Abdelrahman M. Ibrahim

Coverage probability analysis for wireless networks using repulsive point processes

The recent witnessed evolution of cellular networks from a carefully planned deployment to more irregular, heterogeneous deployments of Macro, Pico and Femto-BSs motivates new analysis and design approaches. In this paper, we analyze the coverage probability in cellular networks assuming repulsive point processes for the base station deployment. In particular, we characterize, analytically using stochastic geometry, the downlink probability of coverage under a Matern hardcore point process to ensure minimum distance between the randomly located base stations. Assuming a mobile user connects to the nearest base station and Rayleigh fading, we derive two lower bounds expressions on the downlink probability of coverage that is within 4% from the simulated scenario. To validate our model, we compare the probability of coverage of the Matern hardcore topology against an actual base station deployment obtained from a public database. The comparison shows that the actual base station deployment can be fitted by setting the appropriate Matern point process density.

Stability Analysis of Slotted Aloha With Opportunistic RF Energy Harvesting

Energy harvesting (EH) is a promising technology for realizing energy-efficient wireless networks. In this paper, we utilize the ambient RF energy, particularly interference from neighboring transmissions, to replenish the batteries of the EH enabled nodes. However, RF energy harvesting imposes new challenges into the analysis of wireless networks. Our objective in this paper is to investigate the performance of a slotted Aloha random access wireless network consisting of two types of nodes, namely Type I, which has unlimited energy supply and Type II, which is solely powered by an RF energy harvesting circuit. The transmissions of a Type I node are recycled by a Type II node to replenish its battery. We characterize an inner bound on the stable throughput region under half-duplex and full-duplex energy harvesting paradigms as well as for the finite capacity battery case. Additionally, we analyze the case where RF energy harvesting serves as a backup for an unlimited energy source. We present numerical results that validate our analytical results, and demonstrate their utility for the analysis of the exact system.

Green Distributed Storage Using Energy Harvesting Nodes

We consider a distributed storage system where data storage nodes are equipped with energy harvesting transmitters. In particular, F files are stored over n storage nodes using regenerating codes. The main operations of the distributed storage system are serving the file requests of data collectors and repairing the content of storage nodes that fail or leave the system. Each operation has an associated energy expenditure. Under the intermittent energy arrival profile, we study the problem of maximizing the number of retrieved files given a deadline. Additionally, we consider the problem of minimizing the repair time of a failed node. Both optimization problems turn out to be equivalent to binary programs, for which we provide a tractable solution in two steps. First, we determine necessary and sufficient conditions on the harvested energy that ascertain the feasibility of retrieving (repairing) M files in T time slots. Using these conditions, we develop two algorithms that reduce the formulated optimization problems to a single feasibility problem. Then, we solve the feasibility problem using forward and backward algorithms. Additionally, we study the online setup where only causal knowledge of energy arrivals is available at the network nodes. We present numerical results on the short and long term performance of the system operations under the proposed algorithms.

Analytical Markov model for slotted ALOHA with opportunistic RF energy harvesting

In this paper, we investigate the performance of an ALOHA random access wireless network consisting of nodes with and without RF energy harvesting capability. We develop and analyze a Markov model for the system when nodes with RF energy harvesting capability are infinitely backlogged. Our results indicate that the network throughput is improved when the conventional nodes are underloaded. On the contrary, when all types of nodes have finite backlogs, we numerically demonstrate that the network throughput and delay are improved when the overall system is overloaded. We show that there exists a trade-off between energy efficiency and delay, and we determine the optimal number of energy harvesting nodes in a network maximizing the energy efficiency while satisfying a given delay requirement.

Towards green distributed storage systems

We model a distributed storage system consisting of energy harvesting nodes which store multiple files. To investigate the performance of file retrieval and node repair, we formulate two optimization problems: maximizing the number of retrieved (repaired) files given a deadline, and minimizing the retrieval (repair) time of a number of stored files. We derive the necessary and sufficient conditions for the feasibility of retrieving (repairing) a number of files by a deadline. Utilizing these conditions, we reduce the aforementioned problems to a single feasibility problem, which is solved using forward and backward algorithms. Finally, the system performance is illustrated numerically.