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Epidemic Enhanced Cellular Networks

When the base station density is sparse, users are often out of the coverage area of the cellular networks. In such scenarios, the users can rely on fellow users (willing to relay) to deliver delay tolerant information to a base station. Further, the users (and relays) can observe independent environments, during their traverse, if they are moving at considerable speeds. This provides them an opportunity to (independent) search for relays and or base stations at regular intervals of time. However, the user should beacon (transmit short pulses and wait for response), when it desires to be detected by the available relays in its neighbourhood. We derive the performance of such a system, accounting for the power utilized for beaconing, and obtain the beaconing policies that maximize the success (user/any previously contacted relay comes in contact with one of the base stations) probability of message delivery. The base stations and relays (at any given instance of time) are randomly distributed according to a Poisson Point process. We formulate the problem as a Markov Decision Process (MDP) to derive optimal policies depending on the system state (closed-loop). We show that the value function satisfies certain monotonicity properties and the optimal policy exhibits a certain switch-off property. We obtain an approximate solution for the continuous control and an exact solution for the ON-OFF (two action) control. Our investigations show that the closed-loop ON-OFF policies perform (almost) as good as the closed-loop continuous policies for all practically viable test cases. We further investigate open-loop policies for ON-OFF control, the policies that can be used when the system state is not known.