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108 results on '"Hashima, Sherief"'

13. Reconfigurable intelligent surface‐aided millimetre wave communications utilizing two‐phase minimax optimal stochastic strategy bandit

Author

Mohamed, Ehab Mahmoud, Hashima, Sherief, Anjum, Nasreen, Hatano, Kohei, Shafai, Walid El, and Elhlawany, Basem M.

Subjects
QA75, Electrical and Electronic Engineering, Computer Science Applications
Abstract

Millimetre wave (mm Wave) communications, that is, 30 to 300 GHz, have intermittent short-range transmissions, so the use of reconfigurable intelligent surface (RIS) seems to be a promising solution to extend its coverage. However, optimizing phase shifts (PSs) of both mm Wave base station (BS) and RIS to maximize the received spectral efficiency at the intended receiver seems challenging due to massive antenna elements usage. In this paper, an online learning approach is proposed to address this problem, where it is considered a two-phase multi-armed bandit (MAB) game. In the first phase, the PS vector of the mm Wave BS is adjusted, and based on it, the PS vector of the RIS is calibrated in the second phase and vice versa over the time horizon. The minimax optimal stochastic strategy(MOSS) MAB algorithm is utilized to implement the proposed two-phase MAB approach efficiently. Furthermore, to relax the problem of estimating the channel state information(CSI) of both mm Wave BS and RIS, codebook-based PSs are considered. Finally, numerical analysis confirms the superior performance of the proposed scheme against the optimal performance under different scenarios.

Published
2022

39. On Softwarization of Intelligence in 6G Networks for Ultra-Fast Optimal Policy Selection: Challenges and Opportunities

Author

Hashima, Sherief, Fadlullah, Zubair Md, Fouda, Mostafa M., Mohamed, Ehab Mahmoud, Hatano, Kohei, ElHalawany, Basem M., and Guizani, Mohsen

Abstract

The emerging Sixth Generation (6G) communication networks promising 100 to 1000 Gb/s rates and ultra-low latency (1 millisecond) are anticipated to have native, embedded Artificial Intelligence (AI) capability to support a myriad of services, such as Holographic Type Communications (HTC), tactile Internet, remote surgery, etc. However, these services require ultra-reliability, which is highly impacted by the dynamically changing environment of 6G heterogeneous tiny cells, whereby static AI solutions fitting all scenarios and devices are impractical. Hence, this article introduces a novel concept called the softwarization of intelligence in 6G networks to select the most ideal, ultra-fast optimal policy based on the highly varying channel conditions, traffic demand, user mobility, and so forth. Our envisioned concept is exemplified in a Multi-Armed Bandit (MAB) framework and evaluated within a use case of two simultaneous scenarios (i.e., Neighbor Discovery and Selection (NDS) in a Device-to-Device (D2D) network and aerial gateway selection in an Unmanned Aerial Vehicle (UAV)-based under-served area network). Furthermore, our concept is evaluated through extensive computer-based simulations that indicate encouraging performance. Finally, related challenges and future directions are highlighted.

Published
2023
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