Resource Allocation for Intelligent Reflecting Surfaces Assisted Federated Learning System with Imperfect CSI

Huang, Wei; Han, Zhiren; Zhao, Li; Xu, Hongbo; Li, Zhongnian; Wang, Ze

doi:10.3390/a14120363

Cited by 4 publications

(4 citation statements)

References 27 publications

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“…Moreover, to further improve the system performance, multiple antennae at the transmitters and/or receivers can be adopted to exploit the diversity gain via diversity combining techniques [61][62][63][64]. The impact of the imperfect channel state information on the system performance is also valuable to address in future work [56,[65][66][67][68]. Another promising extension of the present paper is to enhance the system performance of both the D2D and cellular networks with the support of the reconfigurable intelligent surface (RIS) [69][70][71] and/or utilizing interference alignment to mitigate mutual interference between two networks [72,73].…”

Section: Discussionmentioning

confidence: 99%

On the Performance of Underlay Device-to-Device Communications

Nguyen

et al. 2022

Sensors

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This paper comprehensively investigates the performance of the D2D underlaying cellular networks where D2D communications are operated concurrently with cellular networks provided that the aggregate interference measured on licensed users is strictly guaranteed. In particular, we derive the outage probability (OP), the average rate, and the amount of fading (AoF) of the D2D networks in closed-form expressions under three distinct power allocation schemes, i.e., the path-loss-based, equal, and random allocation schemes. It is noted that the considered networks take into consideration the impact of the intra-D2D networks, the inter-interference from the cellular networks and background noise, thus involving many random variables and leading to a complicated mathematical framework. Moreover, we also reveal the behavior of the OP with respect to the transmit power based on the rigorous mathematical frameworks rather than the computer-based simulation results. The derived framework shows that increasing the transmit power is beneficial for the OP of the D2D users. Regarding the cellular networks, the coverage probability (Pcov) of the cellular users is computed in closed-form expression too. Monte Carlo simulations are given to verify the accuracy of the proposed mathematical frameworks. Our findings illustrate that the power allocation method based on prior path-loss information outperforms the other methods in the average sum rate.

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Section: Discussionmentioning

confidence: 99%

On the Performance of Underlay Device-to-Device Communications

Nguyen

et al. 2022

Sensors

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“…To minimize the latency of FL training, the authors of [15] proposed a Multi-Armed Bandit algorithm based on training latency, availability, and fairness constraints. A notable contribution in resource allocation and optimization in dynamically evolving network environments is proposed by Huang et al [16]. Their research investigates the complexities of resource allocation in FL systems assisted by intelligent 104 reflecting surfaces (IRS), particularly under the constraints of imperfect channel state information (CSI).…”

Section: (A)mentioning

confidence: 99%

“…Poryazov et al [31] address QoS estimation challenges, proposing a normalization approach for telecommunication systems. Huang et al [16] explore resource allocation in FL systems, contributing to the understanding of QoS under imperfect channel conditions. These insights are vital for optimizing both QoS and QoE in FL systems.…”

Section: Federated Learning-driven Edge Node Selectionmentioning

confidence: 99%

Resource-Aware Federated Hybrid Profiling for Edge Node Selection in Federated Patient Similarity Network

Navaz,

Kassabi,

Serhani

et al. 2023

Applied Sciences

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The widespread adoption of edge computing for resource-constrained devices presents challenges in computational straggler issues, primarily due to the heterogeneity of edge node resources. This research addresses these issues by introducing a novel resource-aware federated hybrid profiling approach. This approach involves classifying edge node resources with relevant performance metrics and leveraging their capabilities to optimize performance and improve Quality of Service (QoS), particularly in real-time eHealth applications. Such paradigms include Federated Patient Similarity Network (FPSN) models that distribute processing at each edge node and fuse the built PSN matrices in the cloud, presenting a unique challenge in terms of optimizing training and inference times, while ensuring efficient and timely updates at the edge nodes. To address this concern, we propose a resource-aware federated hybrid profiling approach that measures the available static and dynamic resources of the edge nodes. By selecting nodes with the appropriate resources, we aim to optimize the FPSN to ensure the highest possible Quality of Service (QoS) for its users. We conducted experiments using edge performance metrics, i.e., accuracy, training convergence, memory and disk usage, execution time, and network statistics. These experiments uniquely demonstrate our work’s contribution to optimizing resource allocation and enhancing the performance of eHealth applications in real-time contexts using edge computing.

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“…The RIS has passive reflecting elements (RE) that can scatter the incident signal in a particular direction in such a way as to increase the signal strength in one direction while lessening it in the other direction [12]. The individual elements can be controlled by adjusting the phase shift angle using phase [11,14]. In [15], the RIS is used in symbiotic radio (SR) for introducing channel diversity for secret key generation.…”

Section: Introductionmentioning

confidence: 99%

Improved Rate of Secret Key Generation Using Passive Re-Configurable Intelligent Surfaces for Vehicular Networks

et al. 2022

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The reconfigurable intelligent surfaces (RIS) is a new technology that can be utilized to provide security to vehicle-to-vehicle (V2V) communications at the physical layer. In this paper, we achieve a higher key generation rate for V2V communications at lower cost and computational complexity. We investigate the use of a passive RIS as a relay, to introduce channel diversity and increase the key generation rate (KGR), accordingly. In this regard, we consider the subsets of consecutive reflecting elements instead of the RIS as a whole in a time slot, i.e., instead of a single reflector, the subsets of reflectors are utilized to redirect the signal to the receiver via passive beam forming. Simulations are conducted for different sizes of RISs and subsets of reflectors per RIS. From the results obtained, it can be seen that when we consider a subset of reflectors instead of the RIS as a single entity, it becomes increasingly difficult to intercept the signal at the eavesdropper. In the proposed scheme, the KGR reaches up to 6 bps per time slot.

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Resource Allocation for Intelligent Reflecting Surfaces Assisted Federated Learning System with Imperfect CSI

Cited by 4 publications

References 27 publications

On the Performance of Underlay Device-to-Device Communications

On the Performance of Underlay Device-to-Device Communications

Resource-Aware Federated Hybrid Profiling for Edge Node Selection in Federated Patient Similarity Network

Improved Rate of Secret Key Generation Using Passive Re-Configurable Intelligent Surfaces for Vehicular Networks

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