Gap Sense: Lightweight coordination of heterogeneous wireless devices
14 Apr 2013-pp 3094-3101
TL;DR: Gap Sense (GSense) is introduced, a novel mechanism that can coordinate heterogeneous devices without modifying their PHYlayer modulation schemes or spectrum widths and is shown to deliver coordination information with close to 100% accuracy within practical SNR regions.
Abstract: Coordination of co-located wireless devices is a fundamental function/requirement for reducing interference. However, different devices cannot directly coordinate with one another as they often use incompatible modulation schemes. Even for the same type (e.g., WiFi) of devices, their coordination is infeasible when neighboring transmitters adopt different spectrum widths. Such an incompatibility between heterogeneous devices may severely degrade the network performance. In this paper, we introduce Gap Sense (GSense), a novel mechanism that can coordinate heterogeneous devices without modifying their PHYlayer modulation schemes or spectrum widths. GSense prepends legacy packets with a customized preamble, which piggy-backs information to enhance inter-device coordination. The preamble leverages the quiet period between signal pulses to convey such information, and can be detected by neighboring nodes even when they have incompatible PHY layers. We have implemented and evaluated GSense on a software radio platform, demonstrating its significance and utility in three popular protocols. GSense is shown to deliver coordination information with close to 100% accuracy within practical SNR regions. It can also reduce the energy consumption by around 44%, and the collision rate by more than 88% in networks of heterogeneous transmitters and receivers.
Citations
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TL;DR: Experimental tests demonstrate that the proposed system for smart home control networks is practically feasible and performs well and the impact of wireless interference on the proposedsmart home control network is substantially mitigated.
Abstract: Wireless sensor networks (WSNs) and power line communications (PLCs) are used in this work to implement a smart home control network. The goals are to reduce the impact of wireless interference on a smart home control network and unnecessary energy consumption of a smart home. An isolated WSN with one coordinator, which is integrated into the PLC transceiver, is established in each room. The coordinator is responsible for transferring environmental parameters obtained by WSNs to the management station via PLCs. The control messages for home appliances are directly transferred using PLCs rather than WSNs. According to the experimental results, the impact of wireless interference on the proposed smart home control network is substantially mitigated. Additionally, a smart control algorithm for lighting systems and an analysis of the illumination of a fluorescent lamp were presented. The energy saving of lighting systems relative to those without smart control was evaluated. Numerical results indicate that the electricity consumption on a sunny or cloudy day can be reduced by at least 40% under the smart control. Moreover, a prototype for the proposed smart home control network with the smart control algorithm was implemented. Experimental tests demonstrate that the proposed system for smart home control networks is practically feasible and performs well.
237 citations
Cites methods from "Gap Sense: Lightweight coordination..."
...To solve this problem, some methods have been proposed for interference avoidance [19] or coordinating such a heterogeneous network environment [20]....
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...On the other hand, compared with the methods in [11], [19], and [20], by modifying the transmission mechanism of WSNs to reduce packet failure rates, no modification in the transmission protocol of WSNs is required when the proposed WSN+PLC architecture is used....
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07 Sep 2015
TL;DR: FreeBee is presented, which enables direct unicast as well as cross-technology/channel broadcast among three popular wireless technologies: WiFi, ZigBee, and Bluetooth and a new \emph{interval multiplexing} technique is proposed to enable concurrent broadcasts from multiple senders or boost the transmission rate of a single sender.
Abstract: This paper presents FreeBee, which enables direct unicast as well as cross-technology/channel broadcast among three popular wireless technologies: WiFi, ZigBee, and Bluetooth. Our design aims to shed the light on the opportunities that cross-technology communication has to offer including, but not limited to, cross-technology cooperation and coordination. The key concept of FreeBee is to modulate symbol messages by shifting the timing of periodic beacon frames already mandatory for wireless standards without incurring extra traffic. Such a generic cross-technology design consumes zero additional bandwidth, allowing continuous broadcast to safely reach mobile and/or duty-cycled devices. A new \emph{interval multiplexing} technique is proposed to enable concurrent broadcasts from multiple senders or boost the transmission rate of a single sender. Theoretical and experimental exploration reveals that FreeBee offers a reliable symbol delivery under a second and supports mobility of 30mph and low duty-cycle operations of under 5%.
199 citations
Cites background from "Gap Sense: Lightweight coordination..."
...Conversely, the ZigBee network often operates as a stand-alone and has limited information, but is extremely energy efficient....
