A Green Paradigm for Internet of Things:Ambient Backscatter Communications

Wei Zhang,Yao Qin,Wenjing Zhao,Minzheng Jia,Qiang Liu,Ruisi He,Bo Ai

1 Science and Technology on Information Systems Engineering Laboratory,National University of Defense Technology,and also with Institute of Telecommunication Satellites,China Academy of Space Technology (CAST)

2 Beijing Key Lab of Transportation Data Analysis and Mining,Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications,School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China

3 Department of Information Engineering,Beijing Polytechnic College,Beijing 100042,China

4 State Key Laboratory of Rail Traffic Control and Safety,Beijing Jiaotong University,Beijing 100044,China

Abstract: Internet of Things (IoT) has attracted extensive interest from both academia and industries,and is recognized as an ultimate infrastructure to connect everything at anytime and anywhere.The implementation of IoT generally faces the challenges from energy constraint and implementation cost.In this paper,we will introduce a new green communication paradigm,the ambient backscatter (AmBC),that could utilize the environmental wireless signals for both powering a tiny-cost device and backscattering the information symbols.Specifically,we will present the basic principles of AmBC,analyze its features and advantages,suggest its open problems,and predict its potential applications for our future IoT.

Keywords: ambient backscatter (AmBC); RF-powered device; Internet of Things (IoT); battery-free tag; wire-less sensor

I.INTRODUCTION

Internet of Things (IoT) that targets at connecting everyday physical objects is deemed as an essential feature of future networks and has attracted vast attention from both academic circles and industrial worlds [1].According to the prediction by Gartner,a world-famous leading research and advisory company,the number of IoT devices is growing exponentially and will reach 26 billion by 2020.It is also reported by IDTechEx that the total market of radio-frequency identification (RFID),a significant component of IoT,was worth $6.96 billion in 2012,$7.77 billion in 2013,$8.89 billion in 2014,and is forecast to rise to $27.31 billion in 2024 [2].

The concept of IoT originated in 1982 when a modified Coke machine was connected to the Internet at Carnegie Mellon University,while its earliest remark was provided in the book “The Road Ahead” written by Bill Gates in 1995.Nevertheless,the general opinion is that the first appearance of IoT was suggested by Kevin Ashton in the Auto-ID Center at Massachusetts Institute of Technology in 1999.Ever since then,IoT became popular.

Many governments attach crucial importance to IoT and have taken various measures to advance its applications.For example,Germany proposed the industry 4.0 project in 2013,Europe Union established Alliance for Internet of Things innovation (AIOTI) in 2015,and China held the World IoT Exposition in 2016 and distributed “smart manufacturing development plan” to guide its IoT development of the next five years.

In 2014,five top information technology corporations including International Business Machines (IBM),Integrated Elec- tronics (Intel),General Electric (GE),Cisco,and American Telephone and Telegraph (AT＆T) established Industrial Internet Consortium (IIC) to promoting IoT applications.In addition,narrow band IoT (NB-IoT) standard was raised by the 3rd Generation Partnership Project (3GPP) in Release 13 in 2016.

Compared with the mobile telecommunications technology,which is currently in its 4th generation,IoT is still at the germination stage,awaiting a large scale deployment and a wide range commercialization.Generally speaking,IoT is facing three challenges:

1)Energy sources:Existing energy sources in IoT mainly include batteries,luminous,solar,wind,vibrational,thermal,and wireless powering,each being limited by its respective disadvantages.For example,batteries could not last for a long period and thus require replacement or recharging.In addition,batteries are not suitable for dangerous places such as poisonous,high-temperature,or high-voltage areas.The luminous,solar,wind,vibrational,and thermal energy sources are unstable and depend largely on environments like weather conditions.Meanwhile,the traditional wireless energy harvesting necessitates powerful RF sources,and is of low efficiency due to the severe radio channel fading.

Fig.1.A typical ambient backscatter communication system.

