An adaptive stochastic-based M-ary Modulation extension algorithm for short range wireless CRs

Abstract

Increasingly, unlicensed devices demand access to the licensed wireless spectrum, raising the problem of spectrum scarcity. This problem can be addressed by allowing unlicensed devices opportunistic access. Because opportunistic devices regard licensed users as interference, channel Signal to Interference Noise Ratio (SINR) is an important consideration for transmission. Cognitive Radio (CR) technology allows devices to sense spectrum and dynamically allocate bits to channels with good SINR. In this paper we introduce a stochastic modulation algorithm called the Cognitive Radio Stochastic Modulation (CRSM), for use as an extension to established M-ary Modulation schemes in underlay channels with poor SINR. In this modulation scheme, in additive channels, both the transmitting and receiving CR sense the magnitude and variance of the interference energy in the channel. The transmitter uses deterministic signals as unique identifiers in manipulating the variance of the signal detected at the receiver. The detected change in variance, measured at the receiver, is indicative of the presence or absence of a signal. In this paper we determine the critical regions for the CRSM and introduce a probability of error model.