Sum discrete-rate maximization with rate and power control in layered space-time coding

• Published in: IEEE transactions on communications Vol. 57; no. 3; pp. 789 - 800
• Main Authors: Layec, P., Visoz, R., Berthet, A.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.2009; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antenna accessories; Antenna feeds; Antennas; Applied sciences; Coding, codes; Computer Science; Control systems; Control theory; Decoding; Degrees of freedom; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Feedback; Information rates; Information Theory; Information, signal and communications theory; Interference cancellation; Mathematical analysis; Mathematics; Mean square error methods; MIMO systems; Noise reduction; Optimization; partial feedback; Power control; Quantization; Radiocommunications; Signal and communications theory; Signal, noise; sum rate optimization; Telecommunications; Telecommunications and information theory; Transmitting antennas; Space-time codes; Partition method; Noise reduction; Information rate; Transmitter; Optimization; Mean square error; Traffic control; MIMO system; Monte Carlo method; Flow rate regulation; Teletraffic; Decoding; Algorithm; Information transmission; Information rates; Quantization noise; Interference suppression; MIMO systems; Transmitting antenna; Power control; Traffic management; Signal processing; Numerical simulation; Reduced order model; sum rate optimization; Information theory; partial feedback
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2009.03.070392

This paper generalizes the information-theoretic optimality of minimum mean square error successive interference cancellation in layered space-time coding with rate and power control. Based on this derivation, a new concept relying on partial feedback is introduced, whose core idea is to exploit an additional degree of freedom relative to the partitioning of transmit antennas. Taking into account this additional degree of freedom, together with power control and decoding order, allows the reduction of the quantization noise induced by the use of finite discrete-rate sets at the transmitter. However, the simultaneous optimization of all those degrees of freedom proves to be computationally intensive and would result in a tremendous feedback load. Practical algorithms are thus proposed to achieve this optimization with a reasonable complexity and a limited amount of feedback. Monte-Carlo simulations show that those algorithms perform close to the theoretical limits.