Cooperative Feedback in Multi-Antenna Cognitive Networks

Abstract

Cognitive beamforming (CB) is a promising technique for efficient spectrum sharing between primary users (PUs) and secondary users (SUs) in a cognitive radio network. With CB, the multi-antenna SU transmitter is able to suppress the interference to the PU receiver and maximize the SU link throughput. Existing designs on CB assume that the SU transmitter either has prior knowledge of the interference channel to the PU receiver or can acquire this knowledge by observing the PU transmission. Both assumptions may be impractical. In this paper, we propose a new and practical design paradigm for CB based on finite-rate cooperative feedback from the PU receiver to the SU transmitter. Specifically, for the case of multiple-input single-output (MISO) SU channel and single- input single-output (SISO) PU channel, the PU receiver collaboratively communicates to the SU transmitter the channel direction information (CDI), namely the quantized shape of the SU- to-PU MISO channel, and the interference power control (IPC) signal, which specifies the maximum transmit power of the SU given the interference margin at the PU receiver. We present a CB algorithm for the SU transmitter based on the finite-rate CDI and IPC feedback. The resulting outage probability of the SU MISO channel is derived and shown to be lower-bounded by a function of the number of feedback bits, which is independent of the signal- to-noise ratio. Moreover, the optimal tradeoff between CDI and IPC feedback is analyzed.