Meryem Simsek

When cellular meets WiFi in wireless small cell networks

The deployment of small cell base stations, SCBSs, overlaid on existing macrocellular systems is seen as a key solution for offloading traffic, optimizing coverage, and boosting the capacity of future cellular wireless systems. The next generation of SCBSs is envisioned to be multimode (i.e., capable of transmitting simultaneously on both licensed and unlicensed bands). This constitutes a cost-effective integration of both WiFi and cellular radio access technologies that can efficiently cope with peak wireless data traffic and heterogeneous quality of service requirements. To leverage the advantage of such multimode SCBSs, we discuss the novel proposed paradigm of cross-system learning by means of which SCBSs self-organize and autonomously steer their traffic flows across different RATs. Cross-system learning allows the SCBSs to leverage the advantage of both the WiFi and cellular worlds. For example, the SCBSs can offload delay-tolerant data traffic to WiFi, while simultaneously learning the probability distribution function of their transmission strategy over the licensed cellular band. This article first introduces the basic building blocks of cross-system learning and then provides preliminary performance evaluation in a Long-Term Evolution simulator overlaid with WiFi hotspots. Remarkably, it is shown that the proposed cross-system learning approach significantly outperforms a number of benchmark traffic steering policies.

5G-Enabled Tactile Internet

The long-term ambition of the Tactile Internet is to enable a democratization of skill, and how it is being delivered globally. An integral part of this is to be able to transmit touch in perceived real-time, which is enabled by suitable robotics and haptics equipment at the edges, along with an unprecedented communications network. The fifth generation (5G) mobile communications systems will underpin this emerging Internet at the wireless edge. This paper presents the most important technology concepts, which lay at the intersection of the larger Tactile Internet and the emerging 5G systems. The paper outlines the key technical requirements and architectural approaches for the Tactile Internet, pertaining to wireless access protocols, radio resource management aspects, next generation core networking capabilities, edge-cloud, and edge-AI capabilities. The paper also highlights the economic impact of the Tactile Internet as well as a major shift in business models for the traditional telecommunications ecosystem.

Latency Critical IoT Applications in 5G: Perspective on the Design of Radio Interface and Network Architecture

Next generation mobile networks not only envision enhancing the traditional MBB use case but also aim to meet the requirements of new use cases, such as the IoT. This article focuses on latency critical IoT applications and analyzes their requirements. We discuss the design challenges and propose solutions for the radio interface and network architecture to fulfill these requirements, which mainly benefit from flexibility and service-centric approaches. The article also discusses new business opportunities through IoT connectivity enabled by future networks.

An LTE-femtocell dynamic system level simulator

A dynamic system level simulator for LTE networks was developed for investigating the interference behaviour of femtocells placed within macrocells. We simulate a multi-cell, multi-user and multi-carrier system in the downlink for Single-Input, Single-Output (SISO) and Multiple-Input, Multiple-Output (MIMO) antenna configurations.

Dynamic Inter-Cell Interference Coordination in HetNets: A reinforcement learning approach

In this paper, we investigate enhanced Inter-Cell Interference Coordination (e-ICIC) techniques for Heterogeneous Networks (HetNets), consisting of a mix of macro and picocells. We model this strategic coexistence as a multi-agent system in which decentralized interference management and cell association strategies inspired from Reinforcement Learning (RL) are devised. Specifically, we focus on time and frequency domain ICIC techniques in which picocells optimally learn their cell range bias and downlink transmit power allocation. In turn, the macrocell optimizes its transmission by serving its own users while adhering to the picocell interference constraint. To substantiate our theoretical findings, system level simulations are carried out in which our proposed solution is compared with a number of existing ICIC approaches, such as resource partitioning, fixed cell range expansion (CRE) and fixed Almost Blank Subframe (ABS). Interestingly, our proposed solution is shown to yield substantial gains of up to 125% compared to static ICIC approaches.

