Advanced Spectrum Sensing for Multiple Transmitter Identification

摘要: Author(s): Urriza, Paulo Isagani Malijan | Advisor(s): Cabric, Danijela Abstract: The exponential growth in demand for mobile data has led to significant research efforts aimed at more efficient methods of utilizing the scarce RF spectrum resource. One potential solution this scarcity problem is Cognitive Radio (CR) which involves dynamic access a set unlicensed users occupy holes without causing degradation performance incumbent users. A key enabling technology CR networks accurate sensing aims learn radio environment order adapt transmission. Traditional techniques have mainly focused on determining only presence or absence licensed user. Recent work past few years shown however that detailed knowledge pertaining radio-scene analysis can be used improve networks. secondary user knows about active users, better it its transmission strategies. In work, we put forward concept advance takes multi-dimensional approach estimates various parameters transmitters through sensing, localization and tracking, modulation classification, PHY parameter estimation, MAC-layer classification. investigate elements such an system. Firstly, will look conventional detecting transmitting Primary Users. particular, study how detection could improved use cyclostationary feature made robust fading, noise uncertainty, co-channel interferers optimal multiple sensors. Second, attack classification argue critical piece information future cognitive systems. We present new type pattern algorithm based sampled distribution distance offers low computational complexity alternative maximum-likelihood Through our extensive analysis, derived form classifier applied problem. Finally, propose system 4th-order cumulants distinguishes between TDMA, OFDMA, CDMA contention-based schemes. addition, also able jointly perform with channel method. statistics cumulant large applications different areas including estimation number