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Proceedings Article

Wireless communications

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
Citations
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Journal ArticleDOI
TL;DR: The proposed model is pessimistic (a lower bound on coverage) whereas the grid model is optimistic, and that both are about equally accurate, and the proposed model may better capture the increasingly opportunistic and dense placement of base stations in future networks.
Abstract: Cellular networks are usually modeled by placing the base stations on a grid, with mobile users either randomly scattered or placed deterministically. These models have been used extensively but suffer from being both highly idealized and not very tractable, so complex system-level simulations are used to evaluate coverage/outage probability and rate. More tractable models have long been desirable. We develop new general models for the multi-cell signal-to-interference-plus-noise ratio (SINR) using stochastic geometry. Under very general assumptions, the resulting expressions for the downlink SINR CCDF (equivalent to the coverage probability) involve quickly computable integrals, and in some practical special cases can be simplified to common integrals (e.g., the Q-function) or even to simple closed-form expressions. We also derive the mean rate, and then the coverage gain (and mean rate loss) from static frequency reuse. We compare our coverage predictions to the grid model and an actual base station deployment, and observe that the proposed model is pessimistic (a lower bound on coverage) whereas the grid model is optimistic, and that both are about equally accurate. In addition to being more tractable, the proposed model may better capture the increasingly opportunistic and dense placement of base stations in future networks.

3,309 citations


Cites background from "Wireless communications"

  • ...Tractable analysis can sometimes be achieved for a fixed user with a small number of interfering base stations, for example by considering the “worst-case” user location – the cell corner – and finding the signal-to-interference-plus-noise ratio (SINR) [12], [13]....

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Journal ArticleDOI
TL;DR: This paper proposes S-MAC, a medium access control (MAC) protocol designed for wireless sensor networks that enables low-duty-cycle operation in a multihop network and reveals fundamental tradeoffs on energy, latency and throughput.
Abstract: This paper proposes S-MAC, a medium access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect sensor networks to be deployed in an ad hoc fashion, with nodes remaining largely inactive for long time, but becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in several ways: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important. S-MAC uses a few novel techniques to reduce energy consumption and support self-configuration. It enables low-duty-cycle operation in a multihop network. Nodes form virtual clusters based on common sleep schedules to reduce control overhead and enable traffic-adaptive wake-up. S-MAC uses in-channel signaling to avoid overhearing unnecessary traffic. Finally, S-MAC applies message passing to reduce contention latency for applications that require in-network data processing. The paper presents measurement results of S-MAC performance on a sample sensor node, the UC Berkeley Mote, and reveals fundamental tradeoffs on energy, latency and throughput. Results show that S-MAC obtains significant energy savings compared with an 802.11-like MAC without sleeping.

2,843 citations


Cites background from "Wireless communications"

  • ...wherePt is the transmission power, and β is an environmentdependent constant normally between 2–5 [23]....

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Posted Content
TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management and recent standardization efforts on MEC are introduced.
Abstract: Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

2,289 citations


Cites background from "Wireless communications"

  • ...To be specific, wireless channels differ from the wired counterparts in the following key aspects [61]: 1) Due to atmospheric ducting, reflection and refraction from scattering objects in the environment (e....

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Journal ArticleDOI
08 Nov 2004
TL;DR: An overview of MIMO wireless technology covering channel models, performance limits, coding, and transceiver design is provided, in principle, to meet the 1 Gb/s data rate requirement with a single-transmit single-receive antenna wireless system.
Abstract: High data rate wireless communications, nearing 1 Gb/s transmission rates, is of interest in emerging wireless local area networks and home audio/visual networks. Designing very high speed wireless links that offer good quality-of-service and range capability in non-line-of-sight (NLOS) environments constitutes a significant research and engineering challenge. Ignoring fading in NLOS environments, we can, in principle, meet the 1 Gb/s data rate requirement with a single-transmit single-receive antenna wireless system if the product of bandwidth (measured in hertz) and spectral efficiency (measured in bits per second per hertz) is equal to 10/sup 9/. A variety of cost, technology and regulatory constraints make such a brute force solution unattractive, if not impossible. The use of multiple antennas at transmitter and receiver, popularly known as multiple-input multiple-output (MIMO) wireless, is an emerging cost-effective technology that offers substantial leverages in making 1 Gb/s wireless links a reality. The paper provides an overview of MIMO wireless technology covering channel models, performance limits, coding, and transceiver design.

2,154 citations


Cites background from "Wireless communications"

  • ...If the bandwidth-delay spread product of the channel satisfies , the channel is generally said to be frequency selective [19]....

