International audienceShort Range Devices (SRD) are increasingly employed in urban sensor networks using different communication protocols. That becomes a key problem in the gateway design, since its cost and energy consumption increase with the number of implemented technologies. This cost and energy can be reduced by using a reconfigurable gateway to perform the biggest part of signal processing digitally, as it is done in Software-Defined Radio (SDR). As several received signals should be simultaneously digitized, Analog-to-Digital Converter (ADC) must be able to treat the whole frequency band used by SRD, with a high enough resolution to properly demodulate the signals. This paper describes what the ADC's constraints are and how to dimension an ADC in SDR for SRD. An example based on the SmartSantander deployment shows that an ADC resolution of 23 bits is required to properly demodulate the data

Hutu, Florin

Miscopein, Benoit

Risset, Tanguy

Vallerian, Mathieu

Villemaud, Guillaume

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HAL Id: hal-00920906https://hal.inria.fr/hal-00920906Submitted on 19 Dec 2013HAL is a multi-disciplinary open accessarchive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come fromteaching and research institutions in France orabroad, or from public or private research centers.L’archive ouverte pluridisciplinaire HAL, estdestinée au dépôt et à la diffusion de documentsscientifiques de niveau recherche, publiés ou non,émanant des établissements d’enseignement et derecherche français ou étrangers, des laboratoirespublics ou privés.SDR for SRD: ADC specifications for reconfigurablegateways in urban sensor networksMathieu Vallerian, Guillaume Villemaud, Benoit Miscopein, Tanguy Risset,Florin HutuTo cite this version:Mathieu Vallerian, Guillaume Villemaud, Benoit Miscopein, Tanguy Risset, Florin Hutu. SDR forSRD: ADC specifications for reconfigurable gateways in urban sensor networks. IEEE Radio WirelessSymposium, Jan 2014, Newport Beach, United States. ￿hal-00920906￿SDR for SRD: ADC specifications for reconfigurablegateways in urban sensor networksMathieu Vallérian 1,2, Guillaume Villemaud 2, Benoit Miscopein 1, Tanguy Risset 2, and Florin Hutu 21Orange-Labs, 38243, Meylan , France,2Université de Lyon, INRIA, INSA-Lyon, CITI-INRIA, F-69621, Villeurbanne, FranceAbstract— Short Range Devices (SRD) are increasinglyemployed in urban sensor networks using different communi-cation protocols. That becomes a key problem in the gatewaydesign, since its cost and energy consumption increase withthe number of implemented technologies. This cost andenergy can be reduced by using a reconfigurable gatewayto perform the biggest part of signal processing digitally, asit is done in Software-Defined Radio (SDR).As several received signals should be simultaneously dig-itized, Analog-to-Digital Converter (ADC) must be able totreat the whole frequency band used by SRD, with a highenough resolution to properly demodulate the signals. Thispaper describes what the ADC’s constraints are and how todimension an ADC in SDR for SRD. An example based on theSmartSantander deployment shows that an ADC resolutionof 23 bits is required to properly demodulate the data.Index Terms— Analog-digital conversion, software radio,wireless sensor networksI. INTRODUCTIONUrban sensor networks covers a large number of appli-cations, such as water, gas and electricity metering, wasteand parking management, air pollution monitoring, publiclightning monitoring or self service bike renting. Eachof these applications have their own constraints, in termsof duty cycle, periodicity, or emitted power. Short RangeDevices (SRD) emitting on the 868 MHz band are usuallyused with a total potential bandwidth of 8 MHz [1].These networks are usually composed of sensors thatonly send data and sink nodes that gather data and trans-mit them to central database [1]. Several technologiescoexist to fulfill each application’s constraints [2], usingfor example spread-spectrum techniques to minimize theinterference risk or to allow a better sensitivity [3].A problem caused by the coexistence of these tech-nologies is that the sinks must be able to receive sig-nals using several technologies. The solution commonlyadopted by manufacturers is to have a stack up of receiversdedicated to each technology, and to assemble the dataonce converted into a digital form. This method has somedrawbacks. Firstly, it lacks flexibility: it does not allowreconfiguration when sensors using a new technologyare added to the network. Secondly, it is costly: sincethe global cost of the architecture is almost the sum ofindividual costs of all individual receivers, some of thereceivers’ components could be re-used instead of beingdedicated to one technology in particular.This problem can be addressed by designing a re-configurable gateway. In the ideal case, such a gatewayshould be able to digitize the whole band immediatelyafter down-conversion to proceed digitally with all thesignal processing, as