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04 Oct 2017
TL;DR: The comprehensive evaluation reveals that WEBee can achieve a more than 99% reliable parallel CTC between WiFi and ZigBee with 126 Kbps in noisy environments, a throughput about 16,000x faster than current state-of-the-art CTCs.
Abstract: Recent advances in Cross-Technology Communication (CTC) have improved efficient coexistence and cooperation among heterogeneous wireless devices (e.g., WiFi, ZigBee, and Bluetooth) operating in the same ISM band. However, until now the effectiveness of existing CTCs, which rely on packet-level modulation, is limited due to their low throughput (e.g., tens of bps). Our work, named WEBee, opens a promising direction for high-throughput CTC via physical-level emulation. WEBee uses a high-speed wireless radio (e.g., WiFi OFDM) to emulate the desired signals of a low-speed radio (e.g., ZigBee). Our unique emulation technique manipulates only the payload of WiFi packets, requiring neither hardware nor firmware changes in commodity technologies -- a feature allowing zero-cost fast deployment on existing WiFi infrastructure. We designed and implemented WEBee with commodity devices (Atheros AR2425 WiFi card and MicaZ CC2420) and the USRP-N210 platform (for PHY layer evaluation). Our comprehensive evaluation reveals that WEBee can achieve a more than 99% reliable parallel CTC between WiFi and ZigBee with 126 Kbps in noisy environments, a throughput about 16,000x faster than current state-of-the-art CTCs.
190 citations
Cites methods from "Gap Sense: Lightweight coordination..."
...In comparison with these packet-level CTC [5, 9, 23, 48, 49], WEBee is the first work to implement the CTC based on physical signal emulation, leading to 16,000x throughput improvement....
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...GSense [48] uses gaps embedded between the customized preamble to deliver cross-technology communications....
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14 Nov 2016
TL;DR: B2W2, a novel communication framework that enables N-way concurrent communication among WiFi and Bluetooth Low Energy (BLE) devices, is proposed and it is demonstrated that it is possible to enable the BLE to WiFi cross-technology communication while supporting the concurrent Ble to BLE and WiFi to WiFi communications.
Abstract: The exponentially increasing number of internet of things (IoT) devices and the data generated by these devices introduces the spectrum crisis at the already crowded ISM 2.4 GHz band. To address this issue and enable more flexible and concurrent communications among IoT devices, we propose B2W2, a novel communication framework that enables N-way concurrent communication among WiFi and Bluetooth Low Energy (BLE) devices. Specifically, we demonstrate that it is possible to enable the BLE to WiFi cross-technology communication while supporting the concurrent BLE to BLE and WiFi to WiFi communications. We conducted extensive experiments under different real-world settings and results show that its throughput is more than 85X times higher than the most recently reported cross-technology communication system [22], which only supports one-way communication (i.e., broadcasting) at any specific time.
109 citations
Cites background or methods from "Gap Sense: Lightweight coordination..."
...Instead of mitigating the interference [25], researchers proposed to leverage the coexistence feature of multiple communication technologies under the same frequency for crosstechnology communication [10, 50, 22]....
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...In Esense [10], GSense [50] and FreeBee [22], researchers use RSS to measure the WiFi signal so that it enables the communication between WiFi and ZigBee devices....
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01 May 2017
TL;DR: C-Morse is presented, which leverages all traffic (such as through data packets, beacons and other control frames) to achieve a high cross-technology communication throughput and achieves a free side-channel, whose CTC throughput is as much as 9 χ of the present state of the art, while maintaining the through traffic within a negligible delay that goes unnoticed by applications and end-users.
Abstract: Recent research on CTC (cross-technology communication) demonstrates the viability of direct coordination among heterogeneous devices (e.g., WiFi and ZigBee) with incompatible physical layers. Although encouraging, current solutions suffer from either severe inefficiency in channel utilization or low throughput using limited beacons. To address these limitations, this paper presents C-Morse, which leverages all traffic (such as through data packets, beacons and other control frames) to achieve a high cross-technology communication throughput. The key idea of C-Morse is to slightly perturb the transmission timing of existing WiFi packets to construct recognizable radio energy patterns without introducing noticeable delays to upper layers. At the receiver side, ZigBee captures such patterns by sensing the RSSI value, and then decodes the transmitted symbols. C-Morse also introduces a novel timing-based multiplexing technique to allow the coexistence of multiple C-Morse access points and reject other interference, showing a reliable symbol delivery ratio. As a result, C-Morse achieves a free side-channel, whose CTC throughput is as much as 9 χ of the present state of the art, while maintaining the through traffic within a negligible delay that goes unnoticed by applications and end-users.
