Semi-distributed radio resource management for elastic traffic in a hybrid network (original) (raw)
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Elastic Game Based Radio Resource Management
2012 IEEE 75th Vehicular Technology Conference (VTC Spring), 2012
With the abundance of diverse air interfaces in the same operating area, a mobile user is able to connect concurrently to different wireless access networks in order to meet more easily its target performance. In this paper, we consider the downlink of a multi-class hybrid network with two Radio Access Technologies (RAT): WiMAX [1] and WiFi [2]. We devise a distributed Radio Resource Management (RRM) scheme for elastic traffic that coexists with streaming traffic. The proposed scheduling policy is original in the sense that elastic users have a counterintuitive behaviour: they will try to occupy the least amount possible of bandwidth owing to their delay tolerance to accommodate QoS stringent streaming users. A non-cooperative submodular game is used to load balance the traffic of elastic users between the two available RATs aiming at minimizing their bandwidth consumption. We characterize the Nash Equilibriums (NE) of the resource management game and study the efficiency of a distributed algorithm based on best response dynamics to achieve those equilibriums. The game is played upon every new arrival and an admission control scheme is used to limit the number of ongoing connections so that admitted elastic flows are sustained with a guaranteed minimal rate.
2009
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.
A characterization of resource allocation in LTE systems aimed at game theoretical approaches
2010 15th IEEE International Workshop on Computer Aided Modeling, Analysis and Design of Communication Links and Networks (CAMAD), 2010
This paper proposes a novel approach, based on game theory, for radio resource allocation in the downlink of cellular networks using Orthogonal Frequency Division Multiple Access. The reference technology is the Long Term Evolution of the 3GPP UTRAN. The main contribution is to identify a model for the allocation objectives, and how to approach them in a tunable manner. The resource management issue is framed in the context of spectrum sharing, where multiple entities agree on utilizing the radio access channel simultaneously. A trade-off between sum-rate throughput and fairness among the users is identified and addressed through game theory, i.e., moving the operation of the system towards a stable Pareto efficient point. Such a methodology can be implemented with low complexity while ensuring logical modularity of the overall system. Numerical results are also shown, to exemplify the validity of the proposed approach.
Congestion Games for Distributed Radio Access Selection in Broadband Networks
2010
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.
Maximizing the capacity of mobile cellular networks with heterogeneous traffic q
We propose a novel adaptive reservation scheme that handles, in an integrated way, heterogeneous traffic of two types: streaming and elastic. The scheme adjusts the rates of streaming sessions to meet the QoS objective, adapting to any mix of traffic and enforcing a differentiated treatment among services, in both fixed and variable capacity systems. The resource utilization achieved by streaming traffic is close to the one obtained by an optimal policy, while the efficiency in the use of resources achieved by elastic traffic is greatly improved by limiting the abandonment probability. The performance evaluation carried out verifies that the QoS objective is met with an excellent precision and that the scheme converges rapidly to new operating conditions. We also compare the new adaptive scheme with two previous ones verifying that ours performs better in terms of carried traffic and convergence rate. The proposed scheme has low complexity which makes it practical for real cellular networks.
Stackelberg game for heterogeneous traffics management in next‐generation cellular network
IET Communications, 2021
The innovations in the internet of things and the advent of media-intensive applications have massively increased the data burden on third-and fourth-generation (wireless cellular technology) mobile networks. The existing cellular networks face an overloading issue due to the growing rate of data traffics resultantly reducing the quality of service (QoS) in terms of delay and throughput. To overcome this issue, mobile network operators are searching for well-organized ways to support such a massive data flow. Mobile data offloading schemes through small cells such as WiFi can be implemented to provide a lucrative and effective solution. A game-based quality of service model for heterogeneous traffic to achieve the quality of service parameters is proposed. This model deals with a trade-off between mobile network operators and access points, allocating economic incentives by mobile network operators to acess points for saving the spectrum. The model is simulated in MATLAB and the preliminary analyses proved the intense impact of the model on the offloading ratio and energy consumption by achieving superior results in the aforementioned parameters.
Maximizing the capacity of mobile cellular networks with heterogeneous traffic
Computer Networks, 2009
We propose a novel adaptive reservation scheme that handles, in an integrated way, heterogeneous traffic of two types: streaming and elastic. The scheme adjusts the rates of streaming sessions to meet the QoS objective, adapting to any mix of traffic and enforcing a differentiated treatment among services, in both fixed and variable capacity systems. The resource utilization achieved by streaming traffic is close to the one obtained by an optimal policy, while the efficiency in the use of resources achieved by elastic traffic is greatly improved by limiting the abandonment probability. The performance evaluation carried out verifies that the QoS objective is met with an excellent precision and that the scheme converges rapidly to new operating conditions. We also compare the new adaptive scheme with two previous ones verifying that ours performs better in terms of carried traffic and convergence rate. The proposed scheme has low complexity which makes it practical for real cellular networks.
HYBRID TRAFFIC ALLOCATION USING APPLICATION-AWARE ALLOCATION OF RESOURCES IN CELLULAR NETWORKS
SHODHSAMHITA, 2021
In current cellular networks, the data created by delay-tolerant and real-time applications, which includes elastic and inelastic data, together constitute the vast majority of the traffic. systems that help handle and adapt to applications' varying needs for resources, networks' intelligence about application traffic, and networks' ability to handle temporal variations in application traffic are critical to realizing optimal resource assignment for these concerns and thus to improving the overall Quality-of-Experience (QoE). The focus of the research in question is on establishing a convex proportional equity resource allocation approach for cognitive cellular systems capable of thinking about traffic patterns, which exist throughout time and how priority levels may be accommodated. Conceptually similar and decentralized central and distributed formulas are established, together with algorithms for solution and convergence. The centralization strategy has been shown to have reduced overhead transmission, with upper limitations on it, for the centralized and dispersed approaches. This report describes the varying bidding situations, based on the dynamic nature of the system, with regards to changes in the amount and usage of user equipment (UEs).
Novel user centric, game theory based bandwidth allocation mechanism in WiMAX
Human-centric Computing and Information Sciences, 2013
Bandwidth allocation plays a crucial role in ensuring overall quality of service in WiMAX. WiMAX supports non-contention based bandwidth allocation mechanism, where the responsibility of bandwidth allocation lies with the base station. In this paper, a novel user- centric, Game Theory-based bandwidth allocation algorithm is proposed. The Users/Mobile Station shall be grouped in pairs and bandwidth allocation is performed alternately between the two users of a group. In any given frame only one user from a pair is allocated bandwidth. The bandwidth thus allocated shall satisfy the requirements of the user/mobile station for two consecutive frames. Since, in any given frame, only one user/MS is allocated the bandwidth, the proposed algorithm reduces the frame overhead, thereby saving precious bandwidth that can be utilized to improve throughput. Simulation results show a 50% decrease in the uplink frame overhead and about 8% improvement in the uplink throughput per user/mobile station.