Publications

Feasibility Studies on the Use of Higher Frequency Bands and Beamforming Selection Scheme for High Speed Train Communication

With increasing popularity of high speed trains and traffic forecast for future cellular networks, the need to provide improved data rates using higher frequency bands (HFBs) for train passengers is becoming crucial. In this paper, we modify the OFDM frame structure for HST, taking into account the increasing sensitivity to speed at HFBs. A lower bound on the SNR/SINR for a given rate for reliable communication was derived considering the physical layer parameters from the OFDM frame. We also analyze different pathloss models in the context of examining the required gain needed to achieve the same performance as with microwave bands. Finally, we present a time-based analogue beamforming selection approach for HST. We observed that, irrespective of the pathloss models used, the required gains are within the same range. For the same SNR/SINR at different frequency bands, the achievable data rate varies with respect to the frequency bands. Our results show the potential of the use of HFBs. However, due to the increased sensitivity of some channel parameters, a maximum frequency band of 38 GHz is suggested. Evaluation of our proposed beamforming scheme indicates a close performance to the optimal SVD scheme with a marginal rate gap of less than 2 b/s/Hz.

Performance Analysis of Two-Way Relay System with Antenna Correlation

This paper investigates the performance of amplify-and-forward (AF) two-way relay system with antenna correlation. Overall outage probability (OOP), average symbol error rate (SER) and ergodic capacity are analyzed. By considering general correlation structure with arbitrary eigenvalue distribution, we derive a tight lower bound for OOP and use it to evaluate average SER and ergodic capacity. Moreover, the system is studied in high signal-to-noise ratio (SNR) to obtain the insightful behavior of the performance and diversity gain. Finally Monte Carlo simulations are conducted to verify the accuracy of the results.

Hierarchical Bayesian-based Indoor Positioning Using Distributed Antenna Systems

This work proposes and evaluates hierarchical Bayesian-based localization methods to estimate the position of a target node in indoor deployment scenarios. The measurements are acquired through a distributed antenna system which is connected to a common master anchor node. Each antenna head is affected by different channels parameters, what makes the estimation more difficult. The proposed method combines received signal strength and time of flight measurements to estimate the target location. In our investigations, we also consider a one-level hierarchical Bayesian network model, which introduces conditional interdependencies to the model parameters, resulting in less susceptibility to local variations. The Markov Chain Monte Carlo sampling method is used to approximate the posterior distribution of the two-dimensional target's location coordinates. The root mean square error is used to evaluate the performance of the proposed solution in indoor scenarios. Our results show that by combining hybrid measurements or increasing conditions between the parameters by a hierarchical approach, the proposed mechanisms outperform the classic Bayesian model when estimating the target node using even fewer measurements.

Energy efficient load sharing in LTE-A HetNets

This paper addresses energy efficiency and throughput performance of joint LTE-A macrocell and femtocell deployment. We consider two techniques discontinuous transmission (DTX) and offloading of users from macrocells to lower power femtocells. When the DTX is applied base stations delay transmissions until sufficient user data is available to transmit using 40 percent or more of the system bandwidth. This allows the base stations to remain inactive for larger periods of time, and therefore reducing energy consumption. The target is to reduce the overall network energy consumption per area with minimal impact to the throughput. The numerical results show that when the majority of macrocell users can be offloaded to be served by femtocells the mean power per area consumption will decrease by up to 34.7 percent and at the same time a larger portion of users are able to meet the intended throughput target. When DTX is applied energy consumption is reduced further still to 45.3 percent.

Energy efficient MIMO two-way relay system with physical layer network coding

We investigate error performance and an optimum power allocation scheme for multiple-input multiple-output (MIMO) channel physical layer network coding (PNC) based two-way relay system. Zero forcing precoding technique is used at source nodes to facilitate PNC operations at the relay node. First, system error performance is investigated by introducing upper and lower bounds for BPSK modulation system. They are validated with numerical results and bounds provide accurate results at high SNR regime. Then, we consider sum rate maximization under a total power constraint to obtain the optimum power allocation scheme. Analytical solutions are derived and compared with other possible schemes, which are suboptimal. Numerical results confirm that the power allocation scheme provides the optimal solution for the achievable sum rate with the total available power and the relay position.