it is done in Software-Designed Radio(SDR). This implies the possibility of receiving signalsfrom various applications and so with different constraints.It is supposed in this paper that no power control isapplied to the emitting nodes, so the signals may have verydifferent amplitude levels depending on their location andpropagation conditions. This may lead to the well-knownnear-far problem.In this paper, the constraints on the Analog-to-DigitalConverter (ADC) are firstly evaluated taking into accountthe particularities of the used technologies. Secondly, thenear-far problem effect on digitization is treated, and amethod to evaluate the ADC resolution as a function ofthe received signal powers is proposed.II. URBAN SENSOR NETWORK TECHNOLOGIESThe most representative technologies used in urbansensor networks are selected in this study. The onesprovided by the IEEE 802.15.4k’s specifications [4] andWMBus are chosen. WMBus is described in the standardin development EN 13757-4 [5].IEEE 802.15.4k has two modes: it can employ a DSSSmode, with a spreading factor up to 32768, or a FSK mode,using a FSK modulation with a spreading factor limitedto 16. WMBus uses a FSK modulation, without spreadspectrum. The DSSS technique allows to reach negativeSignal-to-Noise Ratios (SNRs) when transmitting data.This is usually not taken into account when estimating theADC’s SNR because there is an hypothesis of a positiveSNR. With a negative SNR, the noise is scaled to theADC’s dynamic range, whereas with a positive SNR, itis the signal that is scaled to the dynamic range. This factjustifies a new estimation of the ADC SNR, when DSSSis used, in the context of urban sensor network.Fig. 1. Simulated transmission chain in Agilent ADSIII. QUANTIZATION REQUIREMENTS ON A SPREADSIGNALTo find the best resolution when using DSSS (i.e. thesmallest resolution that allows to properly demodulatethe data), a simulation has been set up on Agilent ADSsoftware[6], returning the Bit Error Rate (BER) for a givenSNR and ADC resolution. The simulated transmissionchain is shown in Fig. 1. A binary signal is first generatedand spread using a pseudo-noise (PN) sequence. Then,a white Gaussian noise is added to the signal, whichis filtered, digitized and de-spread. The quality of thetransmission is measured via the BER with the MonteCarlo method.Fig. 2 shows the simulated BER as a function of theADC resolution. The BER is plotted for several Eb/N0 toshow the ADC’s performance in a large enough operatingrange. It can be seen that BER is degraded with a lowADC resolution, because quantization noise is strongerwith a lower ADC resolution. If ADC resolution increases,quantization noise is smaller, and thermal noise becomespreponderant. Eb/N0 converges therefore when quantiza-tion noise becomes negligible compared to thermal noise.This happens from a resolution of 4 bits, or 5 bits whenEb/N0 is 9 dB, as it can be seen on Fig. 2. The worstresolution value is kept in the following to guarantee agood digitization in every case.It is thus considered that a resolution of 5 bits is requiredto properly demodulate a spread signal. This confirms whatis commonly done in DSSS systems, where an empiricalvalue of 5 bits is considered to be necessary for digitizingone signal.IV. SIMULTANEOUS RECEPTION OF TWO SIGNALSA. Resolution requirements analysisTo understand what the near-far problem implies onthe receiver architecture, the ADC resolution has to beexpressed as a function of the power of two signals ofdifferent magnitudes. It is supposed that a high and a lowstrength signals are simultaneously treated on the receiverin the same frequency band, but in different channels toallow filtering. The RMS magnitude of the strong signalis noted Ss, and the RMS magnitude of the weak one isnoted Sw. The input signal (whose amplitude is the sum0 2 4 6 8 1010−510−410−310−210−1ADC resolution (bits)BER  Eb/N0 = 3 dBEb/N0 = 5 dBEb/N0 = 7 dBEb/N0 = 9 dBFig. 2. Simulated BER vs ADC resolution of a DSSS signalwith a spreading factor of 16of the weak and strong signals’ amplitudes) is scaled tothe dynamic range of the ADC. In this subsection, we findthe resolution that introduces the same quantization noiseon the weak signal when digitizing simultaneously twosignals than if only the weak signal was digitized.As the dynamic range can be expressed as ∆ ·2n, where∆ is the quantization step, one can write:∆ · 2n = (Ss + Sw) · 2√2K(1)where K is the scaling factor, meaning that K = 0.8 ifthe input signal occupies 80 % of the dynamic range.The quantization noise brought by the ADC is:NQ =∆2√3(2)From (1) and (2), the signal-to-quantization noise ratio(SNQR) of the weak signal can be expressed as:SNQRw =SwNQ= K · SwSw + Ss· 2n ·√32(3)If only the weak signal was received, a resolution nwwould be needed to have an acceptable BER. Then theSNQR would be:SNQR = 2nw ·√32(4)To find what resolution allows to have the same SNQR(and so the same digitization quality) on the weak signalwhen digitizing a strong and a weak signal, an