2)Cost of sensors:The cost for sensors is another indispensable factor restricting the extensive applications of IoT.Considering the case where the prices of the sensors are expensive,deployment of IoT will be limited due to lack of profits.For instance,the price of the laser radar Velodyne-brand sensor for self-driving cars by Google company in 2009 was more than 75,000 $,as high as an intermediate car,which will certainly hinder the commercialization of driverless cars.The price of such sensor in 2017 is cut down to one-tenth of that in 2009,and thus buying a self-driving car will be possibly within the reach of middle class.

3)Interconnection and interworking of IoT:The rapid development of Internet depends largely on the adoption of transmission control protocol/Internet protocol (TCP/IP),an open protocol that allows interconnection and interworking between computers.However,there does not exist such an open and recognized protocol for IoT.

Recently,a new technology that combines wireless energy harvesting and backscatter communications,called the ambient backscatter (AmBC) communications.The technology relies on inexpensive radio frequency (RF) circuit component,and is free from batteries.Thus,AmBC would serve as an potential solutions for the aforementioned first two challenges.

In this paper,we will present a brief survey on AmBc including its state of art and current situations,strengths and weaknesses,open problems,and potential applications in IoT,etc.

The remainder of this article is organized as follows.Section II introduces basic principles of AmBC,analyzes its merits,and investigates current research on AmBC technology.Section III presents the open challenges for AmBC.Section IV suggests potential applications for AmBC and Section V concludes the paper.

II.OVERVIEW OF AMBC

2.1 Origin and fundamentals of AmBC

AmBC was first proposed by Vincent Liu et.al.from the University of Washington in 2013 [3].Different from traditional backscattering in RFID systems,AmBC utilizes existing wireless signals from the environment to trigger battery-free devices and does not need a specific reader to generate RF signals.Specifically,battery-free devices,such as a tag or a sensor,can harvest wireless energy and then transmit “0” or “1” bit through reflecting or non-reflecting states that can be realized by changes of the tag antenna impedance.

Figure 1 depicts a typical ambient backscatter communication system composed of one RF source,a reader (sink node),and a tag (sensor).The RF source can be a base station (BS),a Wi-Fi gateway,or radio television (TV) center.

Denote the RF signals transmitted by the source asx(n).The sensor or the tag will receive the signalx(n) and harvest wireless energy from it.Then,the sensor can be be actived to collect information and encode the information into binary bitsB(n).Next,the sensor will transmitB(n) to the reader.IfB(n) = 1,the sensor will adapt its antenna impedance so that a portion of the incoming signalx(n) will be scattered back; IfB(n) = 0,the sensor will change its antenna impedance to another value so that most of the energy of the signalx(n) will be dissipated inside the tag [4].The overall process is shown in figure 2.

Accordingly,the baseband signaly(n) received at the reader can be expressed as [5]

whereηrepresents the signal fading inside the tag,andh,g,fdenote the wireless channel from the RF source to the reader,from the RF source to the tag,and from the tag to the reader,respectively.Then the reader could obtainB(n) fromy(n) with energy detection algorithms.

2.2 Advantages of AmBC

Clearly,the first advantage of AmBC is that it enables tags to communicate without battery,and removes the battery constraint like labor work of battery replacement and undesired performance due to energy shortage.

On the other hand,it is well-known that the RF circuit is the most expensive and energy-consuming component of the hardware implementation.AmBC allows tags to avoid RF signal generating and remove the transmission circuits such as oscillators,mixers,filters,and amplifiers,which then achieves low cost of the circuit design.

Moreover,deployment of sensors is convenient with AmBC,since sensors can be located wherever wireless signals can reach.The places can be dangerous spots filled with poisonous gases or liquids,high-voltage areas,positions inside building walls,or even human bodies.

In addition,AmBC can utilize the RF signal of other communication systems,which do not require fixed carrier frequency or specially allocated spectrum and can thus improve the spectrum efficiency.

In summary,being free of battery,low cost,easy deployment,and enhanced spectrum efficiency constitute the main advantages of AmBC technology,which also makes it a “green” communication technology for IoT.

Fig.2.Block diagram of an ambient backscatter device,e.g.a sensor or a tag.

