arXiv subjects

Hussein Al-Shatri

Publications and source records attributed to Hussein Al-Shatri.

4 recordsLinked to original sources

arXiv2024

Communications over Unlicensed sub-8 GHz Spectrum: Opportunities and Challenges

The utilization of unlicensed spectrum presents a promising solution to the issue of spectrum scarcity in densely populated areas, while also offering a cost-effective means to connect underserved regions. In response to this potential, both academia and industry are actively exploring innovative applications of unlicensed spectrum. This work offers a thorough overview of unlicensed spectrum bands below 8 GHz, including TV White Spaces, Civil Broadband Radio Services, Industrial Scientific Medical bands, and the Unlicensed National Information Infrastructure. The paper focuses on three key aspects: regulations, existing technologies, and applications. It is essential to recognize that "unlicensed" does not equate to "unregulated"; therefore, a clear understanding of permissible and prohibited activities is crucial. From a technological perspective, we examine the current technologies, their capabilities, and relevant applications. Additionally, the shared nature of this spectrum introduces challenges related to interference among users. These collisions can be managed through two primary strategies, that we described: a database-driven approach and coexistence mechanisms at the MAC and PHY layers. This work may serve as a starting point for those who are interested in the unlicensed spectrum, both in academia and industry.

eess.SP↗

arXiv2020

Cost Sharing Games for Energy-Efficient Multi-Hop Broadcast in Wireless Networks

We study multi-hop broadcast in wireless networks with one source node and multiple receiving nodes. The message flow from the source to the receivers can be modeled as a tree-graph, called broadcast-tree. The problem of finding the minimum-power broadcast-tree (MPBT) is NP-complete. Unlike most of the existing centralized approaches, we propose a decentralized algorithm, based on a non-cooperative cost-sharing game. In this game, every receiving node, as a player, chooses another node of the network as its respective transmitting node for receiving the message. Consequently, a cost is assigned to the receiving node based on the power imposed on its chosen transmitting node. In our model, the total required power at a transmitting node consists of (i) the transmit power and (ii) the circuitry power needed for communication hardware modules. We develop our algorithm using the marginal contribution (MC) cost-sharing scheme and show that the optimum broadcast-tree is always a Nash equilibrium (NE) of the game. Simulation results demonstrate that our proposed algorithm outperforms conventional algorithms for the MPBT problem. Besides, we show that the circuitry power, which is usually ignored by existing algorithms, significantly impacts the energy-efficiency of the network.

cs.GT↗

arXiv2019

Multi-Agent Reinforcement Learning for Energy Harvesting Two-Hop Communications with a Partially Observable State

We consider an energy harvesting (EH) transmitter communicating with a receiver through an EH relay. The harvested energy is used for data transmission, including the circuit energy consumption. As in practical scenarios, the system state, comprised by the harvested energy, battery levels, data buffer levels, and channel gains, is only partially observable by the EH nodes. Moreover, the EH nodes have only outdated knowledge regarding the channel gains for their own transmit channels. Our goal is to find distributed transmission policies aiming at maximizing the throughput. A channel predictor based on a Kalman filter is implemented in each EH node to estimate the current channel gain for its own channel. Furthermore, to overcome the partial observability of the system state, the EH nodes cooperate with each other to obtain information about their parameters during a signaling phase. We model the problem as a Markov game and propose a multi-agent reinforcement learning algorithm to find the transmission policies. We show the trade-off between the achievable throughput and the signaling required, and provide convergence guarantees for the proposed algorithm. Results show that even when the signaling overhead is taken into account, the proposed algorithm outperforms other approaches that do not consider cooperation.

cs.IT↗

arXiv2015

Maximizing the Sum Rate in Cellular Networks Using Multi-Convex Optimization

In this paper, we propose a novel algorithm to maximize the sum rate in interference-limited scenarios where each user decodes its own message with the presence of unknown interferences and noise considering the signal-to-interference-plus-noise-ratio. It is known that the problem of adapting the transmit and receive filters of the users to maximize the sum rate with a sum transmit power constraint is non-convex. Our novel approach is to formulate the sum rate maximization problem as an equivalent multi-convex optimization problem by adding two sets of auxiliary variables. An iterative algorithm which alternatingly adjusts the system variables and the auxiliary variables is proposed to solve the multi-convex optimization problem. The proposed algorithm is applied to a downlink cellular scenario consisting of several cells each of which contains a base station serving several mobile stations. We examine the two cases, with or without several half-duplex amplify-and-forward relays assisting the transmission. A sum power constraint at the base stations and a sum power constraint at the relays are assumed. Finally, we show that the proposed multi-convex formulation of the sum rate maximization problem is applicable to many other wireless systems in which the estimated data symbols are multi-affine functions of the system variables.

cs.IT↗