Massive multiple-input-multiple-output (MIMO) systems use few hundred antennas to
simultaneously serve large number of wireless broadband terminals. It has been …

Emerging communication technologies, such as 5G and beyond, have introduced diverse
requirements that demand high performance and energy efficiency at all levels …

In this paper, we propose low-complexity algorithms based on Monte Carlo sampling for
signal detection and channel estimation on the uplink in large-scale multiuser multiple-input …

We introduce a revised derivation of the bitwise Markov Chain Monte Carlo (MCMC) multiple-
input multipleoutput (MIMO) detector. The new approach resolves the previously reported …

Multiuser/multiple-input-multiple-output detectors that use Markov chain Monte Carlo
(MCMC) simulation techniques to obtain likelihood of information bits have been developed …

The maximum information rates for bandlimited channels with direct detection are achieved
with joint detection and decoding (JDD), but JDD is often too complex to implement. Two …

In this paper, we consider a Markov chain Monte Carlo (MCMC) algorithm using Gibbs
sampling for signal detection in multiple input multiple output (MIMO) or code division …

The next generation of wireless networks will face different challenges from new scenarios.
The conventional Orthogonal Frequency Division Multiplexing (OFDM) has shown difficulty …

Within the framework of Monte Carlo simulation, this paper derives a Markov chain Monte
Carlo (MCMC) algorithm for efficient detection in multiple-input multiple-output (MIMO) …

In this paper, we propose low complexity algorithms based on Markov chain Monte Carlo
(MCMC) technique for signal detection and channel estimation on the uplink in large scale …