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Proceedings ArticleDOI
27 Aug 2013
TL;DR: The design and implementation of the first in-band full duplex WiFi radios that can simultaneously transmit and receive on the same channel using standard WiFi 802.11ac PHYs are presented and achieves close to the theoretical doubling of throughput in all practical deployment scenarios.
Abstract: This paper presents the design and implementation of the first in-band full duplex WiFi radios that can simultaneously transmit and receive on the same channel using standard WiFi 802.11ac PHYs and achieves close to the theoretical doubling of throughput in all practical deployment scenarios. Our design uses a single antenna for simultaneous TX/RX (i.e., the same resources as a standard half duplex system). We also propose novel analog and digital cancellation techniques that cancel the self interference to the receiver noise floor, and therefore ensure that there is no degradation to the received signal. We prototype our design by building our own analog circuit boards and integrating them with a fully WiFi-PHY compatible software radio implementation. We show experimentally that our design works robustly in noisy indoor environments, and provides close to the expected theoretical doubling of throughput in practice.

2,084 citations


Additional excerpts

  • ...Categories and Subject Descriptors C.2.1 [Computer Communication Networks]: Network Architecture and Design—Wireless communication General Terms: Algorithms, Design, Experimentation, Performance Keywords: Full Duplex, Interference Cancellation, Non-linear Cancellation...

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References
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Journal ArticleDOI
Siavash Alamouti1
TL;DR: This paper presents a simple two-branch transmit diversity scheme that provides the same diversity order as maximal-ratio receiver combining (MRRC) with one transmit antenna, and two receive antennas.
Abstract: This paper presents a simple two-branch transmit diversity scheme. Using two transmit antennas and one receive antenna the scheme provides the same diversity order as maximal-ratio receiver combining (MRRC) with one transmit antenna, and two receive antennas. It is also shown that the scheme may easily be generalized to two transmit antennas and M receive antennas to provide a diversity order of 2M. The new scheme does not require any bandwidth expansion or any feedback from the receiver to the transmitter and its computation complexity is similar to MRRC.

13,706 citations


"Wireless communications" refers background or methods in this paper

  • ...The signal envelope in this case can be shown to have a Rician distribution [9], given by...

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  • ...Capacity for time-varying channels under assumptions other than these three are discussed in [8, 9]....

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  • ...The joint pdf of z and ż for Rician fading was derived in [9] and can also be found in [11]....

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  • ...Comparison of the ray tracing method with empirical data shows it to accurately model received signal power in rural areas [10], along city streets where both the transmitter and receiver are close to the ground [8, 7, 10], or in indoor environments with appropriately adjusted diffraction coefficients [9]....

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  • ...This model has been used to characterize the mechanism by which signals are diffracted around street corners, which can result in path loss exceeding 100 dB for some incident angles on the wedge [9, 37, 38, 39]....

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Book
01 Jan 1963
TL;DR: A simple but nonoptimum decoding scheme operating directly from the channel a posteriori probabilities is described and the probability of error using this decoder on a binary symmetric channel is shown to decrease at least exponentially with a root of the block length.
Abstract: A low-density parity-check code is a code specified by a parity-check matrix with the following properties: each column contains a small fixed number j \geq 3 of l's and each row contains a small fixed number k > j of l's. The typical minimum distance of these codes increases linearly with block length for a fixed rate and fixed j . When used with maximum likelihood decoding on a sufficiently quiet binary-input symmetric channel, the typical probability of decoding error decreases exponentially with block length for a fixed rate and fixed j . A simple but nonoptimum decoding scheme operating directly from the channel a posteriori probabilities is described. Both the equipment complexity and the data-handling capacity in bits per second of this decoder increase approximately linearly with block length. For j > 3 and a sufficiently low rate, the probability of error using this decoder on a binary symmetric channel is shown to decrease at least exponentially with a root of the block length. Some experimental results show that the actual probability of decoding error is much smaller than this theoretical bound.

11,592 citations


"Wireless communications" refers background or methods in this paper

  • ...Irreducible error floors due to ISI are often obtained by simulation, which can easily incorporate different channel models, modulation formats, and symbol sequence characteristics [26, 28, 27, 22, 23]....

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  • ...Measurements for the partition loss at different frequencies for different partition types can be found in [1, 23, 24, 19, 25], and Table 2....

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  • ...The value for γ0 cannot be solved for in closed form for typical continuous pdfs p(γ) and thus must be found numerically [23]....

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  • ...A typical model assumes the channel is composed of several scattering centers which generate the multipath [23, 24]....

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  • ...In [23] the Jakes model is extended to produce spatio-temporal characteristics using the ideas of [25, 26, 27]....

