Adaptive Pricing for Efficient Spectrum Sharing in MIMO Systems

The concept of cognitive radio with many promising features like spectrum sensing, dynamic spectrum access has the potential to greatly improve the spectral efficiency. In this paper, we consider the problem of spectrum-hole sharing, i.e., vacant channel and power allocation to multiple cognitive radio (CR) users who coexist in a network. These CR users are equipped with multiple antennas at both transmitters and receivers. A non-cooperative game with pricing formulation is adopted to tackle the problem. We show that, to achieve the maximum sum data rate, each user should incorporate a vector of adaptive pricing factors on each channel based on transmission power of other users. The formula of optimal pricing is derived and a distributed iterative algorithm is designed through small amount of information exchange between users. The simulation results demonstrate the performance gain of the proposed algorithm over the classical iterative water-filling algorithm without pricing and intuitive pricing formulations.