Enabling grant-free multiple access through Successive Interference Cancellation

Internet of Things (IoT) is stirring a surge of interest in effective methods for sharing communication channels, with nodes transmitting sporadic, short messages. These messages are often related to control systems that collect sensor data to drive process actuation, such as in industries, autonomous vehicles, and environmental control. Traditional approaches that dominate wireless and cellular communications prove most effective when dealing with a limited number of concurrently active nodes, sending relatively large volumes of data. We address a different scenario where numerous nodes generate and transmit short messages according to non-periodic schedules. In such cases, random multiple access becomes the typical approach for sharing the communication channel. We propose a general modeling framework that enables the investigation of the impact of Successive Interference Cancellation (SIC) on two of the main random access paradigms, namely Slotted ALOHA (SA) and Carrier-Sense Multiple Access (CSMA). The key varying parameter is the target Signal to Interference plus Noise Ratio (SINR) at the receiver, directly tied to the spectral efficiency of the adopted coding and modulation scheme. Two different regimes are highlighted that bring the system to work at relative maxima of the sum-rate. We further investigate the impact of different transmission power settings and imperfect interference cancellation. Leveraging on the insight gained in the saturated node scenario, an adaptive algorithm is defined for the dynamic case, where the number of backlogged nodes varies over time. The numerical results provide evidence of a significant potential for grant-free multiple access, calling for practical algorithms to translate this promise into feasible realizations.