Afef Feki

Cell wilting and blossoming for energy efficiency

In this article, we consider the adoption of sleep modes for the base stations of a cellular access network, focusing on the design of base station sleep and wake-up transients.. We discuss the main issues arising with this approach, and we focus on the design of base station sleep and wake-up transients, also known as cell wilting and blossoming. The performance of the proposed procedures is evaluated in a realistic test scenario, and the results show that sleep and wake-up transients are short, lasting at most 30 seconds.

Autonomous Spectrum Sharing for Mixed LTE Femto and Macro Cells Deployments

We consider the problem of sharing spectrum between different base stations in an OFDM network where some cells have a small radius. Such scenarios will become increasingly common in fourth generation networks where the need for ubiquitous high-speed coverage will lead to an increased use of small cells as well as indoor femtocells. Our aim is to devise autonomous algorithms for small cells and femtocells to choose spectrum so that they can achieve high data rates without causing interference to users in the traditional macro cells. We present a number of algorithms that perform combinations of frequency and time sharing based on the channel conditions reported by the mobile users. Our schemes bear some resemblance to the traditional 802.11 MAC algorithms. However, they differ in the fact that they are able to use better information about channel conditions from the mobiles and they are allowed to adjust the amount of spectrum that they are using. We evaluate our schemes using a platform that combines a physical-layer ray-tracing tool for indoor and outdoor environments with an upper layer OFDM simulation tool. We believe that this type of simulation capability will become increasingly important as cellular networks target the provision of high-speed performance in dense urban environments. Our results suggest that user channel quality measurements can be used to set the level of sharing between femtocells and macrocells and that finding the correct level of sharing is important for optimal network performance.

Enhanced Resource Sharing Strategies for LTE Picocells with Heterogeneous Traffic Loads

In this paper, we address the problem of spectrum sharing for LTE pico cells (PCs) networks with heterogeneous traffic loads. Distributed mechanisms are designed to steer the PCs in selecting the most suitable resources so that the overall throughput is maximized. The goal is to respond to the real traffic needs, while ensuring users fairness. Dynamic Cooperative Algorithms (DCA) relying on information exchange between the PCs and Non Cooperative Algorithms (DNCA) relying only on local measurements are elaborated and compared through extensive simulations. Different propagation conditions and varied resource needs between the PCs are also considered. We demonstrate in this paper the performance gain brought by the cooperative solution comparing to the non cooperative one and we show the capability of the algorithm to dynamically adjust the allocated resources to the real traffic loads.

Autonomous resource allocation for dense LTE networks: A Multi Armed Bandit formulation

Resource allocation is an important prerequisite for the effective deployment of Pico Cells (PCs). This topic becomes even more challenging in the case of heterogeneous networks, where autonomous interference management mechanisms are necessary. In this article, we propose a resource sharing method inspired from the reinforcement learning theory and particularly the methods used to solve the Multi Armed Bandit (MAB) problem. The main goal resides in giving the ability for each cell to make its decision autonomously while dynamically taking into account the resource occupation of each surrounding cell. We set up the global framework for the MAB based resource allocation strategies in the case of total frequency overlapping PCs. The performances of the proposed method are evaluated in the case of Long Term Evolution (LTE) Pico Cells deployment and compared to static allocation schemes. The results demonstrate the efficiency of our method.

Self-Organized Resource Allocation for LTE Pico Cells: A Reinforcement Learning Approach

This articles proposes a smart resource sharing algorithm to manage interference in LTE networks. Relying on reinforcement learning theory, the proposed Cyclic Multi Armed Bandit (CMAB) algorithm steers each cell in the choice of the most suitable frequency band portions, in autonomous manner. Thanks to the traffic aware feature, the algorithm adapts as well to the real needs of the cell. Adding to that, a refinement of the decision function is proposed to speed up the convergence time. The proposed approach is tested in LTE compliant simulator and the results shows its efficiency compared to conventional static reuse schemes.