Transmission strategies for full duplex multiuser MIMO systems

We introduce a full duplex multiuser multiple-input multiple-output (FD MU-MIMO) system, and consider the total throughput maximization problem under a sum power constraint in the downlink (DL) channel and per-user power constraints in the uplink (UL) channel. Due to the nature of asymmetric DL/UL capacity, a trivial method to this problem is to optimize the DL and UL channels sequentially. However, when the self-interference (SI) is large, the sum rate of the UL channel in this sequential design is dramatically degraded. Herein, a joint design is proposed, in which the DL and UL channels are optimized simultaneously. Since the objective function of the throughput maximization problem is non-convex, it is difficult to find the optimal solution. Thus, we propose a joint iterative algorithm to find a suboptimal design, using a local optimization strategy. Simulation results demonstrate that the iterative joint design outperforms the sequential design, and the FD MU-MIMO system is superior to the conventional half duplex (HD) system in terms of the total system throughput when the SI is sufficiently small. This makes the FD MU-MIMO techniques promising for small cell deployments where the transmit power is relatively small.

Energy Beamforming for RF Wireless Power Transfer with Dynamic Metasurface Antennas

Radio frequency (RF) wireless power transfer (WPT) is a promising technology for charging the Internet of Things. Practical RF-WPT systems usually require energy beamforming (EB), which can compensate for the severe propagation loss by directing beams toward the devices. The EB flexibility depends on the transmitter architecture, existing a trade-off between cost/complexity and degrees of freedom. Thus, simpler architectures such as dynamic metasurface antennas (DMAs) are gaining attention. Herein, we consider an RF-WPT system with a transmit DMA for meeting the energy harvesting requirements of multiple devices and formulate an optimization problem for the minimum-power design. First, we provide a mathematical model to capture the frequency-dependant signal propagation effect in the DMA architecture. Next, we propose a solution based on semi-definite programming and alternating optimization. Results show that a DMA-based structure can outperform a fully-digital implementation and that the required transmit power decreases with the antenna array size, while it increases and remains almost constant with frequency in DMA and FD, respectively.

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.

Tutorial on Joint Embedding Predictive Architectures (JEPA): Foundations, Applications, and Future Directions

Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks

In this paper, we study the problem of joint inband backhauling and interference mitigation in 5G heterogeneous networks (HetNets) in which a massive multiple-input multipleoutput (MIMO) macro cell base station equipped with a large number of antennas, overlaid with self-backhauled small cells is assumed. This problem is cast as a network utility maximization subject to wireless backhaul constraints. Due to the non-tractability of the problem, we first resort to random matrix theory to get a closed-form expression of the achievable rate and transmit power in the asymptotic regime, i.e., as the number of antennas and users grows large. Subsequently, leveraging the framework of stochastic optimization, the problem is decoupled into dynamic scheduling of macro cell users and backhaul provisioning of small cells as a function of interference and backhaul links. Via simulations, we evaluate the performance gains of our proposed framework under different network architectures and low/high frequency bands. Our proposed HetNet method achieves the achievable average UE throughput of 1.7 Gbps as well as ensures 1 Gbps cell-edge UE throughput when serving 200 UEs per km2 at 28 GHz with 1 GHz bandwidth. In ultra-dense network, the UE throughput at 28 GHz achieves 62x gain as compared to 2.4 GHz.

Finite Blocklength Error Probability Distribution for Designing Ultra Reliable Low Latency Systems

Future wireless systems are envisioned to support completely new use cases with extremely stringent requirements on both latency and reliability, e.g., Ultra-Reliable Low-Latency Communication. However, guaranteeing truly reliable services is quite challenging, much more under strict latency constraints. Notice that when it comes to reliability, the traditional approaches relying on average performance figures do not provide sufficient reliability guarantees. Instead, analyses/designs based on risk measures are more useful since they offer a more fine-grained probabilistic information of the system reliability. In this paper, we depart from novel information theory results on finite-blocklength (FB) coding, which characterize the error-latency trade-off under strict delay constraints, to highlight that the FB error probability is in fact a random variable in fading scenarios. Then, we provide accurate analytical approximations for the FB error probability distribution. This allows us to evaluate some well-known risk measures and, based on them, quantify the system reliability under strict latency constraints from different standpoints. We validate our results via simulation and provide numerical examples that illustrate, for instance, that two systems performing similar in terms of average reliability, may offer services with different risk perceptions.

Bit error probability analysis of linear receivers for CDMA systems

Bit error probability of linear receivers for multiuser communications is analysed. The results can be applied both for centralised multiuser or joint receivers as well as for decentralised single-user receivers. The analysis is presented for AWGN and known or perfectly estimated fading multipath channels. The analysis is also extended to the estimated fading multipath channel case with data-aided (DA) channel estimation. Two ways to approximate the averaging over the interfering data symbol combinations are considered and compared. One is a semi-analytic method, where only part of the interfering data symbol combinations are taken into consideration in the averaging. The other is the Gaussian approximation. In addition to MAI, the analysis directly incorporates the impact of the interpath interference (IPI) or inter symbol interference (ISI) to the receiver performance. Numerical examples are presented to demonstrate the usefulness of the method.

