Heterogeneous cellular networks performance is usually analysed by taking several Key Performance Indicators (KPIs) into account, their proper balance being required in order to guarantee a desired Quality of Service (QoS). An approach to simplify and integrate a set of KPIs into a single one is presented, by using the proposed Cost Function model that includes these KPIs, providing a single evaluation parameter as output, and reflecting network conditions and Common Radio Resource Management (CRRM) strategies performance. This paper proposes a Cost Function that enables the implementation of different CRRM algorithms and policies, by manipulating KPIs according to user's or operator's perspectives, allowing for a better QoS. Results show that different policies can in fact be established, with a different impact on the network, e.g., with median values ranging by a factor higher than two.

A Cost Function Model for CRRM over Heterogeneous Wireless Networks

This PhD study aims to investigate techniques for efficient usage of spectrum for next generation mobile communication networks. The Long Term Evolution (LTE) and LTEAdvanced (LTE-A) systems are taken as case studies. The LTE is under development within 3rd Generation Partnership Project (3GPP) and heading towards its final phase of standardization. The LTE aims for reduced latency, higher user data rates, improved system capacity and coverage, and reduced cost for the operators. Currently the International Telecommunications Union (ITU) is working on specifying the system requirements towards next generation mobile communication systems called International Mobile Telecommunications-Advanced (IMT-A). The 3GPP aims to further evolve LTE towards LTE-A in order to meet or exceed the IMT-A requirements as well as its own requirements for advancing LTE for long term competitiveness. The first half of the PhD study is mainly concerned with LTE, with the main focus on higher order sectorization and inter-cell interference avoidance to improve system capacity and coverage. Typically three antennas are considered rendering 3 sector site deployments for LTE. A migration to 6 sector site deployment has been investigated. A mixed network topology composed of a combination of 3 and 6 sectors site deployment is also proposed. The mixed network topology is found to provide significantly high performance gains in terms of cell throughput and user outage throughput performance, and therefore recommended as a potential solution to meet high traffic demands in localized areas such as hot spots. LTE uses Orthogonal Frequency Division Multiple Access (OFDMA) in the downlink with universal frequency reuse. Due to the characteristics of OFDMA, the intra-cell interference is ideally avoided , but the environment still remains interference limited due to the presence of inter-cell interference. Our focus in this study is on development of schemes for inter-cell interference avoidance under fractional load conditions. The fractional load conditions arise when all the resources are not required to be used due to lack of traffic in the cell. We propose several autonomous inter-cell interference avoidance schemes, which do not require inter-cell signaling and provide significant improvements in cell throughput and user outage throughput performance. The second half of the study is concerned with LTE-A, which aims to provide peak data rates in the order of 1 Gbps in downlink and 500 Mbps in uplink for the nomadic local area/indoor deployment scenarios. Such high data rates may require high spectral efficiency and a wide bandwidth spectrum allocation in the order of 100 MHz. Such high bandwidth allocation may require sharing of spectrum among operators in a flexible manner. Currently, Home e-nodeB (HeNB) is emerging as a potential solution to provide high data rate high quality indoor coverage. Potentially large scale uncoordinated deployment of HeNBs, sharing over the same

Techniques for Efficient Spectrum Usage for Next Generation Mobile Communication Networks. An LTE and LTE-A Case Study

A communication system comprises a configuration manager (119) which includes an optimizer (203) for performing a Radio Access Network (RAN) optimization process. An optimization characteristic for the RAN optimization process and operational data for a plurality of remote terminals is determined, and based on this information a grouping processor (209) determines a plurality of groups of remote terminals. A policy processor (211) determines an operational policy for each of the groups in response to the optimization characteristic and the operational data and a policy distributor (213) transmits the operational policy of each group to at least the remote terminals in the group. Each remote terminal then continues to operate in accordance with the operational policy of the group to which the remote terminal belongs. The invention may typically allow improved performance and specifically may allow operation to be adapted to the specific optimization processes being performed. The invention is suitable for a heterogeneous communication system.

Optimization in a communication system

This paper presents the results of the development of a handset based automatic network reselection software system, which allows keeping end-to-end connections through semi-transparent handoff on WiFi/GSM-GPRS networks.A description of the developed system's software architecture is given, as well as of the components implemented for it, their functionalities and flow of control, all of which allow the permanent discovery of available networks for the mobile device, their evaluation, selection and switching to the network which offers the best ratings in its performance and operational profile, taking into account the preferences previously configured by the user. The system was developed in Java and C# for different operating systems (WinXP, WinMobile and Linux), and its interoperability has been tested in them. Some of the test scenarios are described and final comments about the tests results are given.

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Handset based automatic network re-selection system for GSM/GPRS and WiFi

This paper presents a policy-based radio resource management model for decision sharing between the network and the mobile terminals in composite networks. One of the key issues discussed in this paper is the distribution of RRM decision making between the network and the mobile terminal. IEEE P1900.4 standard project proposes a policy-based radio resource usage scheme where the network orients the mobile terminals decisions by sending rules and constraints. Mobile terminals choose the most appropriate action to their own QoS objectives, within the action set allowed by the network. We propose a joint RRM framework based on this standard project and we discuss both policies definition on the network side and decision making on the mobile terminal side. We propose a model where policies are chosen automatically according to the variations of the environment conditions and the operator strategy. On the mobile terminal side, we propose to introduce a time constraint imposed by the network for policy execution in order to coordinate the resulting terminals' actions execution over time. Moreover, as final decisions are made by MTs in a distributed way, we discuss the modeling of this problem using cooperative and non cooperative games approaches.

Optimal Decision Making Distribution in Composite Networks

This paper presents a policy-based radio resource management model for decision sharing between the network and the mobile terminals in the context of composite networks. One of the key issues discussed in this paper is the distribution of Radio Resource Management (RRM) decision making between the network and the mobile terminal. IEEE P1900.4 standard project proposes a policy-based radio resource usage scheme, where the decision-making is shared between the network and the mobile terminals. The network orients the mobile terminals decisions by sending rules and constraints. Mobile terminals choose the most appropriate action to their own Quality of service (QoS) objectives, within the action set allowed by the network. We define detailed scenarios illustrating this model. In addition, we propose a model where policies are chosen automatically act aiding to the variations of the environment conditions and the operator strategy. For this purpose, we define a policy database that stores the different environment configurations matched with the appropriate policies. Environment configurations are first classified. Then for each environment class an optimization algorithm finds the policy that fits the operator objectives.

P. Houze

Papers

Policy based RRM for network-terminal decision sharing