Constant Envelope MIMO-OFDM Precoding for Low Complexity Large-Scale Antenna Array Systems

• Published in: IEEE transactions on wireless communications Vol. 19; no. 12; pp. 7973 - 7985
• Main Authors: Domouchtsidis, Stavros, Tsinos, Christos G., Chatzinotas, Symeon, Ottersten, Bjorn
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antenna arrays; Antennas; Constant-envelope precoding; Frequency-domain analysis; large MIMO; Least squares method; low-PAR precoding; MIMO communication; MIMO-OFDM; OFDM; Optimization; Orthogonal Frequency Division Multiplexing; Phase shifters; Power amplifiers; Power consumption; Power management; Precoding; Time-domain analysis; Transmitting antennas; Wireless communication
• ISSN: 1536-1276; 1558-2248; 1558-2248
• DOI: 10.1109/TWC.2020.3018431

Herein, we consider constant envelope precoding in a multiple-input multiple-output orthogonal frequency division multiplexing system (CE MIMO-OFDM) for frequency selective channels. In CE precoding the signals for each transmit antenna are designed to have constant amplitude regardless of the channel realization and the information symbols that must be conveyed to the users. This facilitates the use of power-efficient components, such as phase shifters (PS) and nonlinear power amplifiers, which are key for the feasibility of large-scale antenna array systems because of their low cost and power consumption. The CE precoding problem is firstly formulated as a least-squares problem with a unit modulus constraint and solved using an algorithm based on coordinate descent. The large number of optimization variables in the case of the MIMO-OFDM system motivates the search for a more computationally efficient solution. To tackle this, we reformulate the CE precoding design into an unconstrained nonlinear least-squares problem, which is solved efficiently using the Gauss-Newton algorithm. Simulation results underline the efficiency of the proposed solutions and show that they outperform state of the art techniques.