identifica-tion is done between (3) and (4). The result is given in thefollowing equation:n = nw + log21 +SsSwK(5)As the resolution nw is known to be 5 bits from theprevious section and K is easily assessable, the neededresolution to digitize a weak and a strong signals has beenexpressed as a function of these signals’ amplitudes ratio.The following subsection first estimates the maximum ratiobetween Sw and Ss, based on a worst-case scenario. Thenthe minimum required ADC resolution is discussed, withfeasibility assessment elements.B. Minimum required resolution in a worst-case scenarioThe power of the strongest signal is considered to be thepower of a signal emitted from a node located at 10 metersfrom the receiver. This distance has been chosen fromthe SmartSantander project [7] for its representativenessof what is encountered in sensor networks. The powerreceived at 10 m from the emitting node is calculated basedon the propagation model Winner+ [8]. The emitted powerhas been estimated to be 14 dBm from existing systems,and Winner+ gives a 48.5 dB attenuation at 10 m in urbanarea. The maximum power that can be received is thus-34.5 dBm.To evaluate the minimum power that can be received,link budgets have been done for several technologiesthat are considered to be common in our application. Inparticular, we studied WMbus and the IEEE 802.15.4k, toobtain the maximum sensitivity of these technologies, andthus the minimum power that must be properly received.The link budgets lead to a received power ranging from-137.2 to -34.5 dBm, hence a Ss/Sw ratio varying between0 and 102.7 dB.This result is injected in (5) to obtain the Fig. 3, wherethe needed ADC resolution is plotted as a function ofSs/Sw. Useful resolution has been set to 5 bits, accordingto the simulation results. It can be seen on the Fig. 3 thatwhen Ss/Sw = 0 dB, the needed resolution is 7 bits. Onesupplementary bit is indeed needed to digitize two signalsof same amplitude, and the use of a scaling factor makesa second supplementary bit necessary.The limit power ratio is represented in dashed line, andleads to a minimum required resolution of 23 bits with apower ratio between the two signals of 102.7 dB. It canbe seen in [9] that an Effective Number Of Bits (ENOB)of 14 bits can be reached when digitizing with a samplingfrequency above 10 MS/s. As the sampling frequency mustbe at least 16 MS/s to digitize the 8 MHz band, it can besupposed that the ENOB will be lesser than 14 bits.Other ways must then be found to digitize all the bandwith a sufficiently high resolution to demodulate simulta-neously received signals, like parallel subbands processing.0 20 40 60 80 100 12068101214161820222426Needed ADC resolutionPower ratio between strong and weak signals (dB)64256102440961638465536262144104857641943041677721667108864Needed number of quantization statesFig. 3. ADC resolution needed vs power ratio between strongand weak signalV. CONCLUSION AND PROSPECTSThe needed resolution to quantify a spread signal hasbeen evaluated to be 5 bits from simulations on AgilentADS. Through theoretical calculation, this resolution leadsto a needed resolution of 23 bits when digitizing twosignals in presence of the near-far problem. This resolutionis too big to allow a direct digitization of the 8 MHz band,hence another method must be chosen to digitize all theband.Several solutions exist: the band can be split in severalsub-bands individually digitized, and the gateway’s goodworking can be only guaranteed for a given Ss/Sw ratio,which must be big enough to cover most of the casesencountered in urban sensor networks.Oversampling is another way to explore, since one bitof resolution can be added to the ADC resolution bymultiplying the sampling frequency by a factor of 4.REFERENCES[1] ETSI, TR 103 055, september 2011.[2] L. Mainetti, L. Patrono, and A. Vilei, “Evolution of wireless sensornetworks towards the internet of things: A survey,” in Software,Telecommunications and Computer Networks (SoftCOM), 2011 19thInternational Conference on, 2011, pp. 1–6.[3] H. Lehpamer, RFID Design Principles. Norwood, MA, USA: ArtechHouse, Inc., 2007.[4] IEEE Std 802.15.4k-2012 (Draft, last revision: october 2012), 2012.[5] European Standard Std. prEN 13 757-4, Rev. 2011: E, September2011, draft.[6] Agilent Avanced Design System,http://www.home.agilent.com/en/pc-1297113/advanced-design-system-ads.[7] Smart Santander, http://smartsantander.eu/.[8] J. Meinilä et al., WINNER+ Final Channel Models, Petteri Heino ed.,Wireless World Initiative New Radio – WINNER+, June 2010,delivrable D5.3.[9] B. Jonsson, “A survey of A/D-Converter performance evolution,”in Electronics, Circuits, and Systems (ICECS), 2010 17th IEEEInternational Conference on, 2010, pp. 766–769.

SDR for SRD: ADC specifications for reconfigurable gateways in urban sensor networks

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SDR for SRD: ADC specifications for reconfigurable gateways in urban sensor networks

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