2.3 Literature review of AmBC

Ever since its birth in 2013 [3],AmBC were planted to various applications.For example,the battery-free tags or sensors were designed to communicate with off-the-shelf Wi-Fi gateways through AmBC in 2014 [7].Enhanced encoder and detector for the reader with two antennas are designed in [8],which enlarges the transmission distance to maximum 18 meters and increases the effective data rate up to 1 Mbps.

Since the backscattered signalsx(n) are unknown to the reader,it is difficult for the reader to estimate the channel parameters.

Accordingly,differential encoding scheme and detection algorithm were proposed in [5] to eliminate the necessity of channel estimation at the reader,where the corresponding bit-error rate (BER) performance was also analyzed.In addition,the optimal noncoherent detector was presented in [9],where the outage performance was computed.

To remove the interference from the reader and enhance the detection performance,an AmBC scheme with orthogonal fre- quency division multiplex (OFDM) signals were presented in [10].The effect of various system parameters on the transmission rate and detection performance in such a system is further evaluated in [11],[23].

In addition,AmBC can be integrated into RF-powered cognitive radio networks (CRN) to enhance the performance of the secondary users [15].It is in prospect that AmBC can provide more capabilities when combing with channel coding [16],full duplex [19],[25],relay selection [18],cooperative relay [12],[13],maximal ratio combining [21],hybrid transmission [22],and/or massive multiple-input multiple-output (MIMO) [17] technologies.

III.OPEN CHALLENGES

Tag in AmBC communication systems are under both constraints of computing capability and limited power.In addition,the source signalsx(n) are unknown to transceivers.Information transmission for AmBC communication systems under the these constraints raises a series of challenges,including channel estimation,signal detection,multiple access,interference control,and performance analysis.We will elaborate these open issues in this section.

3.1 Wireless energy harvesting and allocation

The first step for AmBC is to harvest wireless energy from surrounding RF sources.The more energy harvested,the better performance was provided by the sensor.The harvested energy will be stored and divided into two parts:the first part is used to run the sensor to collect information and encode into binary symbolsB(n); the other is used to control the antenna impedance to determine backscattering or non-backscattering so as to transmit the encoded bits.The power partition between the two parts should also be optimized according to certain criterion.

On the other hand,since the sensor is usually equipped with one antenna due to low cost limitation,one antenna can either harvest wireless energy or backscatter the incoming RF signal.Hence,energy harvesting and backscattering should be multiplexed on different time periods.

3.2 Channel statistics and channel capacity

The effective wireless channels for AmBC in transmittingB(n) includehandµ¾h+ηfg which are different from traditional point-topoint or cooperative wireless channels such as Rayleigh,Rician or Nakagami channels.It is also worth noting that the two channels,handµ,are correlated.Meanwhile,the tag signalB(n) are discrete and the received signalsy(n) are continuous.Therefore,channel capacity analysis for AmBC communication systems is distinct from that of existing channels,and provides a valuable future research direction [28].

3.3 Channel estimation and training sequence design

The reader aims to recover the signalB(n) hidden in the received signaly(n),as shown in (1).Therefore,it will be helpful if the channel state information (CSI),such ashandµ,is available at the reader.Unfortunately,estimation of the channel is not as simple as in traditional RFID backscattering case,because the source signalsx(n) are unknown at the reader.Moreover,a strong interference from source directly to the reader would also damage the channel estimation accuracy [20].A properly designed blind estimator that could utilize the statistics knowledge ofx(n) may be applied here.Because in AmBC communications environment,the computation delay that usually resides in blind estimation schemes is not that harmful since the data rate of the tag signalB(n) is normally not high.Meanwhile,the design of the optimal training sequenceB(n) that can estimate the channel parameters are waiting for further investigation.

3.4 Signal detection

The detection problem for AmBC is different from traditional binary hypothesis test problems due to the existence of the source interferencex(n).Generally,the RF signalx(n) is unknown to the reader,which may result in unknown or limited CSI at the receiver side as is pointed out in Section III-C.Meanwhile the CSI of the source-reader link cannot be obtained either,since the ambient source is not obliged to help train the channel.Therefore,signal detection at the reader is a rather non-trivial task under the above constraint.

