In this paper, we determine the optimal transmit strategy that achieves the capacity of a nt × 1 Multiple-Input Single-Output (MISO) and 2 × nr Multiple-Input-Multiple-Output (MIMO) channels under: (1) Per-group Power constraints (PGPC), i.e., sum power constraints on groups of antennas, and (2) Joint power constraints, e.g., sum power constraint and per-group power constraints. Sum power constraint over all antennas (SPC) and per-antenna power constraints (PAPC) are special cases of PGPC. The results in this paper generalize some recent results on MISO capacity under: (1) PAPC and (2) joint SPC and PAPC. PGPC and joint power constraints arise naturally in distributed antenna systems, and in systems with some practical implementation constraints. © 2017 IEEE.

Srikrishna Bhashyam

Department of Electrical Engineering

Channel coding

MIMO systems

Telecommunication links

Wireless telecommunication systems

DISTRIBUTED ANTENNA SYSTEM

JOINT POWER

MULTI-ANTENNA TRANSMISSION

MULTIPLE INPUT SINGLE OUTPUTS

MULTIPLE-INPUT MULTIPLE-OUTPUT CHANNELS

PER-ANTENNA POWER CONSTRAINTS

Power constraints

Antennas

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IIT Madras

Optimal Multi-Antenna Transmission with Per-Group and Joint Power Constraints

IEEE Wireless Communications and Networking Conference, WCNC

In this paper, we determine the optimal rank-constrained transmission strategy for the Multiple-Input Multiple-Output (MIMO) channel under Per-group Power constraints (PGPC). PGPC includes sum power constraint and per-antenna power constraints as special cases. We propose a Projected Factored Gradient Descent (PFGD) algorithm to obtain optimal rank-constrained strategy. If the rank constraint is greater than or equal to the rank of the unconstrained optimal covariance matrix, then the rank-constrained capacity coincides with the MIMO capacity under PGPC. The study of rank-constrained transmission under PGPC is important in the context of mmWave systems where the number of antennas could be large, but the number of streams is limited by the rank of the channel and the complexity of implementation of spatial multiplexing with a large number of streams. The proposed algorithm has lower complexity compared to standard approaches for semi-definite programs especially for low rank transmission. Numerical results are shown to study the behavior of the resulting rank-constrained capacity in the context of some existing mmWave channel models and to illustrate the convergence of the algorithm. For a special case where the channel has full column rank and the optimal covariance matrix is also full rank, we determine the MIMO capacity under PGPC analytically. © 2017 IEEE.

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Optimal multi-antenna transmission with per-group and joint power constraints

Journal	Data powered by TypesetIEEE Wireless Communications and Networking Conference, WCNC
Publisher	Data powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
ISSN	15253511
Open Access	No