Publications

Sensor Integration to LTE/LTE-A Network through MC-CDMA and Relaying

In this paper, we propose a method to connect a group of wireless sensors to LTE/LTE-A system by using the cellular users as mobile relays, with the basic principle of maintaining the normal traffic between the cellular users and eNodeB during the sensor data collection. The cellular spectrum is re-used on sensor-to-mobile relay link without employing additional frequency resources. Multi- carrier CDMA methods are suspected to be utilized by sensor nodes, where data of each sensor is spread to the whole re-used cellular spectrum to create a low data rate transmission. In order to avoid additional complex receiver on cellular terminals, the simple amplify-and-forward relaying scheme is used at mobile relays. Since eNodeB can observe the cellular traffic components in the re-used spectrum exactly, it has the capability of canceling them in the received overlapped signals, and detecting the sensor data by using advanced multi-user detection methods. Finally, the end-to-end outage probability is analyzed and a closed-form approximation is derived. The numerical results show that the approximate closed-form equation is significant and that the proposed scheme can be used to collect sensor data in LTE/LTE-A networks.

A Low-Complexity Beamforming Design for Multiuser Wireless Energy Transfer

Wireless energy transfer (WET) is a green enabler of low-power Internet of Things (IoT). Therein, traditional optimization schemes relying on full channel state information (CSI) are often too costly to implement due to excessive energy consumption and high processing complexity. This letter proposes a simple, yet effective, energy beamforming scheme that allows a multi-antenna power beacon (PB) to fairly power a set of IoT devices by only relying on the first-order statistics of the channels. In addition to low complexity, the proposed scheme performs favorably as compared to benchmarking schemes and its performance improves as the number of PB's antennas increases. Finally, it is shown that further performance improvement can be achieved through proper angular rotations of the PB.

Towards Near-Field 3D Spot Beamfocusing: Possibilities, Challenges, and Use-cases

Spot beamfocusing (SBF) is the process of focusing the signal power in a small spot-like region in the 3D space, which can be either hard-tuned (HT) using traditional tools like lenses and mirrors or electronically reconfigured (ER) using modern large-scale intelligent surface phased arrays. ER-SBF can be a key enabling technology (KET) for the next-generation 6G wireless networks offering benefits to many future wireless application areas such as wireless communication and security, mid-range wireless chargers, medical and health, physics, etc. Although near-field HT-SBF and ER-beamfocusing have been studied in the literature and applied in the industry, there is no comprehensive study of different aspects of ER-SBF and its future applications, especially for nonoptical (mmWave, sub-THz, and THz) electromagnetic waves in the next generation wireless technology, which is the aim of this paper. The theoretical concepts behind ER-SBF, different antenna technologies for implementing ER-SBF, employing machine learning (ML)-based schemes for enabling channel-state-information (CSI)-independent ER-SBF, and different practical application areas that can benefit from ER-SBF will be explored.

Capacity and coverage in mixed traffic UMTS CDMA systems

This paper examines the related issues of capacity, coverage and power control in a multi-cell WCDMA network. The analysis is presented for the forward link. The analysis is based on extended models used for IS-95 systems which rely on Gaussian assumptions of interference. The analytical models presented and evaluated give an insight into the effects of varying traffic types, different allowances for signal to interference ratio (SIR) targets and mixed traffic.

On the Application of Network Slicing for 5G-V2X

Ultra-reliable vehicle-to-everything (V2X) communication is essential for enabling the next generation of intelligent vehicles. V2X communication refers to the exchange of information between vehicle and infrastructure (V2I) or between vehicles (V2V). Network slicing is one of the promising technologies for the next generation of connected devices, creating several logical networks on a common and programmable physical infrastructure. Following this idea, we propose a network slicing based communication model for vehicular networks. In this paper, we have modelled a multi-lane highway scenario with vehicles having heterogeneous traffic requirements. Autonomous driving slice (exchanges safety messages) and infotainment slice (provides video stream) are the two logical slices created on a common infrastructure. In addition, a relaying approach is utilized to improve the performance of low signal-to-interferenceplus-noise-ratio (SINR) video streaming vehicles. These low SINR vehicles are served by other infotainment vehicles, which have high quality V2V and V2I link and are not serving as autonomous driving slice access point. An extensive Long Term Evolution Advanced (LTE-A) system level simulator is used to evaluate the performance of the proposed method, in which it is shown that the proposed network slicing approach increases the packet reception ratio (PRR) from 31.15% to 99.47%.

