Browsing by Author "Warrier, Anirudh"

Now showing 1 - 6 of 6
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    AI-enabled interference mitigation for autonomous aerial vehicles in urban 5G networks
    (MDPI, 2023-10-13) Warrier, Anirudh; Al-Rubaye, Saba; Inalhan, Gokhan; Tsourdos, Antonios
    Integrating autonomous unmanned aerial vehicles (UAVs) with fifth-generation (5G) networks presents a significant challenge due to network interference. UAVs’ high altitude and propagation conditions increase vulnerability to interference from neighbouring 5G base stations (gNBs) in the downlink direction. This paper proposes a novel deep reinforcement learning algorithm, powered by AI, to address interference through power control. By formulating and solving a signal-to-interference-and-noise ratio (SINR) optimization problem using the deep Q-learning (DQL) algorithm, interference is effectively mitigated, and link performance is improved. Performance comparison with existing interference mitigation schemes, such as fixed power allocation (FPA), tabular Q-learning, particle swarm optimization, and game theory demonstrates the superiority of the DQL algorithm, where it outperforms the next best method by 41.66% and converges to an optimal solution faster. It is also observed that, at higher speeds, the UAV sees only a 10.52% decrease in performance, which means the algorithm is able to perform effectively at high speeds. The proposed solution effectively integrates UAVs with 5G networks, mitigates interference, and enhances link performance, offering a significant advancement in this field.
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    Future 6G communications powering vertical handover in non-terrestrial networks
    (IEEE, 2024-02-29) Warrier, Anirudh; Aljaburi, Lamees; Whitworth, Huw; Al-Rubaye, Saba; Tsourdos, Antonios
    The integration of Unmanned Aerial Vehicles (UAVs) into future 6G networks will open new possibilities for applications ranging from surveillance to communication infrastructure maintenance, precision agriculture, and surveying. However, ensuring uninterrupted connectivity for UAVs operating in remote or dynamic environments remains a significant challenge. This paper presents a novel approach to achieving seamless handover for UAVs when transitioning between terrestrial and satellite communication networks. The proposed method in this paper, leverages graph theory and develop a decision-making algorithm to optimise handover decisions, minimizing latency, improving performance, and reducing service disruption. It establishes a comprehensive graph model that represents the dynamic topology of available network nodes, including terrestrial base stations and low earth orbit (LEO) satellites, which adapts in real-time to changes in UAV position and network conditions. The approach incorporates a decision-making algorithm that considers several factors, such as received signal strength (RSS), signal-to-noise ratio (SNR), and elevation angle, to determine the optimal time and location for a handover between terrestrial base stations and satellite links. This ensures a seamless transition between communication links, minimizing service disruption. The performance of this method is evaluated through extensive simulations and comparison with existing solutions demonstrating significant improvements in RSS, SNR, throughput, latency, ping-pongs and enhanced overall UAV connectivity. The proposed graph method-based seamless handover solution represents a crucial advancement in enabling reliable and uninterrupted communication for UAVs operating in remote and challenging environments. By managing handovers between terrestrial and satellite networks, this research contributes to the realisation of the full potential of UAVs in emerging applications, thereby advancing the state-of-the-art in UAV technology.
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    Interference mitigation for 5G-connected UAV using deep Q-learning framework
    (IEEE, 2022-10-31) Warrier, Anirudh; Al-Rubaye, Saba; Panagiotakopoulos, Dimitrios; Inalhan, Gokhan; Tsourdos, Antonios
    To boost large-scale deployment of unmanned aerial vehicles (UAVs) in the future, a new wireless communication paradigm namely cellular-connected UAVs has recently received an upsurge of interest in both academia and industry. Fifth generation (5G) networks are expected to support this large-scale deployment with high reliability and low latency. Due to the high mobility, speed, and altitude of the UAVs there are numerous challenges that hinder its integration with the 5G architecture. Interference is one of the major roadblocks to ensuring the efficient co-existence between UAVs and terrestrial users in 5G networks. Conventional interference mitigation schemes for terrestrial networks are insufficient to deal with the more severe air-ground interference, which thus motivates this paper to propose a new algorithm to mitigate interference. A deep Q-learning (DQL) based algorithm is developed to mitigate interference intelligently through power control. The proposed algorithm formulates a non-convex optimization problem to maximize the Signal to Interference and Noise Ratio (SINR) and solves it using DQL. Its performance is measured as effective SINR against the complement cumulative distribution function. Further, it is compared with an adaptive link technique: Fixed Power Allocation (FPA), a standard power control scheme and tabular Q-learning(TQL). It is seen that the FPA has the worst performance while the TQL performs slightly better. This is since power control and interference coordination are introduced but not as effectively in the TQL method. It is observed that DQL algorithm outperforms the TQL implementation. To solve the severe air-ground interference experienced by the UAVs in 5G networks, this paper proposes a DQL algorithm. The algorithm effectively mitigates interference by optimizing SINR of the air-ground link and outperforms the existing methods. This paper therefore, proposes an effective algorithm to resolve the interference challenge in air-ground links for 5G-connected UAVs.
