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Structureless communications such as Device-to-Device (D2D) relaying are undeniably of paramount importance to improving the performance of today’s mobile networks. Such a communication paradigm requires a certain level of intelligence at the device level, thereby allowing it to interact with the environment and make proper decisions. However, decentralizing decision-making may induce paradoxical outcomes, resulting in a drop in performance, which sustains the design of self-organizing yet efficient systems. We propose that each device decides either to directly connect to the eNodeB or get access via another device through a D2D link. In the first part of this article, we describe a biform game framework to analyze the proposed self-organized system’s performance, under pure and mixed strategies. We use two reinforcement learning (RL) algorithms, enabling devices to self-organize and learn their pure/mixed equilibrium strategies in a fully distributed fashion. Decentralized RL algorithms are shown to play an important role in allowing devices to be self-organized and reach satisfactory performance with incomplete information or even under uncertainties. We point out through a simulation the importance of D2D relaying and assess how our learning schemes perform under slow/fast channel fading.

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Ensuring high reliability is one of the major goals of 5G systems. This work investigates the problem of cooperative relaying and the optimal number of devices to be directly connected to the base station, in order to meet best uplink performance in terms of throughput and reliability. We first propose a D2D-relaying system where devices cooperate forming groups of cellular devices serving as relays to other groups of D2D transmitters. Second we adopt a Markov chain framework, where the states are defined as the numbers of D2D-relays present in the network. Based on that, we derive the average network throughput and reliability. Next, we show that there exists an optimal device distribution, that maximizes the overall reliability and throughput. This number is strongly related to the switching probabilities of the devices and the network parameters such as the orthogonality factor, the cooperation level of D2D-transmitter, the network density and the cluster's radius. Simulation results illustrate the optimal switching probabilities and the average number of D2Drelays that maximize the overall throughput and reliability.

Offloading the network, minimizing the power consumption as well as reducing interference are important issues in wireless networks. These requirements mandate that future cellular networks need to use Deviceto-Device communication as a key enabler. To harness this solution, we propose a two-device system that combines cellular and Device-to-Device (D2D) communication in an uplink communication. We model this system as a quitting game where devices choose simultaneously either to continue or to quit transmitting over the cellular network. The devices will strategically choose whether to compete or to cooperate through mobile relaying. We first calculate the throughput and the outage probability in a fading channel. Then we find the Sub-game Perfect Equilibrium of this game by determining the pure and mixed Nash equilibrium of each subgame. Results show that the outage probability depends on the transmission power and the distance separating a device from its serving BS. The quitting decision of devices depends on the fraction of throughput they would get after quitting, on the quitting frame and on the quitting regret.