Bayesian Inference based communication receiver employs Markov-Chain Monte-Carlo (MCMC) sampling for performing several of the main receiver functionalities. The channel estimator estimates the multipath channel coefficients corresponding to a signal received with fading. The symbol demodulator demodulates the received signal according to a QAM constellation, so as to generate a demodulated signal, and estimate the transmitted symbols. The decoder reliably decodes the demodulated signals to generate an output bit sequence, factoring in redundancy induced at a certain code rate. A universal sampler may be configured to use MCMC sampling for generating estimates of channel coefficients, transmitted symbols or decoder bits, for aforementioned functionalities, respectively. The samples may then be used in one or more of the receiver tasks: channel estimation, signal demodulation, and decoding, which leads to a more scalable, reusable, power/area efficient receiver.