Matrix analysis
Convex Optimization
Ultra Wideband Wireless Communication
Ultra Wideband Wireless Communication
Energy-Detection UWB Receivers with Multiple Energy Measurements
IEEE Transactions on Wireless Communications
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
IEEE Transactions on Information Theory
Hi-index | 0.00 |
We have recently proposed a novel receiver for Ultra-Wide-band Impulse-Radio communication in bursty applications like Wireless Sensor Networks. The receiver, based on the principle of Compressed Sensing (CS), exploits the sparsity of the transmitted signal to achieve reliable demodulation. It acquires a modest number of projections of the received signal using analog correlators, and performs a joint decoding of the time of arrival and the data bits from these under-sampled measurements via an efficient quadratic program. In this paper we examine the robustness of this receiver to strong narrow-band interference (NBI) from primary licensed systems like WiMAX. First, by choosing frequency selective test functions in the front-end correlators, we ensure that the interferer can corrupt only a small fraction of the CS measurements. Then we implement a 'digital notch' by identifying and dropping those affected measurements during the quadratic programming reconstruction. The method is easily extended to multiple interferers without additional cost or complexity. We show that by implementing such a 'digital notch' the receiver becomes extremely robust to NBIs. For example its performance is negligibly affected even when the WiMAX customer premise equipment is at a distance comparable to that of the UWB transmitter and the base station is only ten times farther off, both very practical scenarios.