Multiple restarts mixed Gibbs sampling detector for large-scale antenna systems

This work proposes a low-complexity detector for medium- and high-order modulation large-scale multiple-input multiple-output (LS-MIMO) systems based on the set of Markov chain Monte-Carlo techniques. Such efficient signal detection algorithm is based on the mixed Gibbs sampling with multiple restar...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IET signal processing Ročník 13; číslo 3; s. 273 - 285
Hlavní autoři:	Mussi, Alex Miyamoto, Abrão, Taufik
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 01.05.2019
Témata:	aMGS‐based detector approximation theory averaged MGS channel configuration scenarios computational complexity coordinate updating process detection method efficient signal detection algorithm extra computational complexity higher‐order M‐QAM high‐order modulation large‐scale multiple‐input multiple‐output systems high‐order modulation LS‐MIMO systems large‐scale antenna systems low‐complexity detector Markov chain Monte‐Carlo techniques Markov processes medium‐order modulation LS‐MIMO MGS‐MR algorithm MIMO communication mixing ratio parameter Monte Carlo methods multiple restarts mixed Gibbs sampling detector numerical simulation quadrature amplitude modulation Research Article sample‐averaged approach signal detection signal sampling system loading wireless channels high-order modulation LS-MIMO systems mixing ratio parameter quadrature amplitude modulation medium-order modulation LS-MIMO averaged MGS Monte Carlo methods high-order modulation large-scale multiple-input multiple-output systems multiple restarts mixed Gibbs sampling detector higher-order M-QAM low-complexity detector signal sampling system loading wireless channels MIMO communication numerical simulation approximation theory Markov chain Monte-Carlo techniques signal detection extra computational complexity efficient signal detection algorithm channel configuration scenarios MGS-MR algorithm sample-averaged approach detection method Markov processes large-scale antenna systems aMGS-based detector computational complexity coordinate updating process
ISSN:	1751-9675, 1751-9683, 1751-9683
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	This work proposes a low-complexity detector for medium- and high-order modulation large-scale multiple-input multiple-output (LS-MIMO) systems based on the set of Markov chain Monte-Carlo techniques. Such efficient signal detection algorithm is based on the mixed Gibbs sampling with multiple restarts (MGS-MR) strategy with sample-averaged approach during the coordinate updating process, named averaged MGS (aMGS). The proposed strategy applies multiple samples average procedure to restrict the range of the random solution, which comes from the mixture proposed by the original MGS. Numerical simulation results considering higher-order M-QAM demonstrated that the proposed detection method can substantially improve the convergence of the MGS-MR algorithm, while no extra computational complexity is required. The proposed aMGS-based detector suitable for medium- and high-order modulation LS-MIMO further exhibits improved performance when the system loading is high, i.e. when (K/N) ≥ 0.75. In addition, the proposed numerical simulation analyses have shown that the optimal value of the mixing ratio parameter can vary regarding system and channel configuration scenarios, resulting somewhat different from the 1/2K value disseminated in the literature.
ISSN:	1751-9675 1751-9683 1751-9683
DOI:	10.1049/iet-spr.2018.5206