Outage Probability and Capacity for Two-Tier Femtocell Networks by Approximating Ratio of Rayleigh and Log Normal Random Variables

This paper presents the derivation for per-tier outage probability of a randomly deployed femtocell network over an existing macrocell network. The channel characteristics of macro user and femto user are addressed by considering different propagation modeling for outdoor and indoor links. Location based outage probability analysis and capacity of the system with outage constraints are used to analyze the system performance. To obtain the simplified expressions, approximations of ratios of Rayleigh random variables (RVs), Rayleigh to log normal RVs and their weighted summations, are derived with the verifications using simulations.

On Spectrum Sharing Among Micro-Operators in 5G

The growing demand in indoor small cell networks has given rise to the concept of micro-operators (MOs) for local service delivery. We model and analyze a spectrum sharing system involving such MOs where a buyer MO buys multiple licensed subbands provided by the regulator. Also, all small cell base stations (SBSs) owned by a buyer MO can utilize multiple licensed subbands at the same time which are also used by other MOs. A deterministic model in which the location of the SBSs are known can lead to unwieldy problem formulation, when the number of SBSs is large. Subsequently, we adopt a stochastic geometric model of the SBS deployment instead of a deterministic model. Assuming that the locations of the SBSs can be modeled as a homogeneous Poisson point process, we find the downlink signal-to-interference-plus-noise ratio (SINR) coverage probability and average data rate for a typical user (UE) served by the buyer MO in a spectrum sharing environment. In order to satisfy the QoS constraint, we provide a greedy algorithm to find how many licensed subbands and which subband for the buyer MO to purchase from the regulator. We also derive the coverage probability of the buyer MO for interference the limited system.

Opportunistic Sleep Mode Strategies in Wireless Small Cell Networks

The design of energy-efficient mechanisms is one of the key challenges in emerging wireless small cell networks. In this paper, a novel approach for opportunistically switching ON/OFF base stations to improve the energy efficiency in wireless small cell networks is proposed. The proposed approach enables the small cell base stations to optimize their downlink performance while balancing the load among each another, while satisfying their users' quality-of-service requirements. The problem is formulated as a noncooperative game among the base stations that seek to minimize a cost function which captures the tradeoff between energy expenditure and load. To solve this game, a distributed learning algorithm is proposed using which the base stations autonomously choose their optimal transmission strategies. Simulation results show that the proposed approach yields significant performance gains in terms of reduced energy expenditures up to 23% and reduced load up to 40% compared to conventional approaches.

Copula-Based Analysis of Outage Probability: Assessing Redundancy for Improved Resiliency

A Cooperative Moving Relay Node System Deployment in a High Speed Train

In this paper we present system level simulation results for a cooperative moving relay node (MRN) system deployed on a high speed train (HST). Recently interest has grown in using MRNs to provide enhanced cellular coverage to users in public transport, particularly HSTs, of which the modern construction materials and techniques cause high vehicle penetration loss (VPL) when signals propagate into the train. MRNs utilising antenna arrays on the exterior and interior of the train are a promising solution to overcoming this VPL in order to provide onboard users with improved service. We show that a cooperative system of 8 MRNs onboard a HST is able to provide significant improvements to achievable throughput of onboard users when compared to direct transmission, as well as indirectly improving the throughput of other users located in cells the HST is passing through.

Dynamic clustering and sleep mode strategies for small cell networks

In this paper, a novel cluster-based approach for optimizing the energy efficiency of wireless small cell networks is proposed. A dynamic mechanism based on the spectral clustering technique is proposed to dynamically form clusters of small cell base stations. Such clustering enables intra-cluster coordination among the base stations for optimizing the downlink performance through load balancing, while satisfying users' quality-of-service requirements. In the proposed approach, the clusters use an opportunistic base station sleep-wake switching mechanism to strike a balance between delay and energy consumption. The inter-cluster interference affects the performance of the clusters and their choices of active or sleep state. Due to the lack of inter-cluster communications, the clusters have to compete with each other to make decisions on improving the energy efficiency. This competition is formulated as a noncooperative game among the clusters that seek to minimize a cost function which captures the tradeoff between energy expenditure and load. To solve this game, a distributed learning algorithm is proposed using which the clusters autonomously choose their optimal transmission strategies. Simulation results show that the proposed approach yields significant performance gains in terms of reduced energy expenditures up to 40% and reduced load up to 23% compared to conventional approaches.

