Joint spatial division and multiplexing for mm-Wave channels

Ansuman Adhikary, Ebrahim Al Safadi, Mathew K. Samimi, Rui Wang, Giuseppe Caire, Theodore S. Rappaport, Andreas F. Molisch

Research output: Contribution to journalArticlepeer-review


Massive MIMO systems are well-suited for mm-Wave communications, as large arrays can be built with reasonable form factors, and the high array gains enable reasonable coverage even for outdoor communications. One of the main obstacles for using such systems in frequency-division duplex mode, namely, the high overhead for the feedback of channel state information (CSI) to the transmitter, can be mitigated by the recently proposed joint spatial division and multiplexing (JSDM) algorithm. In this paper, we analyze the performance of this algorithm in some realistic propagation channels that take into account the partial overlap of the angular spectra from different users, as well as the sparsity of mm-Wave channels. We formulate the problem of user grouping for two different objectives, namely, maximizing spatial multiplexing and maximizing total received power in a graph-theoretic framework. As the resulting problems are numerically difficult, we proposed (sub optimum) greedy algorithms as efficient solution methods. Numerical examples show that the different algorithms may be superior in different settings. We furthermore develop a new, "degenerate" version of JSDM that only requires average CSI at the transmitter and thus greatly reduces the computational burden. Evaluations in propagation channels obtained from ray tracing results, as well as in measured outdoor channels, show that this low-complexity version performs surprisingly well in mm-Wave channels.

Original languageEnglish (US)
Article number6823686
Pages (from-to)1239-1255
Number of pages17
JournalIEEE Journal on Selected Areas in Communications
Issue number6
StatePublished - Jun 2014


  • 5G systems
  • JSDM
  • directional channel models
  • downlink beamforming
  • mm-Waves

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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