FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud System

in IEEE Transactions on Wireless Communications (in press)

Federated learning (FL) is capable of performing large distributed machine learning tasks across multiple edge users by periodically aggregating trained local parameters. To address key challenges of ... [more ▼]

Federated learning (FL) is capable of performing large distributed machine learning tasks across multiple edge users by periodically aggregating trained local parameters. To address key challenges of enabling FL over a wireless fogcloud system (e.g., non-i.i.d. data, users’ heterogeneity), we first propose an efficient FL algorithm based on Federated Averaging (called FedFog) to perform the local aggregation of gradient parameters at fog servers and global training update at the cloud. Next, we employ FedFog in wireless fog-cloud systems by investigating a novel network-aware FL optimization problem that strikes the balance between the global loss and completion time. An iterative algorithm is then developed to obtain a precise measurement of the system performance, which helps design an efficient stopping criteria to output an appropriate number of global rounds. To mitigate the straggler effect, we propose a flexible user aggregation strategy that trains fast users first to obtain a certain level of accuracy before allowing slow users to join the global training updates. Extensive numerical results using several real-world FL tasks are provided to verify the theoretical convergence of FedFog. We also show that the proposed co-design of FL and communication is essential to substantially improve resource utilization while achieving comparable accuracy of the learning model. [less ▲]

RIS-Assisted Energy-Efficient LEO Satellite Communications with NOMA

E-print/Working paper (2023)

This paper proposes an energy-efficient RIS-assisted downlink NOMA communication for LEO satellite networks. The proposed framework simultaneously optimizes the transmit power of ground terminals of the ... [more ▼]

This paper proposes an energy-efficient RIS-assisted downlink NOMA communication for LEO satellite networks. The proposed framework simultaneously optimizes the transmit power of ground terminals of the LEO satellite and the passive beamforming of RIS while ensuring the quality of services. Due to the nature of the considered system and optimization variables, the energy efficiency maximization problem is non-convex. In practice, obtaining the optimal solution for such problems is very challenging. Therefore, we adopt alternating optimization methods to handle the joint optimization in two steps. In step 1, for any given phase shift vector, we calculate satellite transmit power towards each ground terminal using the Lagrangian dual method. Then, in step 2, given the transmit power, we design passive beamforming for RIS by solving the semi-definite programming. We also compare our solution with a benchmark framework having a fixed phase shift design and a conventional NOMA framework without involving RIS. Numerical results show that the proposed optimization framework achieves 21.47% and 54.9% higher energy efficiency compared to the benchmark and conventional frameworks. [less ▲]

Energy-Efficient Service-Aware Multi-Connectivity Scheduler for Uplink Multi-Layer Non-Terrestrial Networks

in IEEE Transactions on Green Communications and Networking (2023)

This paper introduces the concept of energy efficiency (EE) in the uplink with the capability of multi-connectivity (MC) in a multi-orbit non-terrestrial network (NTN), where user terminals (UTs) can be ... [more ▼]

This paper introduces the concept of energy efficiency (EE) in the uplink with the capability of multi-connectivity (MC) in a multi-orbit non-terrestrial network (NTN), where user terminals (UTs) can be simultaneously served by more than one satellite to achieve higher peak throughput at reduced energy consumption. This concept also considers the service classification of the users, so that network dimensioning is performed in order to satisfy the quality of service (QoS) requirement of users. MC can increase throughput, but this entails increased power consumption at user terminal for uplink transmissions. To this end, an energy-efficient service-aware multi-connectivity (EE-SAMC) scheduling algorithm is developed in this paper to improve the EE of uplink communications. EE-SAMC uses available radio resources and propagation information to intelligently define a dynamic resource allocation pattern, that optimally routes traffic so as to reduce the energy consumption at the UT while ensuring QoS is maximized. EE-SAMC is designed based on the formulation of a non-convex combinatorial problem, it is solved in two ways involving firstly an optimization solution and secondly a heuristic approach. The effectiveness of EE-SAMC is compared with random allocation, round robin and heuristic schedulers in terms of EE, throughput and delay; EE-SAMC outperforms all schedulers. [less ▲]

Energy-Efficient RIS-Enabled NOMA Communication for 6G LEO Satellite Networks

E-print/Working paper (2023)

Reconfigurable Intelligent surfaces (RIS) have the potential to significantly improve the performance of future 6G LEO satellite networks. In particular, RIS can improve the signal quality of ground ... [more ▼]

Reconfigurable Intelligent surfaces (RIS) have the potential to significantly improve the performance of future 6G LEO satellite networks. In particular, RIS can improve the signal quality of ground terminal, reduce power consumption of satellite and increase spectral efficiency of overall network. This paper proposes an energy-efficient RIS-enabled NOMA communication for LEO satellite networks. The proposed framework simultaneously optimizes the transmit power of ground terminals at LEO satellite and passive beamforming at RIS while ensuring the quality of services. Due to the nature of the considered system and optimization variables, the problem of energy efficiency maximization is formulated as non-convex. In practice, it is very challenging to obtain the optimal solution for such problems. Therefore, we adopt alternating optimization methods to handle the joint optimization in two steps. In step 1, for any given phase shift vector, we calculate efficient power for ground terminals at satellite using Lagrangian dual method. Then, in step 2, given the transmit power, we design passive beamforming for RIS by solving the semi-definite programming. To validate the proposed solution, numerical results are also provided to demonstrate the benefits of the proposed optimization framework. [less ▲]