94 citations
Cites background from "Gap Sense: Lightweight coordination..."
...Although promising, recent studies such as [4], [11], [22] require dedicated hardware, resulting in incompatibility with existing billions of devices....
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References
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TL;DR: In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented and the cooperative sensing concept and its various forms are explained.
Abstract: The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.
4,812 citations
"Gap Sense: Lightweight coordination..." refers background in this paper
...The problem of sensing energy pulses is analogous to that of sensing primary users in cognitive radio networks (see [19] for a comprehensive survey)....
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02 Jan 2017TL;DR: In this paper, the authors present the often "difficult" concepts of digital communications in an easy-to understand manner-without diluting the mathematical precision, using a student-friendly approach.
Abstract: For courses in Digital Communications. Exceptionally accessible, this book presents the often "difficult" concepts of digital communications in an easy-to- understand manner-without diluting the mathematical precision. Using a student-friendly approach, it develops the important techniques in the context of a unified structure (in block diagram form)-providing organization and structure to a field that has, and continues, to grow rapidly, and ensuring that students gain an awareness of the "big picture" even while delving into the details (the most up-to-date modulation, coding, and signal processing techniques that have become the basic tools of our modern era). It traces signals and key processing steps from the information source through the transmitter, channel, receiver, and ultimately to the information sink.
2,496 citations
01 Jan 1996
2,375 citations
03 Nov 2010
TL;DR: This work first examines the interference patterns between ZigBee and WiFi networks at the bit-level granularity, then designs BuzzBuzz to mitigate WiFi interference through header and payload redundancy, which improves the ZigBee network delivery rate and reduces ZigBee retransmissions.
Abstract: Frequency overlap across wireless networks with different radio technologies can cause severe interference and reduce communication reliability. The circumstances are particularly unfavorable for ZigBee networks that share the 2.4 GHz ISM band with WiFi senders capable of 10 to 100 times higher transmission power. Our work first examines the interference patterns between ZigBee and WiFi networks at the bit-level granularity. Under certain conditions, ZigBee activities can trigger a nearby WiFi transmitter to back off, in which case the header is often the only part of the Zig-Bee packet being corrupted. We call this the symmetric interference regions, in comparison to the asymmetric regions where the ZigBee signal is too weak to be detected by WiFi senders, but WiFi activity can uniformly corrupt any bit in a ZigBee packet. With these observations, we design BuzzBuzz to mitigate WiFi interference through header and payload redundancy. Multi-Headers provides header redundancy giving ZigBee nodes multiple opportunities to detect incoming packets. Then, TinyRS, a full-featured Reed Solomon library for resource-constrained devices, helps decoding polluted packet payload. On a medium-sized testbed, BuzzBuzz improves the ZigBee network delivery rate by 70%. Furthermore, BuzzBuzz reduces ZigBee retransmissions by a factor of three, which increases the WiFi throughput by 10%.
401 citations
"Gap Sense: Lightweight coordination..." refers background in this paper
...High-speed devices may preempt low-speed devices and cause severe collision even with CSMA enabled [5], [6]....
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TL;DR: This article proposes several MAC enhancements via various frame aggregation mechanisms that overcome the theoretical throughput limit and reach higher throughput and introduces some PHY proposals and study the fundamental issue of MAC inefficiency.
Abstract: This article introduces a new standardization effort, IEEE 802.11n, an amendment to IEEE 802.11 standards that is capable of much higher throughputs, with a maximum throughput of at least 100 Mb/s, as measured at the medium access control data services access point. The IEEE 802.11n will provide both physical layer and MAC enhancements. In this article we introduce some PHY proposals and study the fundamental issue of MAC inefficiency. We propose several MAC enhancements via various frame aggregation mechanisms that overcome the theoretical throughput limit and reach higher throughput. We classify frame aggregation mechanisms into many different and orthogonal aspects, such as distributed vs. centrally controlled, ad hoc vs. infrastructure, uplink vs. downlink, single-destination vs. multi-destination, PHY-level vs. MAC-level, single-rate vs. multirate, immediate ACK vs. delayed ACK, and no spacing vs. SIFS spacing.
323 citations