Modulation and SNR Optimization for Achieving Energy-Efficient Communications over Short-Range Fading Channels

It is commonly assumed that the energy consumption of wireless communications is minimized when low-order modulations such as BPSK are used. Nevertheless, the literature provides some evidence that low-order modulations are suboptimal for short transmission distances. No complete analysis on how the modulation size and transmission power must be chosen in order to achieve energy-efficient communications over fading channels has been reported so far. In this paper we provide this analysis by presenting a model that determines the energy consumed per payload bit transferred without error over fading channels of various statistics. We find that each modulation scheme has a single optimal signal-to-noise ratio (SNR) at which the energy consumption is minimized. The optimal SNR and the minimal energy consumption are larger for channels with less favorable error statistics. We also find that, if each modulations is operated at its optimal SNR, BPSK and QPSK are the optimal choices for long transmission distances, but as the transmission distance shortens the optimal modulation size grows to 16-QAM and even to 64-QAM. This result leads to showing that for short-range communications the lifetime of a typical low-power transceiver can be up to 500% longer by selecting the optimal constellation instead of BPSK.

[1]  Tianqi Wang,et al.  Link Energy Minimization in IR-UWB Based Wireless Networks , 2010, IEEE Transactions on Wireless Communications.

[2]  V. Kühn.  Wireless Communications over MIMO Channels: Applications to CDMA and Multiple Antenna Systems , 2006 .

[3]  Bülent Tavli,et al.  Optimizing physical-layer parameters for wireless sensor networks , 2011, TOSN.

[4]  Mani Srivastava,et al.  Energy-aware wireless microsensor networks , 2002, IEEE Signal Process. Mag..

[5]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[6]  Lei Zhao,et al.  Energy Efficient Design of WSN Based on an Accurate Power Consumption Model , 2007, 2007 International Conference on Wireless Communications, Networking and Mobile Computing.

[7]  Andreas Willig,et al.  Protocols and Architectures for Wireless Sensor Networks , 2005 .

[8]  George K. Karagiannidis,et al.  On the symbol error probability of general order rectangular qam in nakagami-m fading , 2006, IEEE Communications Letters.

[9]  Thomas H. Lee,et al.  The Design of CMOS Radio-Frequency Integrated Circuits: RF CIRCUITS THROUGH THE AGES , 2003 .

[10]  Jan M. Rabaey,et al.  The Energy-per-Useful-Bit Metric for Evaluating and Optimizing Sensor Network Physical Layers , 2006, 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks.

[11]  Andrea Conti,et al.  Wireless Sensor and Actuator Networks: enabling technologies, information processing and protocol design , 2008 .

[12]  M. Srivastava,et al.  Modulation scaling for energy aware communication systems , 2001, ISLPED'01: Proceedings of the 2001 International Symposium on Low Power Electronics and Design (IEEE Cat. No.01TH8581).

[13]  Elena Simona Lohan,et al.  An improved simulation model for Nakagami-m fading channels for satellite positioning applications , 2006 .

[14]  Mohamed-Slim Alouini,et al.  Digital Communication over Fading Channels: Simon/Digital Communications 2e , 2004 .

[15]  Anantha Chandrakasan,et al.  Energy efficient Modulation and MAC for Asymmetric RF Microsensor Systems , 2001, ISLPED '01.

[16]  Geoffrey G. Messier,et al.  Optimizing Physical Layer Energy Consumption for Wireless Sensor Networks , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[17]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[18]  Kirk Martinez,et al.  Deploying a sensor network in an extreme environment , 2006, IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC'06).

[19]  Deborah Estrin,et al.  Next Century Challenges: Mobile Networking for Smart Dust , 1999, MobiCom 1999.

[20]  Qin Wang,et al.  A Realistic Power Consumption Model for Wireless Sensor Network Devices , 2006, 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks.

[21]  Manel Gasulla,et al.  Powering wireless sensor nodes: Primary batteries versus energy harvesting , 2009, 2009 IEEE Instrumentation and Measurement Technology Conference.

[22]  Masanori Hamamura,et al.  Performance Tradeoff with Adaptive Frame Length and Modulation in Wireless Network , 2005, The Fifth International Conference on Computer and Information Technology (CIT'05).

[23]  Andrea J. Goldsmith,et al.  Energy-constrained modulation optimization , 2005, IEEE Transactions on Wireless Communications.

[24]  Tianqi Wang,et al.  Minimization of transceiver energy consumption in wireless sensor networks with AWGN channels , 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.