Efficient subcarrier and bit allocation under interference temperature constraints in OFDMA-based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum opportunistically. This paper addresses the problem of assigning subcarriers and bits in uplink for OFDMA-based cognitive radio networks. The objective is to maximize the system throughput in the presence of interference temperature constraint. In this paper, an adaptive bit loading algorithm is proposed first, which converges faster than the traditional bit loading methods. Then a computationally efficient dynamic subcarrier allocation algorithm is devised using Lagrangian method of optimization. The key contribution of this algorithm is in three aspects. Firstly, a simplified rule is derived to guide the subcarrier assignment. Secondly, table lookup search is used in each iteration. Thirdly, the multiplicative search of Lagrangian-multiplier speedups the convergence. Combining the two algorithms, the subcarrier and bits allocation scheme for uplink is presented. The performance of the proposed scheme is investigated by numerical results.