In this paper, we propose an analytical model for estimating the irreducible bit error ratio (BER) in multipath channel with small-extent delay dispersion, such as indoor, where the signal-to-noise ratio is high, implying dominance of intersymbol interference as error-generating mechanism. Both channel and overall orthogonal frequency-division multiplexing (OFDM) symbols are modeled stochastically, resulting with novel expression for the residual BER prediction that is shown to analytically distinguish power delay profiles with equal delay spreads but having different profile shapes. In addition, the model could simply accommodate insertion of cyclic prefix onto the OFDM symbol, providing a means for either testing adequacy of any applied (standard) cyclic prefix length or finding its optimal value as a compromise between the performance enhancement achieved by inserting cyclic prefix and the consequently added redundancy. Finally, the model was modified as to include the analysis of effects of subcarrier frequency inaccuracy or Doppler shift, by adding additional equivalent delay dispersion with equal effect on BER degradation, while considering the system virtually free of carrier frequency offset. All analytically achieved results and conclusions are tested and successfully verified by conducted extensive Monte Carlo simulations.
This paper addresses the problem of locating a single source from noisy received signal-strength (RSS) measurements in wireless sensor networks (WSNs). To overcome the non-convexity of the maximum likelihood (ML) optimization problem, we provide an efficient convex relaxation that is based on the second order cone programming (SOCP), for both cases of known and unknown source transmit power, and we use a simple iterative procedure to solve the problem when the transmit power and the path loss exponent (PLE) are simultaneously unknown. Simulation results demonstrate that the new approach outperforms the existing ones in terms of the estimation accuracy, while in terms of the complexity, it represents a good balance when compared to the existing approaches 1 .
Optical time-domain reflectometer (OTDR) is used to characterize fiber optic links by identifying and localizing various refractive and reflective events such as breaks, splices, and connectors, and measuring insertion/return loss and fiber length. Essentially, OTDR inserts a pulsed signal into the fiber, from which a small portion that is commonly referred to as Rayleigh backscatter, is continuously reflected back with appropriate delays of the reflections expressed as the power loss versus distance, by conveniently scaling the time axis. Specifically, for long-distance events visibility and measurement accuracy, the crucial OTDR attribute is dynamic range, which determines how far downstream the fiber can the strongest transmitted optical pulse reach. As many older-generation but still operable OTDR units have insufficient dynamic range to test the far-end of longer fibers, we propose a simple and cost-effective solution to reactivate such an OTDR by inserting a low-noise high-gain optical preamplifier in front of it to lower the noise figure and thereby the noise floor. Accordingly, we developed an appropriate dynamic range and distance span extension model which provided the exemplar prediction values of 30 dB and 75 km, respectively, for the fiber under test at 1550 nm. These values were found to closely match the dynamic range and distance span extensions obtained for the same values of the relevant parameters of interest by the preliminary practical OTDR measurements conducted with the front-end EDFA optical amplifier, relative to the measurements with the OTDR alone. This preliminary verifies that the proposed concept enables a significantly longer distance span than the OTDR alone. We believe that the preliminary results reported here could serve as a hint and a framework for a more comprehensive test strategy in terms of both test diversification and repeating rate, which can be implemented in a network operator environment or professional lab.
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