Energy-constrained modulation optimization
TL;DR: It is shown that up to 80% energy savings is achievable over nonoptimized systems and that the benefit of coding varies with the transmission distance and the underlying modulation schemes.
Abstract: Wireless systems where the nodes operate on batteries so that energy consumption must be minimized while satisfying given throughput and delay requirements are considered. In this context, the best modulation strategy to minimize the total energy consumption required to send a given number of bits is analyzed. The total energy consumption includes both the transmission energy and the circuit energy consumption. For uncoded systems, by optimizing the transmission time and the modulation parameters, it is shown that up to 80% energy savings is achievable over nonoptimized systems. For coded systems, it is shown that the benefit of coding varies with the transmission distance and the underlying modulation schemes.
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Proceedings Article•
01 Jan 2005
TL;DR: This book aims to provide a chronology of key events and individuals involved in the development of microelectronics technology over the past 50 years and some of the individuals involved have been identified and named.
Abstract: Alhussein Abouzeid Rensselaer Polytechnic Institute Raviraj Adve University of Toronto Dharma Agrawal University of Cincinnati Walid Ahmed Tyco M/A-COM Sonia Aissa University of Quebec, INRSEMT Huseyin Arslan University of South Florida Nallanathan Arumugam National University of Singapore Saewoong Bahk Seoul National University Claus Bauer Dolby Laboratories Brahim Bensaou Hong Kong University of Science and Technology Rick Blum Lehigh University Michael Buehrer Virginia Tech Antonio Capone Politecnico di Milano Javier Gómez Castellanos National University of Mexico Claude Castelluccia INRIA Henry Chan The Hong Kong Polytechnic University Ajit Chaturvedi Indian Institute of Technology Kanpur Jyh-Cheng Chen National Tsing Hua University Yong Huat Chew Institute for Infocomm Research Tricia Chigan Michigan Tech Dong-Ho Cho Korea Advanced Institute of Science and Tech. Jinho Choi University of New South Wales Carlos Cordeiro Philips Research USA Laurie Cuthbert Queen Mary University of London Arek Dadej University of South Australia Sajal Das University of Texas at Arlington Franco Davoli DIST University of Genoa Xiaodai Dong, University of Alberta Hassan El-sallabi Helsinki University of Technology Ozgur Ercetin Sabanci University Elza Erkip Polytechnic University Romano Fantacci University of Florence Frank Fitzek Aalborg University Mario Freire University of Beira Interior Vincent Gaudet University of Alberta Jairo Gutierrez University of Auckland Michael Hadjitheodosiou University of Maryland Zhu Han University of Maryland College Park Christian Hartmann Technische Universitat Munchen Hossam Hassanein Queen's University Soong Boon Hee Nanyang Technological University Paul Ho Simon Fraser University Antonio Iera University "Mediterranea" of Reggio Calabria Markku Juntti University of Oulu Stefan Kaiser DoCoMo Euro-Labs Nei Kato Tohoku University Dongkyun Kim Kyungpook National University Ryuji Kohno Yokohama National University Bhaskar Krishnamachari University of Southern California Giridhar Krishnamurthy Indian Institute of Technology Madras Lutz Lampe University of British Columbia Bjorn Landfeldt The University of Sydney Peter Langendoerfer IHP Microelectronics Technologies Eddie Law Ryerson University in Toronto
7,826 citations
TL;DR: This survey presents a comprehensive review of the recent literature since the publication of a survey on sensor networks, and gives an overview of several new applications and then reviews the literature on various aspects of WSNs.
5,626 citations
Cites background from "Energy-constrained modulation optim..."
...Modulation optimization: In [111], a detailed analysis of the tradeoff in transmission energy, circuit energy, transmission time, and constellation size for both uncoded and coded M-QAM and M-FSK is studied....
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TL;DR: This work considers radio applications in sensor networks, where the nodes operate on batteries so that energy consumption must be minimized, while satisfying given throughput and delay requirements, and analyses the best modulation and transmission strategy to minimize the total energy consumption.
