Transmit power adaptation for multiuser OFDM systems

Abstract

In this paper, we develop a transmit power adaptation method that maximizes the total data rate of multiuser orthogonal frequency division multiplexing (OFDM) systems in a downlink transmission. We generally formulate the data rate maximization problem by allowing that a subcarrier could be shared by multiple users. The transmit power adaptation scheme is derived by solving the maximization problem via two steps: subcarrier assignment for users and power allocation for subcarriers. We have found that the data rate of a multiuser OFDM system is maximized when each subcarrier is assigned to only one user with the best channel gain for that subcarrier and the transmit power is distributed over the subcarriers by the water-filling policy. In order to reduce the computational complexity in calculating water-filling level in the proposed transmit power adaptation method, we also propose a simple method where users with the best channel gain for each subcarrier are selected and then the transmit power is equally distributed among the subcarriers. Results show that the total data rate for the proposed transmit power adaptation methods significantly increases with the number of users owing to the multiuser diversity effects and is greater than that for the conventional frequencydivision multiple access (FDMA)-like transmit power adaptation schemes. Furthermore, we have found that the total data rate of the multiuser OFDM system with the proposed transmit power adaptation methods becomes even higher than the capacity of the AWGN channel when the number of users is large enough.

Joint Resource Block Assignment and Power Allocation Problem for Rate Maximization With QoS Guarantees in Multiservice Wireless

“…When the JRAPAP OPT solution reaches an outage rate of 10%, the differences in outage rate performance between JRAPAP OPT and RAP OPT are 22.4%, 16.1% and 17.25% in scenarios 1 to 3, respectively. Differently of the conclusions of [4], the power optimization jointly with RB assignment leads to important gains over the RB assignment optimization only. The main difference in the conclusions is that the RRA problem considered in [4] does not consider QoS or satisfaction constraints.…”

“…Differently of the conclusions of [4], the power optimization jointly with RB assignment leads to important gains over the RB assignment optimization only. The main difference in the conclusions is that the RRA problem considered in [4] does not consider QoS or satisfaction constraints. The solution of that problem in general grants terminals in better channel quality with most of the RBs.…”

“…Many works have addressed RRA for point-to-multipoint Orthogonal Frequency Division Multiple Access (OFDMA) networks with different objectives: unconstrained total data rate maximization [4], margin adaptive or power minimization [5], [6], rate adaptive or improved fairness [7], [8], among others. Focusing on QoS guarantees we highlight the total data rate maximization problem restricted to minimum data rate guarantees (MaxRate-MinReq).…”

“…In this case, the allocated power to the RB n assigned to terminal j is equal to λ j,n,m given by equation (4). The studied problem can be reformulated as follows…”

Modified Cooperative Subchannel Allocation Algorithms and PSO Based Power Allocation for an Alamouti Decode and Forward Relaying Protocol in Multiuser OFDMA Systems

“…In the selected literatures, downlink of non cooperative multi-users OFDMA systems is described using the dynamic Resource Allocation Algorithms (RAA) and optimization techniques. The aim of the RAA is either to achieve the constrained total transmits power with highest throughput and the minimum total transmitted power with constrained throughput [18]- [22]. Cooperative subcarrier allocation for AF Relaying Protocol gives the increased throughput and fairness among the multi-user OFDMA systems.…”