Autonomous spectrum sharing for unstructured cellular networks with femtocells

To fulfill the needs for high speed ubiquitous coverage, fourth generation networks give rise to dense deployments of short range cells, such as femtocells. Generally deployed in residential or business areas, they complement the macrocellular service, thanks to guaranteed indoor coverage and improved multimedia experience. However, the addition of user-installed femtocells along with macrocells in a shared spectrum band raises critical management issues for controlling interference. In this paper, we address the problem of spectrum resource selection by the femtocells. The aim is to devise autonomous mechanisms for femtocells to adjust their spectrum resources, without manual configuration, so that they achieve high data rates and generate no interference to traditional macrocells. In this work, we are mainly concerned with the performance of solutions that are compliant with standards like Long Term Evolution (LTE). Detailed performance analysis is provided thanks to a complete simulation platform combining a physical layer ray-tracing tool with an upper layer orthogonal frequency division multiple access (OFDMA) simulator. Our results suggest that user channel quality measurements can be used to set the level of sharing between femtocells and macrocells and that finding the correct level of sharing is important for optimal network performance.

Joint interference management and handover optimization in LTE small cells network

In this paper, we investigate the interaction between two major technical challenges for LTE small cells deployment, in order to face the explosive increase of the traffic growth. These challenges are 1-Inter-Cell Interference Management which becomes critical in dense deployment of small cells and 2-Mobility Management since the handover frequency between close-by cells increases considerably. These two features, often analyzed separately are intertwined. The main reason is that handover occurs in overlapping cellular areas, where interference level is the highest. In this paper, interference is managed by a decentralized approach based on Multi Armed Bandit solutions. Handover performances are evaluated thanks to standard Mobility Robustness Optimization counters. Thus, we evaluate the impact of inter-cell interference management on handover performances and we demonstrate through simulations that the optimal configuration of interference management shall jointly account for performances indicators directly impacted by the interference management mechanism performances like convergence duration and throughput but also for handover-related performance metrics.

Detection of synchronization signals in reuse-1 LTE networks

Robust time and frequency synchronization is an essential requirement for a successful cell search in cellular networks like LTE (Long Term Evolution). High level of co-channel interference experienced in spectrally efficient deployments (Frequency reuse-1) can adversely affect reliable detection of synchronization sequences. Different solutions for the detection of LTE Primary Synchronization Signals (P-SS) are proposed and evaluated in this paper. The global approach consisting in a matched filter or decorrelator based detection module, followed by a decisional entity exhibits good performance: very fast convergence and robustness to interference in different channel conditions. Simulations demonstrate satisfactory detection probabilities from 7dB Signal to Interference ratio. In addition, low complexity and capacity to adapt to any propagation conditions are further important advantages of the proposed solution.

On Queue-Aware Power Control in Interfering Wireless Links: Heavy Traffic Asymptotic Modelling and Application in QoS Provisioning

In this work, we address the problem of power allocation for interfering transmitter-receiver pairs so that the probability that each queue length exceeds a specified threshold is fixed at a desired value. One application is satisfying QoS requirements in a dense cellular network. We deal with this problem using heavy traffic approximation techniques which lead to an asymptotic model of a (controlled) stochastic differential equation. The proposed power control strategy consists of allocating most of the power according to the states of the channel and a smaller fraction according to the queue lengths, for which we find a closed-form expression. We first consider a scenario where all channel realizations and queue lengths are known instantaneously to every transmitter. Then, the algorithm is extended to the case where only local SINR feedback is available and when queue length information is shared with delays among the transmitters. These models and results are also extended to the case where the transmitters are equipped with multiple antennas. Finally, the applicability in practical system settings are discussed and simulation results are provided to illustrate the performance of the proposed method.

A heavy traffic approach for queue-aware power control in interfering wireless links

In this work, we address the problem of power allocation for interfering transmitter-receiver pairs so that the probability that each queue length exceeds a specified threshold is fixed at a desired value. One application is satisfying QoS requirements in a dense cellular network. We address this problem using heavy traffic approximation techniques which lead to an asymptotic model described by a (controlled) stochastic differential equation. The power control strategy consists in allocating most of the power according to the wireless channel state and a smaller fraction according to the queue lengths. Simulation results in a simple setting illustrate that the proposed control policy can yield desirable results in practical systems.