A 4-Dimensional Markov model for the evaluation of radio access technology selection strategies in multiservice scenarios

In order to support the conceptual development of Common Radio Resource Management (CRRM) algorithms, this paper provides an analytical approach to the performance evaluation of Radio Access Technology (RAT) selection procedures in a multi-RAT/multiservice environment. In particular, a 4-Dimensional (4D) Markovian model is devised so as to consider the allocation of voice and data services in a GERAN/UTRAN system. Through the analytical definition of well-established Key Performance Indicators (KPIs) we provide numerical results on the evaluation of a load balancing RAT allocation policy.Peer ReviewedPostprint (published version

Joint radio resource management based on the species competition model

For optimal radio resource utilization in heterogeneous wireless networks, Joint Radio Resource Management (JRRM) is required. In distributed JRRM, each radio each access network (RAN) adjusts network parameters to affect user's RAN selection, thereby indirectly implementing joint radio resource allocation. The mathematical method for instructing such adjustment is lacking. In this article, the relationship between different RANs is mapped into the competition between species in the well-known L-V model developed by ecologists. Based on this model, an adjustment algorithm of distributed joint radio resource allocation is proposed. The simulation results show that compared with no adjustment or over adjustment, our adjustment algorithm can: 1) obtain proper resource allocation; 2) guarantee network coexistence. ©2006 IEEE.published_or_final_versio

On Resource Allocation in Fading Multiple Access Channels - An Efficient Approximate Projection Approach

We consider the problem of rate and power allocation in a multiple-access channel. Our objective is to obtain rate and power allocation policies that maximize a general concave utility function of average transmission rates on the information theoretic capacity region of the multiple-access channel. Our policies does not require queue-length information. We consider several different scenarios. First, we address the utility maximization problem in a nonfading channel to obtain the optimal operating rates, and present an iterative gradient projection algorithm that uses approximate projection. By exploiting the polymatroid structure of the capacity region, we show that the approximate projection can be implemented in time polynomial in the number of users. Second, we consider resource allocation in a fading channel. Optimal rate and power allocation policies are presented for the case that power control is possible and channel statistics are available. For the case that transmission power is fixed and channel statistics are unknown, we propose a greedy rate allocation policy and provide bounds on the performance difference of this policy and the optimal policy in terms of channel variations and structure of the utility function. We present numerical results that demonstrate superior convergence rate performance for the greedy policy compared to queue-length based policies. In order to reduce the computational complexity of the greedy policy, we present approximate rate allocation policies which track the greedy policy within a certain neighborhood that is characterized in terms of the speed of fading.Comment: 32 pages, Submitted to IEEE Trans. on Information Theor

Multiple-RAT selection for reducing call blocking/dropping probability in cooperative heterogeneous wireless networks

There is an increasing demand for high bandwidth-consuming services such as real-time video and video streaming over wireless access networks. A single radio access technology (RAT) in a heterogeneous wireless network may not always have enough radio resource to admit high bandwidth-consuming calls, such as video calls. Existing joint call admission control (JCAC) algorithms designed for heterogeneous wireless networks block/drop an incoming call when none of the available individual RATs in the network has enough bandwidth to admit the incoming call. Consequently, video calls experience high call blocking/dropping probability in the network. However, some calls such as multi-layer coded (scalable) video can be transmitted/received over one or multiple RATs. This article proposes a JCAC algorithm that selects a single or multiple RATs for scalable video calls in heterogeneous wireless networks, depending on availability of radio resources in available RATs. Non scalable calls are always admitted into a single RAT by the algorithm. The aim of the proposed algorithm is to reduce call blocking/dropping probability for both scalable and non-scalable calls. An analytical model is developed for the proposed JCAC algorithm, and its performance is evaluated. Simulation results show that the proposed algorithm reduces call blocking/dropping probability in heterogeneous wireless networks

Guaranteed bit rate traffic prioritisation and isolation in multi-tenant radio access networks

©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Network slicing is a key feature of forthcoming 5G systems to facilitate the partitioning of the network into multiple logical networks customised according to different operation and application needs. Network slicing allows the materialisation of multi-tenant networks, in which the same infrastructure is shared among multiple communication providers, each one using a different slice. The support of multi-tenancy through slicing in the Radio Access Network (RAN) is particularly challenging because it involves the configuration and operation of multiple and diverse RAN behaviour over a common pool of radio resources while guaranteeing a certain Quality of Service (QoS) and isolation to each of the slices. This paper presents a Markovian approach to model different QoS aware Admission Control (AC) policies in a multi-tenant scenario with Guaranteed Bit Rate (GBR) services. From the analytical model, different metrics are defined to later analyse the effect of AC mechanisms on the performance achieved in various scenarios. Results show the impact of priorities for services of different tenants and isolation between tenants when different AC polices are adopted.Peer ReviewedPostprint (author's final draft

Optimality of binary power-control in a single cell via majorization

This paper considers the optimum single cell power-control maximizing the aggregate (uplink) communication rate of the cell when there are peak power constraints at mobile users, and a low-complexity data decoder (without successive decoding) at the base station. It is shown, via the theory of majorization, that the optimum power allocation is binary, which means links are either "on" or "off". By exploiting further structure of the optimum binary power allocation, a simple polynomial-time algorithm for finding the optimum transmission power allocation is proposed, together with a reduced complexity near-optimal heuristic algorithm. Sufficient conditions under which channel-state aware time-division-multiple-access (TDMA) maximizes the aggregate communication rate are established. Finally, a numerical study is performed to compare and contrast the performance achieved by the optimum binary power-control policy with other sub-optimum policies and the throughput capacity achievable via successive decoding. It is observed that two dominant modes of communication arise, wideband or TDMA, and that successive decoding achieves better sum-rates only under near-perfect interference cancellation efficiency.Comment: 24 pages, 11 figure