Optimal and Suboptimal Power Allocation Schemes for OFDM-based Cognitive Radio Systems

Cognitive Radio Systems: Multicarrier Modulation and Power Allocation Challenges

“…Therefore, in the interference limited scenario, allocation of power is based on the position of the subcarrier with respect to the PU's spectrum, i.e., more power should be allocated to distant subcarriers and vice versa. Therefore, in MCM based-CR systems, a judicious power loading scheme is required which should take into consideration the channel gain of the subcarrier as well as the spectral distance between the subcarrier and the PUs band [5]. When the same power allocation scheme is employed in both FBMC and OFDM systems, FBMC achieves higher capacity due to absence of CP which allows more available subcarriers and full control over spectral leakage [16].…”

“…In literature, optimal power assuming the Gaussian input distribution has been investigated in CR systems to maximize the capacity of the SU while keeping the interference introduced to the PU band within the tolerable range [5,17]. However, the Gaussian input assumption is unrealistic, whereas practical systems use FSA input distributions, (i.e., M-QAM).…”

“…One is introduced from the PU into the SU band, and the other is introduced from the SU into the PU band. The objective is to protect the PU from unacceptable interference, therefore, only interference introduced by the SU into the PU band is considered [5] and interference introduced by the PU into the SU is treated as a noise Simulation parameters: For practical reasons, LTE parameters are adopted and assumed that the available bandwidth for the SU transmission is 10 MHz which is divided into 50 resource blocks (RBs) [22]. A simplified path loss model, i.e., Q(r 0 /r) [23] is considered for simulations, where Q is constant, r 0 is reference distance and r is the distance between the SU transmitter and the PU receiver in meters.…”

“…The amount of interference introduced by the SU subcarriers into the PUs band depends on three factors, i.e., power allocated in that subcarrier, spectral distance between that particular subcarrier and the PUs band, and location of the PU (whether it is detectable or not by the SU). To address this issue, different power allocation schemes have been proposed in the literature where Gaussian inputs are assumed to maximize the SU data rate for a given interference threshold values [4,5]. However, the Gaussian input assumption is unrealistic, whereas, Finite Symbol Alphabet (FSA) input is more applicable to practical systems.…”

Optimal Power Allocation and Power Constraint in OFDM-Based Cognitive Radio Systems

“…G. Bansal et al [5] studied the resource allocation plan base on OFDM in CR network. Moreover, according to the traditional power allocation scheme (such as water-filling algorithm), more power should be distributed to the sub carrier with higher quality channel.…”