Delay trackers for multiuser CDMA receivers

Two types of coherent delay-locked loops (DLL) are considered in this paper as delay trackers in multiuser CDMA receivers. The first approach is based on the parallel interference cancellation (PIC) method. PIC based delay trackers require the estimation of channel parameters and data symbols of all users to construct the multiple-access interference (MAI) estimates. The other method is based on decision-directed single-user coherent DLLs. According to the numerical results, the PIC based DLL yields better steady state tracking performance at high SNRs, whereas the single-user coherent DLL performs better at low SNRs with reasonably low interference levels. The single-user DLL in a PIC based receiver is more robust against other user delay errors, which resulted in better transient state performance.

Beamforming and Waveform Optimization for RF Wireless Power Transfer with Beyond Diagonal Reconfigurable Intelligent Surfaces

Radio frequency (RF) wireless power transfer (WPT) is a promising technology to seamlessly charge low-power devices, but its low end-to-end power transfer efficiency remains a critical challenge. To address the latter, low-cost transmit/radiating architectures, e.g., based on reconfigurable intelligent surfaces (RISs), have shown great potential. Beyond diagonal (BD) RIS is a novel branch of RIS offering enhanced performance over traditional diagonal RIS (D-RIS) in wireless communications, but its potential gains in RF-WPT remain unexplored. Motivated by this, we analyze a BD-RIS-assisted single-antenna RF-WPT system to charge a single rectifier, and formulate a joint beamforming and multi-carrier waveform optimization problem aiming to maximize the harvested power. We propose two solutions relying on semi-definite programming for fully connected BD-RIS and an efficient low-complexity iterative method relying on successive convex approximation. Numerical results show that the proposed algorithms converge to a local optimum and that adding transmit sub-carriers or RIS elements improves the harvesting performance. We show that the transmit power budget impacts the relative power allocation among different sub-carriers depending on the rectifier's operating regime, while BD-RIS shapes the cascade channel differently for frequency-selective and flat scenarios. Finally, we verify by simulation that BD-RIS and D-RIS achieve the same performance under pure far-field line-of-sight conditions (in the absence of mutual coupling). Meanwhile, BD-RIS outperforms D-RIS as the non-line-of-sight components of the channel become dominant.

Modeling and Analysis of Content Caching in Wireless Small Cell Networks

Network densification with small cell base stations is a promising solution to satisfy future data traffic demands. However, increasing small cell base station density alone does not ensure better users quality-of-experience and incurs high operational expenditures. Therefore, content caching on different network elements has been proposed as a mean of offloading he backhaul by caching strategic contents at the network edge, thereby reducing latency. In this paper, we investigate cache-enabled small cells in which we model and characterize the outage probability, defined as the probability of not satisfying users requests over a given coverage area. We analytically derive a closed form expression of the outage probability as a function of signal-to-interference ratio, cache size, small cell base station density and threshold distance. By assuming the distribution of base stations as a Poisson point process, we derive the probability of finding a specific content within a threshold distance and the optimal small cell base station density that achieves a given target cache hit probability. Furthermore, simulation results are performed to validate the analytical model.

eMAC: A Multi-channel Cognitive MAC Protocol for the Next Generation Wireless Networks

No abstract is provided for this article.

Optimum Transmission Rate in Fading Channels with Markovian Sources and QoS Constraints

This paper evaluates the performance of reliability and latency in machine type communication networks, which composed of single transmitter and receiver in the presence of Rayleigh fading channel. The source's traffic arrivals are modeled as Markovian processes namely Discrete-Time Markov process, Fluid Markov process, and Markov Modulated Poisson process, and delay/buffer overflow constraints are imposed. Our approach is based on the reliability and latency outage probability, where transmitter not knowing the channel condition, therefore the transmitter would be transmitting information over the fixed rate. The fixed rate transmission is modeled as a two state Discrete time Markov process, which identifies the reliability level of wireless transmission. Using effective bandwidth and effective capacity theories, we evaluate the trade-off between reliability-latency and identify QoS requirement. The impact of different source traffic originated from MTC devices under QoS constraints on the effective transmission rate are investigated.

Adaptive Secure Rate Allocation via TAS/MRC under Multi-Antenna Eavesdroppers