OPTIMAL MODULATION SCHEME FOR ENERGY EFFICIENT WIRELESS SENSOR NETWORKS

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1 OTIMA MODUATION SCHM FOR NRGY FFICINT WIRSS SNSOR NTWORKS Rajoua Anane 1,, Kosai Raoo 1, Maha Ben Zid 3, Ridha Bouallegue 1 aboratory o Acoustics at University o Maine, AUM UMR CNRS no. 6613, e Mans, France Innovation o Communication and Cooperative Mobiles, Innov COM, Tunis, Tunisia 3 National ngineering School o e Mans (NSIM), e Mans, France rajoua.anene.etu@univ-lemans.r, kosai.raoo@univ-lemans.r, maha.ben-zid@univ-lemans.r, ridha.bouallegue@ieee.org Keywords: Wireless Sensor Network, nergy iciency, MQAM, MFSK, MSK, MSK. Abstract As wireless sensor networks are constituted o nodes with limited lie batteries, energy eiciency is a very important metric at all levels o system design. Thereore, perorming optimal modulation schemes is a crucial task at the physical layer o this class o networks. This paper investigates the best modulation strategy to minimize the total energy consumption required to send a given number o bits. nergy consumption with digital modulation schemes including M-ary QAM (MQAM), M-ary SK (MSK), M-ary FSK (MFSK) and MSK are analytically analyzed and simulated over transmission time, modulation rate and transmission distance. A comparative analysis o energy consumption reerring to MSK modulation is presented in this paper. We show that the gain achieved with MSK modulation is very promising to obtain optimal energy network consumption. 1 Introduction The research in the ield o sensors is at present undergoing an important revolution and opens signiicant perspectives in numerous ields o application. The wireless sensor networks (WSN) is an emerging class o communication networks. It has increasingly attracted many researchers in the ield o Telecommunications. The increase o the autonomy o these sensors is the main ocus o research in this domain. Technology evolution and circuit design progresses are not suicient to solve the crucial problem o energy in wireless sensor networks. The eorts so ar made in the modulation schemes with optimal parameters also helps to narrow this energy gap. Several pieces o researches evoked the eect o modulation scheme on energy eiciency. For example, [1] analyzed the binary and M-ary modulation techniques. It showed that M-ary modulation is more energy eicient than binary. In [] the authors compared perormance o MQAM and MFSK modulation schemes in AWGN channel condition. Felipe and Hideki in [3] compared three dierent modulation techniques i.e. MQAM, MSK, and MFSK. They presented relation between signal to noise ratio and channel capacity or cuto rate to ind the optimized parameters or minimizing the energy consumption. The contribution o this paper is the comparative analysis o our types o modulation requently used in wireless communications namely MQAM, MSK and MFSK. The perormance o MSK modulation is analyzed and compared with the other modulation to improve the energy eiciency and bandwidth eicient in a wireless sensor network. This paper is organized as ollows: Section presents the system model parameters. Section 3 provides a detailed analysis o dierent modulation techniques. In Section 4 comparison results is discussed ollowed by the conclusion in Section 5. System Modeling arameters or a Wireless Sensor Network.1 Scenario We consider a wireless sensor networks consisting o sensor nodes that can collect and transmit inormation to a central node. These nodes are denoted S i with I = {1,,, }. Suppose that a source node S 1 send bits o data to a destination node S 5 in a deadline T seconds. The communication link between two sensor nodes will be modelled by an additive white Gaussian noise (AWGN) channel.. Transceiver Model In this paper, we perorm the transmitter and receiver hardware model as introduced in [3]. The transmitter block is composed o a digital to analog converter (DAC), a ilter, a requency synthesizer, a mixer and a power ampliier (A). At the receiver side, a ilter, a ow noise ampliier (NA), requency synthesizer, a mixer, an intermediate requency ampliier (IFA) and an analog to digital converter (ADC) are implemented. The energy consumed by both the transmitter and the receiver blocks will be evaluated or calculating the total energy consumption in the network. We assume that powers consumption o ilter at the transmitter blocks and receiver blocks are the same. Case o requency modulation schemes (MFSK and 5

