![]() ![]() This is achieved by calculating the equivalent evaporator temperature, from the evaporator refrigerant pressure, and subtracting the equivalent temperature from the leaving chilled liquid temperature to obtain a difference temperature which is then compared to a predetermined known temperature range representing normal functioning of the two sensors. By effectively comparing the output of one sensor relative to that of the other sensor, a faulty condition of either sensor may be detected. When sensors are employed to monitor the evaporator refrigerant pressure and the leaving chilled liquid temperature in an air conditioning system of the type having a liquid chiller, the sensor outputs will normally have a prescribed relationship with respect to each other as long as the sensors are functioning properly and regardless of the operating condition of the air conditioning system. In addition to providing vastly improved visual quality, the new estimator typically yields signal-to-noise ratio gains 12 dB or higher for hyperspectral imagery and functional magnetic resonance images. In contrast to optimal estimation, this new scheme does not require second-order signal statistics, making it well suited to many applications. The coefficient weighting is replaced with a wavelet-domain thresholding operation to result in an efficient estimation scheme for both stationary and nonstationary signals. An asymptotically optimal estimation scheme proposed here uses a 2-D discrete wavelet transform to approximately decorrelate the signal in space and the discrete Fourier transform to decorrelate between channels. Many scenarios exist where the required second-order signal and noise statistics are not known in which the decorrelation is difficult or expensive to calculate. Optimal estimation of a two-dimensional (2-D) multichannel signal ideally decorrelates the data in both channel and space and weights the resulting coefficients according to their SNR. The main contribution of our work is the development of the ML estimator, the corresponding Cramer–Rao lower bound, mean square error, signal to interference plus noise ratio, outage probability, bit error probability and the use of simulations to demonstrate the superior performance. Indeed, equispaced pilot symbols are used by maximum likelihood (ML) algorithm to derive channels estimator, and then equalizers are calculated and applied to improve receiver data detection. This paper addresses the joint channel estimation and data detection for cooperative communication systems. But, these advantages cannot be achieved without an efficient estimation of the channels which becomes more challenging for cooperative communications. Orthogonal frequency division multiplexing based cooperative system using Alamouti space–time block coding at relay node represents an alternative solution to achieve better connectivity and significant enhancement to the data rate in wireless fading channels.
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