Optimized Time Splitting to Maximize Rate in An Interference Alignment Based Network

In this paper, considering an interference alignment (IA) based network, a time splitting scheme for transmitting training and data symbols is optimized. The time allocated to transmit training symbols will affect the precision of channel estimation (CE) and thus the achievable rate as well as the duration for data symbol transmission. With the least square (LS) CE algorithm, the lower bound of achievable rate is carefully derived. Then we formulate an optimization problem to maximize the lower bound of achievable rate by optimizing the time splitting factor (TSF) . The existence of optimum is first proven. Then, regarding the complexity of solution, Taylor expansion is adopted to find the approximated optimal TSF. Numerical results are presented to validate the correctness and efficiency of the proposed scheme.