Sum Rate Maximization for Cognitive MISO Broadcast Channels: Beamforming Design and Large Systems Analysis

This paper considers the ergodic weighted sum rate maximization (WSRMax) problem for an underlay cognitive radio multiple input single output (MISO) broadcast channel. In this setting, a secondary network, consisting of a base-station with M transmit antennas and K single-antenna secondary users (SUs), is allowed to share the same spectrum with a primary user (PU), under an average total transmit power (ATTP) constraint and an average interference power (AIP) constraint at the PU receiver. We show that the ATTP constraint always remains active, and as the maximum ATTP Pav→ ∞, the ergodic WSR approaches infinity similar to conventional non-CR networks. We propose a novel low-complexity suboptimal beamforming scheme termed "Partially-Projected & Regularized Zero-Forcing Beamforming" (PP-RZFBF) with a close-form beamformer, by combining the regularized zero-forcing (RZF) with the channel projection idea, to achieve a tradeoff between maximizing secondary throughput and suppressing secondary multiuser interference as well as the interference on PU. In order to analyze and optimize the performance of this scheme, we employ the large system analysis technique, in the limit as M and K approach infinity with a fixed ratio r=KM. This allows us to derive deterministic limiting approximations for the PP-RZFBF problem which enables us to determine asymptotically optimal beamformers for PP-RZFBF. In the large system limit, for the PP-RZFBF scheme, we also find that as Pav→ ∞, the interference on PU caused by the secondary transmission is asymptotically removed. A special suboptimal beamforming scheme called "CZFBF" is also considered, which involves zero forcing all the interference, including the secondary multiuser interference as well as the interference imposed on PU. Various interesting comparisons between PP-RZFBF and CZFBF are provided. Numerical simulations illustrate that the asymptotically optimal beamformers- for the PP-RZFBF scheme provide an excellent performance even for finite-sized systems.