Training Beam Sequence Design for Millimeter-Wave MIMO Systems: A POMDP Framework

Cited 18 time in webofscience Cited 0 time in scopus
  • Hit : 254
  • Download : 0
In this paper, adaptive training beam sequence design for efficient channel estimation in large millimeter-wave (mmWave) multiple-input multiple-output (MIMO) channels is considered. By exploiting the sparsity in large mmWave MIMO channels and imposing a Markovian random walk assumption on the movement of the receiver and reflection clusters, the adaptive training beam sequence design and channel estimation problem is formulated as a partially observable Markov decision process (POMDP) problem that finds non-zero bins in a two-dimensional grid. Under the proposed POMDP framework, optimal and suboptimal adaptive training beam sequence design policies are derived. Furthermore, a very fast suboptimal greedy algorithm is developed based on a newly proposed reduced sufficient statistic to make the computational complexity of the proposed algorithm low to a level for practical implementation. Numerical results are provided to evaluate the performance of the proposed training beam design method. Numerical results show that the proposed training beam sequence design algorithms yield good performance.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2016-03
Language
English
Article Type
Article
Keywords

CHANNEL ESTIMATION; SPARSE MULTIPATH; SIGNAL-DESIGN; CAPACITY; MODELS; NOISE

Citation

IEEE TRANSACTIONS ON SIGNAL PROCESSING, v.64, no.5, pp.1228 - 1242

ISSN
1053-587X
DOI
10.1109/TSP.2015.2496241
URI
http://hdl.handle.net/10203/207619
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 18 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0