Recent studies leverage differential encoder and energy detector to avoid direct channel estimation [5],or utilize the signal ratio at a pair of receiving antennas [8] to detect the AmBC signals.However,these detectors either support low data rates or provide moderate BER performance [16].Figure 3 illustrates BER performance of ambient backscatter systems.Figure 3(a) provides the BER curves as well as upper and lower bounds versus number of received signals to be averaged [5].Figure 3(b) plots the BER curves versus Signal to Noise Ratio(SNR) [16].It can be readily seen that there exist error floors for BER performance of ambient backscatter communication systems.

There still exists many open issues on the detection of AmBC signals.For example,with multi-antenna reader,the more advanced precoding either to improve the performance or to enhance the security is to be designed.The corresponding BER performance is worthy of investigation.In addition,if full duplex transmission is adopted at the reader,the optimal detector and the self-interference cancelation scheme are to be developed.Besides,when the channels between the RF source and the reader (or tag) are frequency-selective,the detection problem of current AmBC faces more challenges and it should be revised.

3.5 Synchronization and multiple access

Traditional RFID systems utilize known-to-tag signals transmitted by the reader for triggering the passive tags and then synchronization.However,the tags in AmBC communication systems are powered by another RF source,instead of the reader,whose signalsx(n) are unknown to the tags.Therefore,depending on the RF sourcex(n) for synchronization between the reader and the tag is almost impossible.The only choice for synchronization is the tag signalsB(n).To obtain synchronization between the tags and the reader,the tag signalB(n) should be carefully designed.

In the case of multiple tags,the synchronization problem becomes more difficult since the functionalities of the tags,such as power,memory,and calculation capability,are limited.Moreover,designing the multiple access scheme for tags,such as time division multiplexing,frequency division multiplexing,and code division multiplexing could be challenging due to the limited computation capability of the tag.The diversity order that the AmBC based multi-user detection can achieve also deserves the exploitation.

Fig.3.BER performance of AmBC communication systems.

3.6 Security

Security is of vital importance to the successful applications of AmBC in IoT.Due to the broadcasting nature of wireless channels,security for wireless transmission is always a topic worthy of research.Due to power and complexity constraint at the tag as well as the backscatter mode of communications,guarantee of secure communications for AmBC is especially difficult.For instance,how to identify a fake AmBC tag for the reader remains unknown.In addition,it is possible to place a noise-generating tag close to the reader and randomly backscatter the ambient signals,which will cause trouble to the reader in accurately recovering signals from legal tags.

3.7 Interference control,awareness,and utilization

For AmBC systems,the backscattered signal will definitely produce some influence on the receiver of the existing systems.It is shown in [3] that the legacy receiver can either possibly utilize the backscattered signals to enhance throughput performance,or suffer from the interference produced by the AmBC signals within certain distance.Therefore,how to design the AmBC scheme at the tag so that the resulted interference can be under certain threshold,or the legacy receiver can be timely aware of the backscattered signals and properly utilize them to improve the performance is an interesting problem.

IV.POTENTIAL APPLICATIONS

As indicated in the Section II-B,the advantages of AmBC enable its many applications in IoT to facilitate our daily lives.In this section,we demonstrate a number of typical applications of AmBC.

4.1 Material Flow

After the successful applications of traditional backscatter in material flow such as bar codes,AmBC will continue to undertake a crucial task in logistics due to the low cost and easy deployment.As shown in figure 4(a),the workers can collect information of all objects through simply pushing a button to start the RF source to transmit wireless signals to all tags on the objects.The tags will utilize AmBC to provide information to the reader or some information collector.With AmBC,a warehouse administrator can automatically keep track of any objects inside the warehouse from one remote place.

Another interesting logistics application of AmBC is checking and locating the books in library that is depicted in figure 4(b).There are two tags for each book:one is on the bookshelf and the other is on the book.The two tags can communicate through AmBC to confirm their matching status.If not matching,then the book is not on the proper position and the tag on the bookshelf can turn on a light emitting diode (LED) or send certain predesigned signals to remind librarians.With AmBC,one can also locate his or her desired book quickly from piles of bookshelves.Since each book is uniquely defined by the tag on the bookshelf,the RF source can transmit special signals to locate the tag,which will guide the person to the right place of the book.

