Power-efficient resource allocation and quantization for TDMA using adaptive transmission and limited-rate feedback

Xin Wang, Antonio G. Marques, Georgios B. Giannakis

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Power-efficient scheduling and resource allocation are critical tasks for wireless sensor networks as well as commercial and tactical radios relying on IEEE access standards for power-limited communications. Tailored for such applications, this paper formulates and solves analytically novel convex optimization problems offering globally optimal user scheduling, as well as rate and power allocation for time-division multiple access (TDMA) in time-division-duplex or frequency-division-duplex operation. Through a limited-rate feedback link the access point provides quantized channel state information to the transmitters (Q-CSIT) based on which users adapt their modulation and code choices to the intended fading channel. When the quantizer needed to form the Q-CSIT is not prescribed, a joint allocation-quantization scheme is devised to minimize average transmit power subject to average rate and bit error rate constraints. The novel design couples adaptive transmission modes with quantization regions which are constructed to attain at least a local minimum of the average transmit power. Fairness in resource allocation is guaranteed by design. Transmit power and quantization region books are efficiently obtained offline while the online Q-CSIT based operation turns out to entail only a few feedback bits. Analysis and simulations include a perfect CSIT benchmark and reveal substantial power savings (as high as 15 dB) with low-overhead feedback.

Original languageEnglish (US)
Pages (from-to)4470-4485
Number of pages16
JournalIEEE Transactions on Signal Processing
Issue number9
StatePublished - 2008

Bibliographical note

Funding Information:
Manuscript received November 22, 2006; revised October 17, 2007. Published August 13, 2008. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Ananthram Swami. 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 Military Communications Conference, Washington DC, October 2006, and the IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, HI, April 2007.


  • Adaptive algorithms
  • Convex optimization
  • Multiple access
  • Power control
  • Quantization
  • Resource management
  • Scheduling
  • Wireless sensor networks


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