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Cross-Layer Energy-Efficiency Optimization of Packet Based Wireless MIMO Communication Systems

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Abstract

Energy in today’s short-range wireless communication is mostly spent on the analog- and digital hardware rather than on radiated power. Hence, purely information-theoretic considerations fail to achieve the lowest energy per information bit and the optimization process must carefully consider the overall transceiver. In this paper, we propose to perform cross-layer optimization, based on an energy-aware rate adaptation scheme combined with a physical layer that is able to properly adjust its processing effort to the data rate and the channel conditions to minimize the energy consumption per information bit. This energy proportional behavior is enabled by extending the classical system modes with additional configuration parameters at the various layers. Fine grained models of the power consumption of the hardware are developed to provide awareness of the physical layer capabilities to the medium access control layer. The joint application of the proposed energy-aware rate adaptation and modifications to the physical layer of an IEEE 802.11n system, improves energy-efficiency (averaged over many noise and channel realizations) in all considered scenarios by up to 44 %.

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Notes

  1. While data reception relies on accurate up-to-date channel state information, we have observed that channel characteristics relevant for RA remain stable over a long time.

  2. Important standards such as IEEE 802.11n already include this possibility.

  3. The payload phase of the transmission for low to medium throughput modes using a large L is much longer than the duration of the header shown in Fig. 2.

  4. Frame error rate remains independent of the number of aggregated frames (individual ACK in the same ACK frame). Still, overhead (PHY and ACK for small packets individually) can be avoided, which motivates aggregation of multiple frames.

  5. 32 transmission modes received with 4 receive chains without applying DVFS; 32 transmission modes with 4 receive chains using DVFS at the channel decoder; 24 transmission modes using 3 receive chains and DVFS wherever applicable; 16 transmission modes using 2 receive chains and DVFS wherever applicable; 8 transmission modes using 1 receive chain and DVFS wherever applicable.

  6. Practical implementation to estimate P e (ν) can be found in [4].

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Acknowledgments

This work was partially supported by the Hasler Foundation project WiLANCE and the EU Marie Curie DARE grant (no. 304186).

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Authors and Affiliations

  1. Telecommunications Circuits Laboratory TCL, École polytechnique fédérale de Lausanne EPFL, Station 11, Lausanne, ELG 030, Switzerland

    Christian Senning, Georgios Karakonstantis & Andreas Burg

  2. School of Electronics, Electrical Engineering and Computer Science, Queen’s University, Elmwood Avenue, Belfast, BT9 6AZ, UK

    Georgios Karakonstantis

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  1. Christian Senning
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Correspondence to Christian Senning.

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This paper extends the work published in ICASSP [32]

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Senning, C., Karakonstantis, G. & Burg, A. Cross-Layer Energy-Efficiency Optimization of Packet Based Wireless MIMO Communication Systems. J Sign Process Syst 85, 129–142 (2016). https://doi.org/10.1007/s11265-015-1003-7

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