A Decision-Theoretic Approach to Resource Allocation in Wireless Multimedia Networks

The allocation of scarce spectral resources to support as many user applications as possible while maintaining reasonable quality of service is a fundamental problem in wireless communication. We argue that the problem is best formulated in terms of decision theory. We propose a scheme that takes decision-theoretic concerns (like preferences) into account and discuss the difficulties and subtleties involved in applying standard techniques from the theory of Markov Decision Processes (MDPs) in constructing an algorithm that is decision-theoretically optimal. As an example of the proposed framework, we construct such an algorithm under some simplifying assumptions. Additionally, we present analysis and simulation results that show that our algorithm meets its design goals. Finally, we investigate how far from optimal one well-known heuristic is. The main contribution of our results is in providing insight and guidance for the design of near-optimal admission-control policies.Comment: To appear, Dial M for Mobility, 200

A connection-level call admission control using genetic algorithm for MultiClass multimedia services in wireless networks

Call admission control in a wireless cell in a personal communication system (PCS) can be modeled as an M/M/C/C queuing system with m classes of users. Semi-Markov Decision Process (SMDP) can be used to optimize channel utilization with upper bounds on handoff blocking probabilities as Quality of Service constraints. However, this method is too time-consuming and therefore it fails when state space and action space are large. In this paper, we apply a genetic algorithm approach to address the situation when the SMDP approach fails. We code call admission control decisions as binary strings, where a value of “1” in the position i (i=1,…m) of a decision string stands for the decision of accepting a call in class-i; a value of “0” in the position i of the decision string stands for the decision of rejecting a call in class-i. The coded binary strings are feed into the genetic algorithm, and the resulting binary strings are founded to be near optimal call admission control decisions. Simulation results from the genetic algorithm are compared with the optimal solutions obtained from linear programming for the SMDP approach. The results reveal that the genetic algorithm approximates the optimal approach very well with less complexity

An Erlang multirate loss model supporting elastic traffic under the threshold policy

In this paper, we propose a multirate teletraffic loss model of a single link with certain bandwidth capacity that accommodates Poisson arriving calls, which can tolerate bandwidth compression (elastic traffic), under the threshold policy. When compression occurs, the service time of new and in-service calls increases. The threshold policy provides different QoS among service-classes by limiting the number of calls of a service-class up to a pre-defined threshold, which can be different for each service-class. Due to the bandwidth compression mechanism, the steady state probabilities in the proposed model do not have a product form solution. However, we approximate the model by a reversible Markov chain, and prove recursive formulas for the calculation of call blocking probabilities and link utilization. The accuracy of the proposed formulas is verified through simulation and found to be very satisfactory

Adaptive stochastic radio access selection scheme for cellular-WLAN heterogeneous communication systems

This study proposes a novel adaptive stochastic radio access selection scheme for mobile users in heterogeneous cellular-wireless local area network (WLAN) systems. In this scheme, a mobile user located in dual coverage area randomly selects WLAN with probability of ω when there is a need for downloading a chunk of data. The value of ω is optimised according to the status of both networks in terms of network load and signal quality of both cellular and WLAN networks. An analytical model based on continuous time Markov chain is proposed to optimise the value of ω and compute the performance of proposed scheme in terms of energy efficiency, throughput, and call blocking probability. Both analytical and simulation results demonstrate the superiority of the proposed scheme compared with the mainstream network selection schemes: namely, WLAN-first and load balancing

A directionally based bandwidth reservation scheme for call admission control

This paper proposes a new advanced Call Admission Control(CAC) strategy involving for the first time, a bandwidth reservation scheme that is influenced by the direction attribute of a mobile terminal (MT). Aside from the Quality-of-Service (QoS) parameters, the direction attribute plays a key role in efficiently reserving resources for MTs supporting multimedia communications for different QoS classes. The framework for a direction-based CAC system is entirely distributed and may be viewed as a message passing system, where MTs inform their neighbouring base stations (BS) not only of their QoS requirements, but also of their mobility parameters. The base stations then predict future demand and reserve resources accordingly, only admitting those terminals that can be adequately supported. The bandwidth reservation scheme proposed in this paper, integrates the direction attribute into the conventional Guard Channel (GC) scheme. Simulation results prove that this new scheme offers significant improvements in both Call Blocking Probability (CBP) and bandwidth utilization, under a variety of differing traffic conditions

Handover Management in Highly Dense Femtocellular Networks

For dense femtocells, intelligent integrated femtocell/macrocell network architecture, a neighbor cell list with a minimum number of femtocells, effective call admission control (CAC), and handover processes with proper signaling are the open research issues. An appropriate traffic model for the integrated femtocell/macrocell network is also not yet developed. In this paper, we present the major issue of mobility management for the integrated femtocell/macrocell network. We propose a novel algorithm to create a neighbor cell list with a minimum, but appropriate, number of cells for handover. We also propose detailed handover procedures and a novel traffic model for the integrated femtocell/macrocell network. The proposed CAC effectively handles various calls. The numerical and simulation results show the importance of the integrated femtocell/macrocell network and the performance improvement of the proposed schemes. Our proposed schemes for dense femtocells will be very effective for those in research and industry to implement