Joint grouping and scheduling in complexity-constrained broadcasting ad-hoc networks

We investigate broadcasting transmission in complexity-constrained networks. If each source transmits to multiple destinations by cooperative broadcasting, the complexity can be high due to multi-level superposition coding (encoding) and successive interference cancellation (decoding). Therefore, we partition the destinations into groups. A source transmits to a group by cooperative broadcasting, while different groups transmit in a time-division way. We restrict the number of levels involved in encoding and decoding. We suggest a sub-optimal algorithm to group the destinations and then optimize the scheduling for different groups such that the total transmit power is minimized. Moreover, there is a tradeoff between power and complexity. Simulation results indicate that by using at most 2–3 levels, the difference in average transmit power compared with using only one group per source is reduced to below 1.7dB. Furthermore, we analyze the convergence performance of our algorithm for different maximum number of levels. We also show that our algorithm only has a difference of below 1.7dB compared with the derived lower bound.