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Journal ArticleDOI
TL;DR: When n identical randomly located nodes, each capable of transmitting at W bits per second and using a fixed range, form a wireless network, the throughput /spl lambda/(n) obtainable by each node for a randomly chosen destination is /spl Theta/(W//spl radic/(nlogn)) bits persecond under a noninterference protocol.
Abstract: When n identical randomly located nodes, each capable of transmitting at W bits per second and using a fixed range, form a wireless network, the throughput /spl lambda/(n) obtainable by each node for a randomly chosen destination is /spl Theta/(W//spl radic/(nlogn)) bits per second under a noninterference protocol. If the nodes are optimally placed in a disk of unit area, traffic patterns are optimally assigned, and each transmission's range is optimally chosen, the bit-distance product that can be transported by the network per second is /spl Theta/(W/spl radic/An) bit-meters per second. Thus even under optimal circumstances, the throughput is only /spl Theta/(W//spl radic/n) bits per second for each node for a destination nonvanishingly far away. Similar results also hold under an alternate physical model where a required signal-to-interference ratio is specified for successful receptions. Fundamentally, it is the need for every node all over the domain to share whatever portion of the channel it is utilizing with nodes in its local neighborhood that is the reason for the constriction in capacity. Splitting the channel into several subchannels does not change any of the results. Some implications may be worth considering by designers. Since the throughput furnished to each user diminishes to zero as the number of users is increased, perhaps networks connecting smaller numbers of users, or featuring connections mostly with nearby neighbors, may be more likely to be find acceptance.

9,008 citations

Book
01 Jan 2004
TL;DR: The book gives many numerical illustrations expressed in large collections of system performance curves, allowing the researchers or system designers to perform trade-off studies of the average bit error rate and symbol error rate.
Abstract: noncoherent communication systems, as well as a large variety of fading channel models typical of communication links often found in the real world, including single- and multichannel reception with a large variety of types. The book gives many numerical illustrations expressed in large collections of system performance curves, allowing the researchers or system designers to perform trade-off studies of the average bit error rate and symbol error rate. This book is a very good reference book for researchers and communication engineers and may also be a source for supplementary material of a graduate course on communication or signal processing. Nowadays, many new books attach a CD-ROM for more supplementary material. With the many numerical examples in this book, it appears that an attached CD-ROM would be ideal for this book. It would be even better to present the computer program in order to be interactive so that the readers can plug in their arbitrary parameters for the performance evaluation. —H. Hsu

6,469 citations


"Wireless communications" refers background or methods in this paper

  • ...Measurements for the partition loss at different frequencies for different partition types can be found in [1, 23, 24, 19, 25], and Table 2....

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  • ...Diffraction results from many phenomena, including the curved surface of the earth, hilly or irregular terrain, building edges, or obstructions blocking the LOS path between the transmitter and receiver [16, 3, 1]....

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  • ...For these environments computer-aided modeling tools are available to predict signal propagation characteristics [1]....

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  • ...This attenuation loss will vary widely, depending on the material and depth of the object [1, 46]....

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  • ...This happens when the nth multipath component results from a reflection cluster with a large number of nonresolvable multipath components [1]....

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Journal ArticleDOI
29 Jun 1997
TL;DR: It is proved that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit, and experimental results for binary-symmetric channels and Gaussian channels demonstrate that practical performance substantially better than that of standard convolutional and concatenated codes can be achieved.
Abstract: We study two families of error-correcting codes defined in terms of very sparse matrices "MN" (MacKay-Neal (1995)) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties The decoding of both codes can be tackled with a practical sum-product algorithm We prove that these codes are "very good", in that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit This result holds not only for the binary-symmetric channel but also for any channel with symmetric stationary ergodic noise We give experimental results for binary-symmetric channels and Gaussian channels demonstrating that practical performance substantially better than that of standard convolutional and concatenated codes can be achieved; indeed, the performance of Gallager codes is almost as close to the Shannon limit as that of turbo codes

3,842 citations


"Wireless communications" refers background or methods in this paper

  • ...Irreducible error floors due to ISI are often obtained by simulation, which can easily incorporate different channel models, modulation formats, and symbol sequence characteristics [26, 28, 27, 22, 23]....

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  • ...Path loss exponents at higher frequencies tend to be higher [31, 26, 25, 27] while path loss exponents at higher antenna heights tend to be lower [34]....

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  • ...Building penetration loss on the ground floor typically range from 8-20 dB for 900 MHz to 2 GHz [27, 28, 3]....

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  • ...Different models for such 3-D channels have been proposed in [25, 26, 27]....

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  • ...The excitement in this area stems from the breakthrough results in [28, 27, 29] indicating that the capacity of a fading channel with multiple inputs and outputs (a MIMO channel) is M times larger then the channel capacity without multiple antennas, where M = min(Mt, Mr) for Mt the number of transmit antennas and Mr the number of receive antennas....

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