Resource allocation for SC‐FDMA based cognitive radio systems

Abstract

SUMMARYThis paper presents resource allocation algorithms for secondary user (SU) transmitters of single-carrier frequency division multiple access (SC-FDMA)-based cognitive radio systems. In addition to the conventional per-SU transmit power constraints, we also consider two types of interference constraints on SUs to protect the primary users links and thereby formulate two resource allocation problems. The first constraint relates to individual per-subcarrier interference power, whereas the second constraint corresponds to joint sum of interference power across all the subcarriers and SUs. In SC-FDMA system, a subcarrier can be allocated to one SU at a time (exclusivity constraint), and the multiple subcarriers allocated to an SU must be adjacent to each other (adjacency constraint). These constraints make the resource allocation problem prohibitively difficult to solve. We derive efficient power and subcarrier allocation algorithms via convex optimization techniques for both problems. We compare the results of our proposed algorithm with the existing schemes. Numerical results show that our algorithms can improve the system performance significantly.

Maximizing energy efficiency in SC‐FDMA uplink with QoS guarantees and user satisfaction

“…Since the number of allocated frequency resources depends on the QoS requirements as well as on the channel qualities, we can conclude that the modeling assumed by Nwamadi et al has a theoretical value, but it is not suitable for practical scenarios. The joint frequency resource and power allocation was considered several studies . Ahmad and Assaad proposed a low‐complexity subgradient‐based iterative algorithm using canonical duality theory.…”

“…Ahmad generalized the problem studied by Ahmad and Assaad by adding the functionality of adaptive modulation. In the work of Ahmad and Khan, the total data rate maximization problem was considered in a SC‐FDMA–based cognitive system and a low‐complexity solution was proposed, which divides the problem into two subproblems. The first subproblem is solved based on a greedy solution, while the second one is solved by using the subgradient method.…”