2 MSK), power consumption o both the DAC and the mixer will not be included in the calculation o the total power consumption [3]..3 reliminary Assumptions It s assumed that transceiver circuit o a sensor works according to three modes: When there is data to transmit the sensor operates in the active mode so all these circuits are active. I there is no inormation to send the circuits switch to standby mode. This contributes to energy saving and power consumption is negligible. Knowing that switching rom standby mode to active mode, the energy overhead caused by start-up transients is also signiicant and must be taken into account. This temporary state called transient mode which is used to set up the requency synthesizer o the local oscillator. To summarize, the energy consumed during the transient mode is considered constant or a speciic hardware but in a sleep state we can assume that it is equal to zero. In this paper we emphasis our analysis on minimizing the active mode power consumption. According to the above assumptions, the transmission period T is given by: T = T + T + T (1) start on _ time stby T start is the time o the transient mode. T on-time represents the time spent to transmit bits. T stby is the duration o the standby mode. owers consumption associated to the described modes are denoted as: start : ower consumed or mode changing. on-time : ower consumed or transition stby : ower consumed during standby mode (assumed to be null or simpliication) Correspondingly, we can derive the equation o the energy consumed data as ollows: = T + T total on _ time on _ time start start ( ) + ( + ) T = T tx tx circuit rx circuit A on _ time tx circuit rx circuit start tx represents the power o data transmission. tx-circuit and rx-circuit are respectively circuit powers or transmitter and receiver without considering the ampliier. We denote: x is the power consumption o device x. xpressing each term: tx circuit = DAC + ilt + mixer + syn (3) () rx circuit = ADC + ilt + mixer + syn + NA + IFA (4) The power o the ampliier is expressed as: A ξ = 1 η tx (5) ƞ represents the drain eiciency o the ampliier. ξ is the peak to average ratio that depends on the modulation technique and is expressed as a unction o M 1 constellation size M as [4]: ξ = 3 M + 1 ξ = 1 or requency modulations i.e. MFSK, MSK. The total energy expression or both the MQAM and MSK modulation techniques are derived as: / = 1+ 1 T + + T + T total MQAM MSK tx on time tx circuit rx circuit on time syn start Similarly or MFSK and MSK: / = 1+ 1 T total MFSK MSK tx tx on time ( ) T ADC ilt mixer syn NA IFA on time + T syn start 3 Analysis o Dierent Modulation Techniques 3.1 Modeling o nergy or Node-to-Node Communication In this section a communication link connecting two wireless sensor nodes is considered. Simulations shown below are perormed with MATAB. 3. M-ary Quadrature Amplitude Modulation For M-ary QAM, we deine M = b where b is the number o bit per symbol. A sensor node must transmit bits within a period T on-time. On the one hand we deine the number o transmitted symbols by: s = /b. On the other hand, s = T on-time /T S where T s is symbol duration. Thereore, b Ts Ton time (6) (7) = (8) et us assume that, square pulses are used or all modulation techniques. The channel bandwidth B equals 1/T s. Thus, the number o bits per symbol can be expressed by: b = (9) BTon time With the data rate R b and the channel bandwidth B, we may express the bandwidth eiciency, as: R bt B ρ = b = (1) B Using (8) and (1) we deduce that: ρ b. The error probability evaluated in the case o AWGN 51

3 channel is expressed in terms o average value o the transmitted energy [4] as: ( ) 1 1 erc 3SNR M 1 M (11) SNR is the signal-to-noise ratio equal to b /N. The unction erc(.) denotes the complementary error unction, t given by erc( x) π = e dt x The error probability could be also expressed as: e b M 3 SNR ( ) M 1 The signal to noise ratiois approximated by: rx ( BN σ ) (1) SNR = (13) rx is the received power. N is the receiver noise igure. σ is the AWGN power spectral density Hence, the received signal power can be written as: 4 1 rx = Bσ N ( M 1) ln 4(1 ) b 3 M (14) The power o the signal in the output o the transmitter is calculated by the equation o K th path loss model [5]. We can state that: = G (15) tx rx d Or, G d = G 1 d k M 1 represents the power gain actor, G 1 is the gain actor at 1 m, M 1 is the link margin and d (meters) is the distance that separate two communicating nodes. The exponent order k is between and 4, in this paper k = 3 is selected. The transmission energy is given by: = T tx MQAM tx on time M = N σ ( M 1) ln Ton timegb d 3 b e (16) Using (6) and (15), the expression o total energy consumption is: N M total MQAM = + σ M ln G d BT b e + T + T circuit on time syn start on time (17) The energy consumption per inormation bit is calculated as ollows: in bit = total (18) Derived relationships between energy consumption and transmit-on time (T on-time ) are simulated and shown in Figure 1. The vertical axis presents the energy in terms o decibels relative to a 1-3joule: 1log 1 ( inbit 1 3 ) db mjoule, and the horizontal axis is the normalized transmission time (T on-time /T). The setting parameters considered in simulation are reported in Table 1 []. Table 1. Simulation parameters. arameters T start T σ Value s.1 s 1 3 bit k 3 ƞ B Carrier requency e.35 or MQAM/MSK,.75 or MFSK/MSK 1 4 Hz.45 GHz 1 3 G M t 1 4 ADC DAC ilt syn NA IFA mixer N 6.7 mw 15.4 mw.5 mw 5 mw mw 3 mw 3.3 mw 1 db The variation o optimum transmit-on-time or dierent values o transmission distance is shown in Figure 1. nergy per inormation bit (db mjoule) d=1m d=3m d=1m Figure 1. Total energy consumption per bit inormation inbit - MQAM or MQAM (AWGN). These curves were plotted or < T on-time < 1 which corresponds to constellation size between and 16. We can see that there are a large number o changes in 5