Abstract: We consider radio applications in sensor networks, where the nodes operate on batteries so that energy consumption must be minimized, while satisfying given throughput and delay requirements. In this context, we analyze the best modulation and transmission strategy to minimize the total energy consumption required to send a given number of bits. The total energy consumption includes both the transmission energy and the circuit energy consumption. We first consider multi-input-multi-output (MIMO) systems based on Alamouti diversity schemes, which have good spectral efficiency but also more circuitry that consumes energy. We then extend our energy-efficiency analysis of MIMO systems to individual single-antenna nodes that cooperate to form multiple-antenna transmitters or receivers. By transmitting and/or receiving information jointly, we show that tremendous energy saving is possible for transmission distances larger than a given threshold, even when we take into account the local energy cost necessary for joint information transmission and reception. We also show that over some distance ranges, cooperative MIMO transmission and reception can simultaneously achieve both energy savings and delay reduction.
1,728 citations
Cites background or methods or result from "Energy-constrained modulation optim..."
...where with the drain efficiency [9] of the RF power amplifier and the peak-to-average ratio (PAR), which is dependent on the modulation scheme and the associated constellation size [6]....
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...Similar to the SISO case discussed in [4]–[6], the total average power consumption along the signal path can be divided into two main components: the power consumption of all the power amplifiers and the power consumption of all other circuit blocks ....
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...The energy cost per bit for local information flow on the Tx side, denoted as , and the energy cost per bit for local information flow on the Rx side, denoted as can be calculated according to the result we obtained for SISO communication links in AWGN channels (see [4] and [6])....
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...The related circuit and system parameters are defined in Table I, where the power consumption values of various circuit blocks are quoted from [9]–[12] as was also used in [4]–[6]....
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...Algorithms proposed in [6] can be used to approximate this problem as a convex one, which can then be efficiently solved [13]....
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TL;DR: These technologies such as multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM), cognitive radio, network coding, cooperative communication, etc.
Abstract: Reducing energy consumption in wireless communications has attracted increasing attention recently. Advanced physical layer techniques such as multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM), cognitive radio, network coding, cooperative communication, etc.; new network architectures such as heterogeneous networks, distributed antennas, multi-hop cellulars, etc.; as well as radio and network resource management schemes such as various cross-layer optimization algorithms, dynamic power saving, multiple radio access technologies coordination, etc. have been proposed to address this issue. In this article, we overview these technologies and present the state-of-the-art on each aspect. Some challenges that need to be solved in the area are also described.
954 citations
Cites background from "Energy-constrained modulation optim..."
...It is indicated in [58] that femtocellular networks must deal with additional timing and synchronization, as well as interference management issues, which cause more signaling overhead and potentially more energy consumption....
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References
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Book•
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TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Abstract: Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.
33,341 citations
TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
Abstract: Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.
10,296 citations
01 Nov 1985
TL;DR: This month's guest columnist, Steve Bible, N7HPR, is completing a master’s degree in computer science at the Naval Postgraduate School in Monterey, California, and his research area closely follows his interest in amateur radio.
Abstract: Spread Spectrum It’s not just for breakfast anymore! Don't blame me, the title is the work of this month's guest columnist, Steve Bible, N7HPR (n7hpr@tapr.org). While cruising the net recently, I noticed a sudden bump in the number of times Spread Spectrum (SS) techniques were mentioned in the amateur digital areas. While QEX has discussed SS in the past, we haven't touched on it in this forum. Steve was a frequent cogent contributor, so I asked him to give us some background. Steve enlisted in the Navy in 1977 and became a Data Systems Technician, a repairman of shipboard computer systems. In 1985 he was accepted into the Navy’s Enlisted Commissioning Program and attended the University of Utah where he studied computer science. Upon graduation in 1988 he was commissioned an Ensign and entered Nuclear Power School. His subsequent assignment was onboard the USS Georgia, a trident submarine stationed in Bangor, Washington. Today Steve is a Lieutenant and he is completing a master’s degree in computer science at the Naval Postgraduate School in Monterey, California. His areas of interest are digital communications, amateur satellites, VHF/UHF contesting, and QRP. His research area closely follows his interest in amateur radio. His thesis topic is Multihop Packet Radio Routing Protocol Using Dynamic Power Control. Steve is also the AMSAT Area Coordinator for the Monterey Bay area. Here's Steve, I'll have some additional comments at the end.
