision Process (SMDP) theory, we show how to obtain an optimal policy that maximizes a predefined reward function accounting for both the operator and user satisfaction. In fact, the reward function consists of a financial gain component, an aggregate throughput component and a blocking cost.

Individual vs. Global Radio Resource Management in a Hybrid Broadband Network

Nowadays, with the abundance of diverse air interfaces in the same operating area, advanced Radio Resource Management (RRM) is vital to take advantage of the available system resources. In such a scenario, a mobile user will be able to connect concurrently to different wireless access networks. In this paper, we consider the downlink of a hybrid network with two broadband Radio Access Technologies (RAT): WiMAX and WiFi. Two approaches are proposed to load balance the traffic of every user between the two available RATs: an individual approach where mobile users selfishly strive to improve their performance and a global approach where resource allocation is made in a way to satisfy all mobile users. We devise for the individual approach a fully distributed resource management scheme portrayed as a non-cooperative game. We characterize the Nash equilibriums of the proposed RRM game and put forward a decentralized algorithm based on replicator dynamics to achieve those equilibriums. In the global approach, resources are assigned by the system in order to enhance global performances. For the two approaches, we show that after convergence, each user is connected to a single RAT which avoids costly traffic splitting between available RATs.

Congestion Games for Distributed Radio Access Selection in Broadband Networks

Nowadays networks are characterized by the abundance of diverse Radio Access Interfaces (RAI) in the same operating area. The various wireless interfaces can belong to the same Radio Access Technology or not. In such a scenario, a mobile user will be able to select selfishly one of the available radio interfaces in order to enhance its own performance. Therefore, the radio access selection policy is vital and must be designed astutely to avoid resource wastage. In this paper, the RAI selection process is apprehended as a congestion game which is a class of noncooperative games in which users share a common set of limited resources. The cost sustained by a given user depends upon the congestion impact inflected by other users sharing the same resource. Devising distributed resource sharing schemes that optimize user air interface selection depends crucially on the existence of Nash equilibria for the modelling congestion games. In this paper, we model the downlink access for three main broadband technologies (WiMAX, WiFi and 3.5G HSDPA) and study the existence of pure Nash equilibria for various multi-RAI scenarios involving those technologies.

Distributed heuristic algorithms for RAT selection in wireless heterogeneous networks

In wireless heterogeneous networks, one of the most challenging problems is Radio Access Technology (RAT) selection that must be designed to avoid resource wastage. In this paper we adopt a hybrid model for RAT selection where the system allocates the downlink traffic between two different technologies in order to enhance global performance. We study the case of an integrated hybrid Wireless Local Area Network environment where the challenge we face is the high computational complexity necessary to obtain the global optimal solution. Therefore, we propose four distributed heuristic algorithms for RAT selection, where two of them are based on the distance between the user and the access points (APs), namely, distance based and probabilistic distance based algorithms. While the two others schemes are based on the peak rate that each user receives from these APs (peak rate based and probabilistic peak rate based algorithms). Results show that the proposed algorithms give efficient results compared to the optimal one depending on the spatial users distribution. Moreover these algorithms have a low computational complexity which makes them more advantageous compared to the optimal scheme in presence of a large number of users.

A downlink power control heuristic algorithm for LTE networks

The recent development of mobile terminals, the proliferation of mobile applications and the increasing need for mobile data have led to a dense deployment of mobile networks. In this context, the Long Term Evolution (LTE) standard is adopted by a large number of mobile network operators. LTE uses Orthogonal Frequency Division Multiple Access (OFDMA) technique on the downlink of the radio interface along with frequency reuse-1 model. However, Inter-Cell Interference (ICI) and system power consumption will cause limitations in terms of mean user throughput and system performance. Indeed, several recent works focus on the minimization of ICI and power consumption in multi-user OFDMA networks. In this paper, we propose a distributed heuristic power control algorithm that aims at minimizing the total downlink power of an LTE system. We also study the impact of the power control algorithm on ICI and system performance. Simulation results show that the proposed algorithm largely reduces the downlink power consumption without degrading system performance. In addition, it increases the mean throughput for cell-edge users that are mainly affected by ICI problems.

Analytical framework for dimensioning hierarchical WiMax-WiFi networks

Providing diverse, ubiquitous and cost-effective broadband services is a foremost challenge for the telecommunication community. Fixed WiMAX or IEEE 802.16d is one of the most promising radio access technologies, providing high performance similar to wired xDSL systems, yet superior to that of current 3G mobile technologies. Numerous deployment concepts are foreseen for WiMAX networks. They are designed to cover isolated areas, thus embodying an appealing solution for cellular networks or wireless backhaul for WiFi access. The latter concept is of interest in this paper that puts forward an analytical model based on the economical aspects to dimension hierarchical WiMax-WiFi networks. The proposed model consists in replacing a finite number of nodes by an equivalent continuum. Its key feature lies in accounting for the effect of interference as well as for the physical layer and channel characteristics in an easy and straightforward manner. On the one hand, the model takes into consideration frequency planning and scheduling aspects; and on the other hand, it provides tractable formulae of the end-user mean capacity and coverage probability in order to properly dimension the hybrid network. Last but not least, the economical facet of network planning is considered to unravel the design trade-offs between maximizing the service provider profit and satisfying the end user requirements in terms of performance.

Radio access selection approaches in heterogeneous wireless networks

Along with the rapid growth of mobile broadband traffic, multiple radio access technologies (RATs) are being integrated and jointly managed. To optimize heterogeneous network performance, efficient Common Radio Resource Management (CRRM) mechanisms need to be defined. This paper tackles the access technology selection - a key CRRM functionality - and proposes a hybrid approach that combines benefits from both network-centric and user-centric methods. Network information, that is periodically broadcasted, assists mobile users in their decisions. By broadcasting appropriate decisional information, the network tries to globally control users decision in a way to meet operator objectives. On the other hand, mobiles also integrate their needs and preferences to select their access technology so as to maximize their own utility. In comparison with other RAT selection techniques, including network-centric, hybrid and user-centric methods, simulation results prove the efficiency of our hybrid approach in enhancing resource utilization and maximizing user satisfaction.

Joint power-delay minimization in green wireless access networks

Growing energy demands, the increasing depletion of traditional energy resources, together with the recent surge in mobile internet traffic, all call for green solutions to address the challenge of energy-efficient wireless access networks. In this paper, we consider possible power saving by reducing the number of active BSs and adjusting the transmit power of those that remain active while maintaining a satisfying service for all users in the network. We thus introduce a joint optimization problem that minimizes the network power consumption of the network and the sum of network user transmission delays. Our formulation allows us to investigate the tradeoff between power and delay by tuning the respective weighting factors. Moreover, to reduce the computational complexity of the optimal solution of our non-linear optimization problem, we convert it into a Mixed Integer Linear Programming (MILP) problem. We provide extensive simulations for various decision preferences such as power minimization, delay minimization and joint minimization of power and delay. The results we present show that we obtain power savings of up to 16% compared to legacy network models.

Fluid Model for Wireless Adhoc Networks

In this paper, we propose an analytical fluid model for adhoc wireless networks. Our fluid model consists in replacing a finite number of nodes by an equivalent continuum - characterized by a density of nodes - and disseminated in the network according to some distribution function. The key feature of our model is that it takes into account the effect of interference, the CSMA/CA mechanism and radio propagation aspects in an easy and straightforward way. We will give closed form formulae of the Mean Capacity per node and the Coverage Probability, along with an evaluation of the impact of nodes density, network size and carrier sense range on overall performance.