Strongly Asynchronous Massive Access Communications

Current wireless networks are designed to accommodate a fixed and finite number of active users at any point in time with a centralized controlling mechanism. Recent years however have witnessed an exponential growth in the number of wireless services and users, especially machine-to-machine communications, also known as the Internet of Things (IoT). IoT drastically differs from human-initiated communications, not only because of the massive number of devices that will potentially need access to the network at the same time, but also because of the type of traffic they are expected to generate (i.e., very bursty, low payload, and requiring both mission-critical reliability and latency). Next generation of IoT wireless networks must therefore to be able to serve a massive number of users where 1. each user demonstrates a bursty traffic pattern in which it transmits short packets of data infrequently to an access point, hence the conventional synchronicity assumption in the network is distorted; and 
 2. arbitrarily large number of users among a massive number of users may be active at each time, which need to be reliably identified and decoded; and 
 3. devices have strict energy consumption limits due to their characteristics; and 
 4. devices have strict latency requirements. 
 These innate features and requirements of the devices in IoT require a general reconsideration of the conventional information theoretic assumptions such as frame synchronization. This thesis is mostly focused on investigating challenges 1 and 2. More specifically we investigate the (information theoretic) fundamental technology-independent performance of a novel channel model that captures the essence of IoT communications. This thesis mainly consists of two parts. The first part is dedicated to the study of a single bursty user, which demonstrates a random-access traffic pattern–challenge 1. We propose a strongly asynchronous bursty user model based on the on-off uplink transmission pattern where the user may transmit sporadically within a large asynchronous window. In this model we do not assume the use of pilot signals and hence the receiver does not have a priori knowledge of the codeword transmission time. We therefore study the tradeoff between the size of the asynchronous window, the rate of transmission and the burstiness of the user. The second part is mostly focused on the study of the effects of the number of bursty users in IoT–challenge 2. In this regard, we propose a strongly asynchronous massive access model in which we allow the number of users to grow exponentially with the codeword blocklength. In this problem, we do not assume the use of pilot signals for either user identification nor synchronization purposes. We study the tradeoff between the number of users, their rate and the length of the asynchronous window.