8,781 citations
Journal Article•
TL;DR: This expanded and thoroughly revised edition of Thomas H. Lee's acclaimed guide to the design of gigahertz RF integrated circuits features a completely new chapter on the principles of wireless systems.
Abstract: 53 ■ IEEE CIRCUITS & DEVICES MAGAZINE ■ NOVEMBER/DECEMBER 2005 THE DESIGN OF CMOS RADIOFREQUENCY INTEGRATED CIRCUITS, 2ND ED By Thomas Lee, Cambridge University Press, 2003. All-CMOS radio transceivers and system-on-a-chip are rapidly making inroads into a wireless market that, for years, was dominated by bipolar solutions. On wireless LAN and Bluethooth, RF CMOS is especially dominant, and it is becoming also in GSM cellular and GPS receivers. Hence, books that cover this widespread domain respond to a real need. The first edition of this book, published on 1998, was a pioneering textbook on the field of RF CMOS design. This second edition is a very interesting and upgraded version that includes new material and revised topics. In particular, it now includes a chapter on the fundamentals of wireless systems. The chapter on IC components is greatly expanded and now follows that on passive RLC components. The chapter on MOS devices has been updated since it includes the understanding of the model for the shorth-channel MOS and considers and discusses the scaling trends and its impact on the next several years. It has also expanded the topic of power amplifiers; indeed, it now also covers techniques for linearization and efficiency enhancement. Low-noise amplifiers, oscillators, and phase noise are now expanded and treated with more detail. Moreover, the chapter on transceiver architectures now includes much more detail, especially on direct-conversion architecture. Finally, additional commentary on practical details on simulations, floorplanning, and packaging has been added. The first edition of this book widely covered all the main arguments needed in the CMOS design context and provided a bridge between system and circuit issues. This second edition, which is upgraded and improved, is really useful, both in the industry and academia, for the new generation of RF engineers. Indeed, it is suited for students taking courses on RF design and is a valuable reference for practicing engineers. Of course, the arguments treated in the textbook lead up to low-frequency analog design IC topics. Hence, readers have to be intimately familiar with that subject. The book is divided into 20 chapters: 1) A Nonlinear History of Radio 2) Overview of Wireless Principles 3) Passive RLC Networks 4) Characteristics of Passive IC Components 5) A Review of MOS Device Physics; 6) Distributed Systems 7) The Smith Chart and S-Parameters 8) Bandwidth Estimation Techniques 9) High-Frequency Amplifier Design 10) Voltage References and Biasing 11) Noise 12) LNA Design 13) Mixers 14) Feedback Amplifiers 15) RF Power Amplifiers 16) Phase Locked Loop 17) Oscillators and Synthesizers 18) Phase Noise 19) Architectures 20) RF Circuits Through the Ages. Moreover, it contains over 100 circuit diagrams and many homework problems. Gaetano Palumbo
3,949 citations
"Energy-constrained modulation optim..." refers background or methods in this paper
...Since the leaking power con sumption is usually much smaller than the power consumption in the active mode (which may not be true for deep sub-micron CMOS technology [11]), it is neglected in our model....
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...For the low-IF structure assumed i n our model, the sampling frequency can be approximately take n asfs = 2(2B + fcor), wherefcor is the corner frequency of the 1/f noise [11] andfIF = B + fcor is the lowest possible value for IF such that the signal is not severely affected by the 1/f noise....
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...Specifically, Pc0 consists of the mixer power consumption Pmix, the frequency synthesizer power consumptionPsyn, the LNA power consumption PLNA, the active filter power consumption Pfilt at the transmitter, the active filter power consumption Pfilr at the receiver, the IFA power consumptionPIFA, the DAC power consumption PDAC , the ADC power consumptionPADC , and the power amplifier power consumptionPamp, wherePamp = αPt and α = ξ η − 1 with η the drain efficiency [11] of the RF power amplifier and ξ the Peak to Average Ratio (PAR), which is dependent on the modulation scheme and the associated constellation size....
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...The circ uitry for such a radio is composed of several blocks described in [11], [15], [16], and [17]....
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...35, which is a practical value for class-A RF power amplifiers [11] (Due to the linearity requirement for amplifying MQAM signals, class-A power amplifiers are usually used....
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