4.2 Smart homes and smart cities

AmBC technology endows the sensors/tags the abilities of flexible deployment and easy maintenance.Accordingly,sensors or tags with AmBC can be a good choice for applications in smart homes and cities.

Figure 4(c) provides an example of AmBC application in smart homes.The WiFi Gateway can first collect information from sensors/tags located indoor or outside the window or even embedded within the wall through AmBC technology,and then display on Television (TV) the sensed information such as temperatures,humidity,wind speed,and security or surveillance information including gas leak,smoke level,and monitor video [24].Figure 4(d) depicts an example of AmBC applications in smart cities.The tags or sensors can be put in any place of interests or shopping mall to provide the tourists the information about restaurants,parking lots,and product advertisements.Such information can be predetermined or be dynamically collected and updated through one reader that can write corresponding data into the tag memory.

Fig.4.AmBC applications in logistics,smart homes and cities.

Fig.5.AmBC applications in biology,finance,and railway transportation.

4.3 Healthcare and finance

Being free of battery and wire brings an extensive range of healthcare application opportunities for AmBC since many biomedical devices require extremely low energy consumption as well as fast and convenient data exchanges.AmBC is suggested to be utilized in implantable neural recording devices in [19] where Wi-Fi or Bluetooth signals are selected as the RF source signals.Figure 5(a) illustrates that the wearable and implantable biomedical devices can be powered by wireless signals from the smart phone and communicate with the phone through AmBC.

Moreover,with AmBC,two bank cards and the smart phone can communicate with each other and realize fast money transfer with multiple operations such as swiping and inputting passwords,as shown in figure 5(b).Even if smart phone runs out of batteries,AmBC can be used to perform such operations in the presence of a radio frequency source,such as a base station(BS).

4.4 Transportation

It is worth noting that AmBC can be applied in railway transportation for security surveillance.Figure 5(c) illustrates such a case,where many sensors or tags are deployed along the railway to supervise the unexpected incidents e.g.,intrusion of unknown animals,bridge damage or collapse,water pipe burst,and geologic hazards,so as to predicts potential dangers.The train or the BSs will transmit RF signals to collect information along the railway from those sensors/tags through AmBC.A searchlight is equipped at the head of train,which can throw light on the railway forward when it is turned on.Note that this communication paradigm is different from the traditional wireless railway communication through which trains can only be informed by the BSs along the railways.

4.5 Environmental monitoring and animal tracking

Ambient wireless signals,such as TV and broadcasting signals and frequency modulation (FM) radio signals,are pervasive,which enables AmBC to be suitable for continuous environmental monitoring and animal tracking.

With traditional backscatter technology,the sensors start to monitor the environment only when the reader transmit RF signals.With AmBC,sensors can obtain power from ambient signals without interruption.Therefore,these sensors can ceaselessly monitor the environment parameters,including humidity in farms,water quality in fishing grounds,and concentration of poisonous gases,and timely report to the reader when abnormalities appear [26],[27].Similarly,farmers and animal wardens can utilize AmBC tags to keep track of their cows or pets without periodically changing batteries.

V.CONCLUSION

Because radio waves can be utilized anywhere,AmBC shows its potential for many low-cost applications and can be utilized as an auxiliary communication scheme in the area of Internet of Things(IoT).As a new technology,AmBC would demand the resign of most modules of a communications system,such as synchronization,channel estimation,signal detection,multi-user access,and even self-organized networking (SON).The computational and structural constraints,energy constraints,distance restrictions,caching capacity-relationship and price costs would all formulate challenges in the realization of a practical AmBC system.

ACKNOWLEDGEMENT

This work was supported in part by National Key R＆D Program of China under Grant 2016YFE0200900,in part by Scientific Research Program of Beijing Municipal Commission of Education under Grant KM201910853003,and in part by Major projects of Beijing Municipal Science and Technology Commission under Grant Z181100003218010.(Corresponding author:Wenjing Zhao.)