Demand-Aware Onboard Payload Processor Management for High Throughput NGSO Satellite Systems

in IEEE Transactions on Aerospace and Electronic Systems (2023)

Opportunities for physical layer security in UAV communication enhanced with intelligent reflective surfaces

in IEEE Wireless Communications (2022), 29(06), 22-28

Unmanned aerial vehicles (UAVs) are an important component of next-generation wireless networks that can assist in high data rate communications and provide enhanced coverage.Their high mobility and ... [more ▼]

Unmanned aerial vehicles (UAVs) are an important component of next-generation wireless networks that can assist in high data rate communications and provide enhanced coverage.Their high mobility and aerial nature offer deployment flexibility and low-cost infrastructure support to existing cellular networks and provide many applications that rely on mobile wireless communications. However, security is a major challenge in UAV communications, and physical layer security (PLS) is an important technique to improve the reliability and security of data shared with the assistance of UAVs. Recently, the intelligent reflective surface (IRS) has emerged as a novel technology to extend and/or enhance wireless coverage by reconfiguring the propagation environment of communications. This article provides an overview of how the IRS can improve the PLS of UAV networks. We discuss different use cases of PLS for IRS-enhanced UAV communications and briefly review the recent advances in this area. Then, based on the recent advances, we also present a case study that utilizes alternate optimization to maximize the secrecy capacity for an IRS-enhanced UAV scenario in the presence of multiple Eves. Finally, we highlight several open issues and research challenges to realize PLS in IRS-enhanced UAV communications. [less ▲]

Optimizing Computational and Communication Resources for MEC Network Empowered UAV-RIS Communication

Scientific Conference (2022, December)

With the technological evolution and new applications, user equipment (UEs) has become a vital part of our lives. However, limited computational capabilities and finite battery life bottleneck the ... [more ▼]

With the technological evolution and new applications, user equipment (UEs) has become a vital part of our lives. However, limited computational capabilities and finite battery life bottleneck the performance of computationally demanding applications. A practical solution to enhance the quality of experience (QoE) is to offload the extensive computation to the mobile edge cloud (MEC). Moreover, the network’s performance can be further improved by deploying an unmanned aerial vehicle (UAV) integrated with intelligent reflective surfaces (IRS): an effective alternative to massive antenna systems to enhance the signal quality and suppress interference. In this work, the MEC network architecture is assisted by UAV-IRS to provide computational services to the UEs. To do so, a cost minimization problem in terms of computing time and hovering energy consumption is formulated. Furthermore, to achieve an efficient solution to a formulated challenging problem, the original optimization problem is decoupled into sub-problems using the block-coordinate decent method. Moreover, numerical results are compared to baseline schemes to determine the effectiveness of the proposed scheme. Simulation results demonstrate that the optimal allocation of local computational resources results in minimizing tasks’ computational time and hovering energy consumption. [less ▲]

Space-Terrestrial Cooperation Over Spatially Correlated Channels Relying on Imperfect Channel Estimates: Uplink Performance Analysis and Optimization

in IEEE Transactions on Communications (2022)

Demand aware Resource Management Techniques for Flexible Broadband Satellite Communication Systems

Poster (2022, November 08)

On the Performance of Cache-Free/Cache-Aided STBC-NOMA in Cognitive Hybrid Satellite-Terrestrial Networks

in IEEE Wireless Communications Letters (2022), 11(12), 2655-2659

Future wireless networks pose several challenges such as high spectral efficiency, wide coverage massive connectivity, low receiver complexity, etc. To this end, this letter investigates an overlay based ... [more ▼]

Future wireless networks pose several challenges such as high spectral efficiency, wide coverage massive connectivity, low receiver complexity, etc. To this end, this letter investigates an overlay based cognitive hybrid satellite-terrestrial network (CHSTN) combining non-orthogonal multiple access (NOMA) and conventional Alamouti space-time block coding (STBC) techniques. Herein, a decode-and-forward based secondary terrestrial network cooperates with a primary satellite network for dynamic spectrum access. Further, for reliable content delivery and low latency requirements, wireless caching is employed, whereby the secondary network can store the most popular contents of the primary network. Considering the relevant heterogeneous fading channel models and the NOMA-based imperfect successive interference cancellation, we examine the performance of CHSTN for the cache-free (CF) STBC-NOMA and the cache-aided (CA) STBC-NOMA schemes. We assess the outage probability expressions for primary and secondary networks and further, highlight the corresponding achievable diversity orders. Indicatively, the proposed CF/CA STBC-NOMA schemes for CHSTN perform significantly better than the benchmark standalone NOMA and OMA schemes. [less ▲]