The future generation of wireless communication systems are expected to support high-speed data rate services as well as high spectrum efficiency in terms of capacity. There has been the need for more efficient use of scarce spectrum and a promising candidate is Orthogonal Frequency Division Multiplexing (OFDM) technique. The efficient utilization of spectrum requires Dynamic Resource Allocation (DRA) strategies with the flexibility to adapt to varying wireless network conditions, user requirements and Quality-of-Service (QoS) constraints, will be one of the major components for the design of a new air interface.
In multiuser OFDMA systems, DRA is a general strategy to assign subcarriers and power to different users in order to maximize system performance under some constraint, such as:
* Maximizing system throughput,
* Minimizing total transmitting power,
* Keeping fairness among users,
* Proportional fairness, etc.
Most of the previous approaches deal with maximization of system throughput (the total transmission rate) or minimization of the total transmitted power under users' QoS constraints. The formulated problem and their solutions are focused on the efficiency issue. These approaches benefit the users closer to the base station or with a higher power capability. On the other hand, another common problem in OFDMA systems is starvation of getting services due to the lack of system fairness. In this work, we emphasize on achieving the tradeoff between system throughput and fairness, i.e maximizing system throughput while keeping system fairness, under users' QoS and transmitted power constraints in downlink case.
Firstly, we propose practical, heuristic algorithms based on Proportional Fairness (PF) Scheduling adopted in single carrier systems to enhance system throughput and maintain system fairness as well as to satisfy users' QoS. Secondly, we formulate the PF optimization problem and analyze this problem using optimization theory. From necessary conditions for optimality, we propose an efficient subcarrier and power allocation with low complexity. The simulation results show that proposed algorithms can achieve the tradeoff between system throughput and fairness.