Learning-based Caching in Cloud-Aided Wireless Networks

This paper studies content caching in cloud-aided wireless networks where small cell base stations with limited storage are connected to the cloud via limited capacity fronthaul links. By formulating a utility (inverse of service delay) maximization problem, we propose a cache update algorithm based on spatio-temporal traffic demands. To account for the large number of contents, we propose a content clustering algorithm to group similar contents. Subsequently, with the aid of regret learning at small cell base stations and the cloud, each base station caches contents based on the learned content popularity subject to its storage constraints. The performance of the proposed caching algorithm is evaluated for sparse and dense environments while investigating the tradeoff between global and local class popularity. Simulation results show 15% and 40% gains in the proposed method compared to various baselines.

Unreachability problem in mobile ad hoc networks: A medium access control perspective

A medium access control (MAC) protocol to address the so-called unreachability problem in mobile ad hoc networks is proposed. Stations maintain double hop neighborhood graphs and exchange designated eMAC tables to share their knowledge about their neighborhood topology. An adaptive table broadcasting technique to facilitate topology information dissemination in mobile ad hoc networks is also proposed. Performance of the proposed schemes is evaluated and compared with earlier schemes through simulations. Our results show performance enhancement due to better handling of unreachability, possible heterogeneous power distributions among contending stations, and mobility issues.

Maximization of worst-case weighted sum-rate for MISO downlink systems with channel uncertainty

The problem of robust weighted sum-rate maximization (WSRMax) in multicell downlink multi-input single-output systems is considered. We assume that the channel state information (CSI) of all users is imperfectly known at the base stations. The problem is known to be NP-hard even in the case of perfect CSI. Assuming a bounded ellipsoidal model for the CSI errors, we maximize the worst-case weighted sum-rate and proposed a fast but possibly suboptimal algorithm. The proposed algorithm is based on alternating optimization technique and sequential convex programming. Numerical results show that the convergence speed of the proposed algorithm is fast, and it finds a close-to-optimal solution in only a few iterations.

High PAPR Sequence Scrambling for Reducing OFDM Peak-to-Average Power Ratio

An Initial Access Optimization Algorithm for millimeter Wave 5G NR Networks

The millimeter wave (mmWave) communication uses directional antennas. Hence, achieving fine alignment of transmit and receive beams at the initial access phase is quite challenging and time-consuming. In this paper, we provide a dynamic-weight based beam sweeping direction and synchronization signal block (SSB) allocation algorithm to optimize the cell search of the initial access in mmWave 5G NR networks. The number of SSBs transmitted in each beam sweeping direction depends on previously learned experience which is based on the number of detected UEs (user equipment) per SSB for each sweeping direction. Overall, numerical simulation results indicate that the proposed algorithm is shown to be capable of detecting more users with a lower misdetection probability. Furthermore, it is possible to achieve the same performance with a smaller number of dynamic resource (i.e., SSB) allocation, compared to constant resource allocation.

Six Key Enablers for Machine Type Communication in 6G.

While 5G is being rolled out in different parts of the globe, few research groups around the world $-$ such as the Finnish 6G Flagship program $-$ have already started posing the question: \textit{What will 6G be?} The 6G vision is a data-driven society, enabled by near instant unlimited wireless connectivity. Driven by impetus to provide vertical-specific wireless network solutions, machine type communication encompassing both its mission critical and massive connectivity aspects is foreseen to be an important cornerstone of 6G development. This article presents an over-arching vision for machine type communication in 6G. In this regard, some relevant performance indicators are first anticipated, followed by a presentation of six key enabling technologies.

Modeling and analysis of handover failure probability in small cell networks

Mobility management in small cell networks is of utmost importance, and is currently under study in 3GPP Release-12. In this article, we model and analyze the outbound handover failure probability in small cell networks, in which a given user crosses its serving cell coverage border before his time-to-trigger elapses, without connecting to his target base station. Using tools from stochastic geometry, a closed-form expression of the handover link failure probability is characterized, as a function of shadowed channel fading, hysteresis margin, time-to-trigger, users' velocity and traveled distances. Numerical results show the effectiveness of the proposed analytical model and provide key insights into the problem of mobility management.