Learning Based Frequency- and Time-Domain Inter-Cell Interference Coordination in HetNets

In this paper, we focus on inter-cell interference coordination (ICIC) techniques in heterogeneous network (HetNet) deployments, whereby macro- and picocells autonomously optimize their downlink transmissions with loose coordination. We model this strategic coexistence as a multi-agent system, aiming at joint interference management and cell association. Using tools from Reinforcement Learning (RL), agents (i.e., macro- and picocells) sense their environment and self-adapt based on local information to maximize their network performance. Specifically, we explore both time- and frequency domain ICIC scenarios and propose a two-level RL formulation. Here, picocells learn their optimal cell range expansion (CRE) bias and transmit power allocation, as well as appropriate frequency bands for multi-flow transmissions, in which a user equipment (UE) can be simultaneously served by two or more base stations (BSs) from macro- and pico-layers. To substantiate our theoretical findings, Long-Term Evolution Advanced (LTE-A) based system-level simulations are carried out in which our proposed approaches are compared with a number of baseline approaches, such as resource partitioning (RP), static CRE, and single-flow Carrier Aggregation (CA). Our proposed solutions yield substantial gains up to 125% compared to static ICIC approaches in terms of average UE throughput in the time domain. In the frequency domain, our proposed solutions yield gains up to 240% in terms of cell-edge UE throughput.

Mobility Modeling and Performance Evaluation of Multi-Connectivity in 5G Intra-Frequency Networks

Ultra-high reliable communication and improved capacity are some of the major requirements of the 5th generation (5G) mobile and wireless networks. Achieving the aforementioned requirements necessitates avoiding radio link failures and the service interruption that occurs during the failures and their re-establishment procedures. Moreover, the latency associated with packet forwarding in classical handover procedures should be resolved. This paper proposes a multi-connectivity concept for a cloud radio access network as a solution for mobility related link failures and throughput degradation of cell-edge users. The concept relies on the fact that the transmissions from co-operating cells are co-ordinated for both data and control signals. Latency incurred due to classical handover procedures will be inherently resolved in the proposed multi-connectivity scheme. Simulation results are shown for a stand alone ultra dense small cells that use the same carrier frequency. It is shown that the number of mobility failures can considerably be decreased without a loss in the throughput performance gain of cell-edge users.

Achieving high availability in wireless networks by an optimal number of Rayleigh-fading links

Future cellular networks have to meet enormous, unprecedented, and multifaceted requirements, such as high availability and low latency, in order to provide service to new applications in, e.g., vehicular communication, smart grids, and industrial automation. Such applications often demand a temporal availability of six nines or higher. In this work, we investigate how high availability can be achieved in wireless networks. To elaborate, we focus on the joint availability of power-controlled Rayleigh-fading links while using selection combining. By applying a basic availability model for uncorrelated links, we determine whether it is more efficient in terms of power to utilize multiple links in parallel rather than boosting the power of a stand-alone link. The results reveal that, for high availability, it can actually be beneficial to use multiple links in parallel. For instance, an availability of 1-1012 is achieved with 100 dB less power when power is shared among multiple links. Depending upon the availability desired, an optimal number of parallel links in terms of power consumption exists. Additionally, we extend the availability model to correlated links and investigate the performance degradation due to correlation.

Analysis of Handover Failures in Heterogeneous Networks With Fading

The handover process is one of the most critical functions in a cellular network and is in charge of maintaining seamless connectivity of user equipments across multiple cells. The handover process is driven by signal measurements from the neighboring base stations (BSs), and it is adversely affected by the time and frequency selectivity of the radio propagation channel. In this paper, we introduce a new model for analyzing handover performance in heterogeneous networks (HetNets) as a function of vehicular user velocity, cell size, and mobility management parameters. In order to investigate the impact of shadowing and fading on handover performance, we extract relevant statistics obtained from a Third-Generation Partnership Project (3GPP)-compliant HetNet simulator, and subsequently, we integrate these statistics into our analytical model to analyze both handover failure and ping-pong probabilities under fluctuating channel conditions. Computer simulations validate the analytical findings, which show that fading can significantly degrade the handover performance in HetNets with vehicular users.

SINR Model With Best Server Association for High Availability Studies of Wireless Networks

The signal-to-interference-and-noise ratio (SINR) is of key importance for the analysis and design of wireless networks. For addressing new requirements imposed on wireless communication, in particular high availability, a highly accurate modeling of the SINR is needed. We propose a stochastic model of the SINR distribution where shadow fading is characterized by random variables. Therein, the impact of shadow fading on the user association is incorporated by modification of the distributions involved. The SINR model is capable of describing all parts of the SINR distribution in detail, especially the left tail, which is of interest for studies of high availability.