We minimize average transmit power with finite-rate feedback for coherent communications in a wireless sensor network (WSN), where sensors communicate with a fusion center using adaptive modulation and coding over a wireless fading channel. By viewing the coherent WSN setup as a distributed space-time multiple-input single-output (MISO) system, we present optimal distributed beamforming and resource allocation strategies when the full (F-) channel state information at the transmitters (CSIT) is available through a feedback channel. We also develop optimal adaptive transmission policies and design optimal quantizers for the finite-rate feedback case where the sensors only have quantized (Q-) CSIT, or, each sensor has F-CSIT of its own link with the FC but only Q-CSIT of other sensors. Numerical results confirm that our novel finite-rate feedback-based strategies achieve near-optimal power savings based on even a small number of feedback bits.
Bibliographical noteFunding Information:
Manuscript received October 5, 2006; revised December 23, 2007. Published August 13, 2008. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Soren Holdt Jensen. Work in this paper was supported by the ARO Grant W911NF-05-1-0283 and was prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon. The work of A. G. Marques in this paper was partially supported by the C.A. Madrid Government Grant P-TIC-000223-0505. Parts of this paper were presented at the Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, October 2006, and the IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, HI, April 2007.
- Multiple-input single-output (MISO) systems
- Nonlinear optimization
- Power efficiency
- Resource allocation
- Wireless sensor networks (WSNs)