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Christina Chaccour

Publications and source records attributed to Christina Chaccour.

23 records · Page 2Linked to original sources

Can Terahertz Provide High-Rate Reliable Low Latency Communications for Wireless VR?

Wireless virtual reality (VR) imposes new visual and haptic requirements that are directly linked to the quality-of-experience (QoE) of VR users. These QoE requirements can only be met by wireless connectivity that offers high-rate and high-reliability low latency communications (HRLLC), unlike the low rates usually considered in vanilla ultra-reliable low latency communication scenarios. The high rates for VR over short distances can only be supported by an enormous bandwidth, which is available in terahertz (THz) frequency bands. Guaranteeing HRLLC requires dealing with the uncertainty that is specific to the THz channel. To explore the potential of THz for meeting HRLLC requirements, a quantification of the risk for an unreliable VR performance is conducted through a novel and rigorous characterization of the tail of the end-to-end (E2E) delay. Then, a thorough analysis of the tail-value-atrisk (TVaR) is performed to concretely characterize the behavior of extreme wireless events crucial to the real-time VR experience. System reliability for scenarios with guaranteed line-of-sight (LoS) is then derived as a function of THz network parameters after deriving a novel expression for the probability distribution function of the THz transmission delay. Numerical results show that abundant bandwidth and low molecular absorption are necessary to improve the reliability. However, their effect remains secondary compared to the availability of LoS, which significantly affects the THz HRLLC performance. In particular, for scenarios with guaranteed LoS, a reliability of 99.999% (with an E2E delay threshold of 20 ms) for a bandwidth of 15 GHz along with data rates of 18.3 Gbps can be achieved by the THz network (operating at a frequency of 1 THz), compared to a reliability of 96% for twice the bandwidth, when blockages are considered.

cs.IT↗

Joint Location, Bandwidth and Power Optimization for THz-enabled UAV Communications

In this paper, the problem of unmanned aerial vehicle (UAV) deployment, power allocation, and bandwidth allocation is investigated for a UAV-assisted wireless system operating at terahertz (THz) frequencies. In the studied model, one UAV can service ground users using the THz frequency band. However, the highly uncertain THz channel will introduce new challenges to the UAV location, user power, and bandwidth allocation optimization problems. Therefore, it is necessary to design a novel framework to deploy UAVs in the THz wireless systems. This problem is formally posed as an optimization problem whose goal is to minimize the total delays of the uplink and downlink transmissions between the UAV and the ground users by jointly optimizing the deployment of the UAV, the transmit power and the bandwidth of each user. The communication delay is crucial for emergency communications. To tackle this nonconvex delay minimization problem, an alternating algorithm is proposed while iteratively solving three subproblems: location optimization subproblem, power control subproblem, and bandwidth allocation subproblem. Simulation results show that the proposed algorithm can reduce the transmission delay by up to $59.3\%$, $49.8\%$ and $75.5\%$ respectively compared to baseline algorithms that optimize only UAV location, bandwidth allocation or transmit power control.

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On the Ruin of Age of Information in Augmented Reality over Wireless Terahertz (THz) Networks

Guaranteeing fresh and reliable information for augmented reality (AR) services is a key challenge to enable a real-time experience and sustain a high quality of physical experience (QoPE) for the users. In this paper, a terahertz (THz) cellular network is used to exchange rate-hungry AR content. For this network, guaranteeing an instantaneous low peak age of information (PAoI) is necessary to overcome the uncertainty stemming from the THz channel. In particular, a novel economic concept, namely, the risk of ruin is proposed to examine the probability of occurrence of rare, but extremely high PAoI that can jeopardize the operation of the AR service. To assess the severity of these hazards, the cumulative distribution function (CDF) of the PAoI is derived for two different scheduling policies. This CDF is then used to find the probability of maximum severity of ruin PAoI. Furthermore, to provide long term insights about the AR content's age, the average PAoI of the overall system is also derived. Simulation results show that an increase in the number of users will positively impact the PAoI in both the expected and worst-case scenarios. Meanwhile, an increase in the bandwidth reduces the average PAoI but leads to a decline in the severity of ruin performance. The results also show that a system with preemptive last come first served (LCFS) queues of limited size buffers have a better ruin performance (12% increase in the probability of guaranteeing a less severe PAoI while increasing the number of users), whereas first come first served (FCFS) queues of limited buffers lead to a better average PAoI performance (45% lower PAoI as we increase the bandwidth).

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Risk-Based Optimization of Virtual Reality over Terahertz Reconfigurable Intelligent Surfaces

In this paper, the problem of associating reconfigurable intelligent surfaces (RISs) to virtual reality (VR) users is studied for a wireless VR network. In particular, this problem is considered within a cellular network that employs terahertz (THz) operated RISs acting as base stations. To provide a seamless VR experience, high data rates and reliable low latency need to be continuously guaranteed. To address these challenges, a novel risk-based framework based on the entropic value-at-risk is proposed for rate optimization and reliability performance. Furthermore, a Lyapunov optimization technique is used to reformulate the problem as a linear weighted function, while ensuring that higher order statistics of the queue length are maintained under a threshold. To address this problem, given the stochastic nature of the channel, a policy-based reinforcement learning (RL) algorithm is proposed. Since the state space is extremely large, the policy is learned through a deep-RL algorithm. In particular, a recurrent neural network (RNN) RL framework is proposed to capture the dynamic channel behavior and improve the speed of conventional RL policy-search algorithms. Simulation results demonstrate that the maximal queue length resulting from the proposed approach is only within 1% of the optimal solution. The results show a high accuracy and fast convergence for the RNN with a validation accuracy of 91.92%.

cs.IT↗

On the Reliability of Wireless Virtual Reality at Terahertz (THz) Frequencies

Guaranteeing ultra reliable low latency communications (URLLC) with high data rates for virtual reality (VR) services is a key challenge to enable a dual VR perception: visual and haptic. In this paper, a terahertz (THz) cellular network is considered to provide high-rate VR services, thus enabling a successful visual perception. For this network, guaranteeing URLLC with high rates requires overcoming the uncertainty stemming from the THz channel. To this end, the achievable reliability and latency of VR services over THz links are characterized. In particular, a novel expression for the probability distribution function of the transmission delay is derived as a function of the system parameters. Subsequently, the end-to-end (E2E) delay distribution that takes into account both processing and transmission delay is found and a tractable expression of the reliability of the system is derived as a function of the THz network parameters such as the molecular absorption loss and noise, the transmitted power, and the distance between the VR user and its respective small base station (SBS). Numerical results show the effects of various system parameters such as the bandwidth and the region of non-negligible interference on the reliability of the system. In particular, the results show that THz can deliver rates up to 16.4 Gbps and a reliability of 99.999% (with a delay threshold of 30 ms) provided that the impact of the molecular absorption on the THz links, which substantially limits the communication range of the SBS, is alleviated by densifying the network accordingly.

cs.IT↗