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    Seamless handover in urban 5G-UAV systems using entropy weighted method
    (World Academy of Science, Engineering and Technology, 2021-12-14) Warrier, Anirudh; Al-Rubaye, Saba; Panagiotakopoulos, Dimitrios; Inalhan, Gokhan; Tsourdos, Antonios
    The demand for increased data transfer rate and network traffic capacity has given rise to the concept of heterogeneous networks. Heterogeneous networks are wireless networks, consisting of devices using different underlying radio access technologies (RAT). For Unmanned Aerial Vehicles (UAVs) this enhanced data rate and network capacity is even more critical especially in their applications of medicine, delivery missions and military. In an urban heterogeneous network environment, the UAVs must be able switch seamlessly from one base station(BS) to another for maintaining a reliable link. Therefore, seamless handover in such urban environments have become a major challenge. In this paper, a novel scheme to achieve seamless handover is developed, an algorithm based on Received Signal Strength (RSS) criterion for network selection is used and Entropy Weighted Method (EWM) is implemented for decision making. Seamless handover using EWM decision-making is demonstrated successfully for a UAV moving across fifth generation(5G) and long-term evolution (LTE) networks via a simulation level analysis. Thus, a solution for UAV-5G communication, specifically the mobility challenge in heterogeneous networks is solved and this work could act as step forward in making UAV-5G architecture integration a possibility.
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    Towards 6G UAV networks: experimental performance analysis
    (IEEE, 2024-09-29) Warrier, Anirudh; Al-Rubaye, Saba; Tsourdos, Antonios
    Unmanned Aerial Vehicles (UAVs) are becoming increasingly prevalent across industries, from surveillance to delivery services, necessitating seamless handover between base stations for continuous operation and safety. Challenges arise due to the need to maintain connectivity and control as the UAV transitions between different access technologies, for Fifth Generation (5G) and beyond such as Sixth Generation (6G). Factors like altitude, mobility, and dynamic operation patterns pose hurdles to achieving smooth handovers critical for mission success. Traditional strategies often lack adaptability and efficiency, prompting the exploration of innovative approaches. To address these challenges, an experimental flight trial evaluates UAV handover performance in a heterogeneous network environment compared to simulation-level analysis. The trial involves UAV flight in an urban area with non-standalone (NSA) 6G connectivity, monitoring key performance indicators (KPIs) such as reference signal received power (RSRP), signal-to-noise interference ratio (SINR), throughput, and number of handovers. The system architecture encompasses an airborne measurement platform (DJI F450 UAV with XCAL mobile measurement tool and Pixhawk 4 Autopilot) and a ground-based counterpart interfacing through the core network. The analysis focuses on three key metrics: RSRP, RSRQ, and SINR, revealing temporary interruptions attributed to the UAV's exclusive connection to the wireless network. Insights from experimental trials highlight complexities and challenges associated with UAV handover performance, informing the design of improved protocols and communication systems. By addressing these challenges, the aim is to enhance operational reliability and mission success, unlocking the full potential of UAV technology across applications like surveillance, reconnaissance, delivery services, and more.
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    Unmanned air vehicle operational framework for public safety communications
    (IEEE, 2024-09-29) Subasu, Stefan; Al-Rubaye, Saba; Warrier, Anirudh; Whitworth, Huw
    The aviation and air mobility sector are experiencing a profound evolution, fuelled by swift technological progress and escalating requirements for effective, secure, and dependable airborne communication frameworks. The integration of Unmanned Aerial Systems (UAS), such as drones, into commercial and logistical activities is revolutionizing traditional concepts of air mobility. Integrating the Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) protocol into UAS communication networks enhances safety and reliability by preventing collisions. CSMA/CA allows UAS to sense the communication medium's availability before transmitting data, minimizing the risk of collisions and ensuring efficient data transmission, cru-cial for scenarios where safety is paramount. Sixth-Generation (6G) technology coupled with CSMA/CA protocol integration strengthens reliability and effectiveness in ensuring safe and efficient UAS operations. Simulation analysis using MATLAB helps understand signal quality and latency variations with distance from the UAV to the receiver, essential for safety communications analysis. Analyzing handover procedures is crucial for public safety, especially in scenarios where UAS encounter situations requiring a change from one base transceiver station (BTS) to another. Vertical handovers, particularly relevant in the context of evolving Unmanned Traffic Management (UTM) and Air Traffic Management (ATM) architectures, may become more prevalent due to the significant altitude variations inherent in UAS operations.