4 the variable T on-time or long distance as compared to short distance and that the total energy consumption is not a monotonically decreasing unction. For ixed B and we can deduce an optimum T on-time or AWGN channel using this simulation. Indeed or d = 1 m and at the optimal case when T on-time < T T start (T on-time.t) the total energy consumption per inormation bit is about 7 db lower than the case where T on-time T. At d = 3 m we notice also about 4 db energy saving under optimized case. nergy per inormation bit(db mjoule) Total nergy Transmission nergy Total energy per inormation bit (db mjoule) Total energy d=1m Total energy d=3m Total energy d=1m Transmission nergy d=1m Transmission nergy d=3m Transmission nergy d=1m Modulation speed, R (bauds) Figure 3. nergy per inormation bit versus speed o modulation, MQAM (AWGN) or d = 1 m. nergy consumption per inormation bit inbit-mqam and transmission energy tx-mqam are drown over modulation rate b or d = 1 m in Figure 4. 3 Total energy Only transmission energy Figure. Total energy consumption per bit inormation inbit- MQAM and transmission nergy tx-mqam, MQAM (AWGN). It is obvious that the more the transmission distance increases the more the transmission energy is important. However, energy consumption by circuits is independent o d. Thereore or a certain threshold value o d, no energy savings could be possible by optimizing T on-time. Both o total energy and transmission energy are plotted in Figure. It is seen, that or small distances, there is a remarkable dierence between the total energy consumed and transmission energy. This dierence is less important or longer distance. The constellation size can be related to the speed o modulation given in symbols per second (bauds) which depends on bit rate D and modulation rate b: D R = b = bt (19) on time Hence, Ton time = () br quivalently, total energy consumption can be ormulated in terms o speed modulation as ollows: total MQAM = + N σ ( M 1 ) 3 (1) 4 4 M ln GB d + circuit + syntstart log( M ) e br br Figure 3 depicts the variation o energy consumption which decays with the modulation speed. We also remark that when the modulation speed increases, the constellation size decreases resulting in energy decreasing. nergy per inormation bit (db mjoule) Modulation Rate, b Figure 4. nergy per inormation bit versus Modulation rate or MQAM (AWGN). We can deduce that the optimal number o bit per symbol b opt is about 8 i we consider the total energy and b opt = when only transmission energy is taken into account. 3.3 M-ary hase-shit Keying (MSK) The bit per symbol b or MSK modulation scheme depends on the time spent to transmit bits T on-time as deined or MQAM modulation. et us assume that MSK uses the same hardware coniguration as the one used or MQAM. The bit error probability or AWGN channel is expressed as ollows [4]: e ( sin( π )) erc SNR M () Using quations (6), (9), (13), (15) and (), the total energy consumption is derived as: total MSK π = 1+ 1 N σ ln sin η b M G BT + T + T d on time circuit on time syn start (3) 53

5 Total energy per inormation bit (db mjoule) Figure 5. nergy per inormation bit or MSK (AWGN). The total energy consumption ( inbit-msk ) as a unction o T on-time.or transmission distances d = 1, 3 and 1 m are shown in Figure 5. The numerical values considered or these curves are the same as those used or MQAM modulation. Total energy per inormation bit (db mjoule) d=1m d=1m d=3m Figure 6. nergy per inormation bit versus modulation rate, MSK (AWGN). Case o MSK technique and under AWGN channel condition, the optimum b or d = 1, 1, 3 m are respectively equal to 7, 4.7 and (Figure 6). 3.4 Multiple Frequency-Shit Keying (MFSK) Remember that, or MFSK we must eliminate the two components noted earlier, the DAC and the mixer o the hardware coniguration since FSK can be implemented by a simple direct modulation such as - modulator. In this section analysis is done or non-coherent MFSK [3]. et us assume that signals are orthogonal and the adjacent signals are separated by 1/Ts. The bandwidth channel is deined as: B = M/Ts. Thereore, B= R b M/log M. Using the previous equation and (1) we can derive bandwidth eiciency expression as: log M b ρ = = (4) M b d=1m d=3m d=1m Modulation rate, b The bit per symbol o MFSK modulation can be related to the transmit on-time as ollowing: b = (5) b BTon time The probability o error or no-coherent MFSK detection is expressed as [4]: ( M 1) erc ( SNR ) (6) Hence, We can deduce that: b γ = ln e On the other hand we ind that [4]: γ b e SNR (7) (8) = brxb σ N (9) where rxb represents the energy per inormation bit at the receiver: = T (3) rxb rx on time Using (7), (8), (9) and (3) we deduce the received signal power as ollows: 4 ln ( b B rx = N σ ) (31) M Knowing that tx = rx G d and tx = tx T on-time We obtain: 4 ln b tx MFSK = N σ Gd b (3) Then the total energy is: b total MFSK = N σ ln ( ) Gd b (33) + T + T circuit on time syn start And the total energy consumption per inormation bit inbit-mfsk is deduced rom (33) and (18). Total energy per inormation bit (db mjoule) d=1m -18 d=3m d=1m Figure 7. nergy per inormation bit inbit-mfsk, MFSK (AWGN). In these simulations, we keep the same values or the 54

6 bandwidth B and the packet size and we change the value o drain eiciency to.75 and that o transmission period T to 1.1 s. In act, MFSK modulation needs a longer transmission time to send bits due to its lower bandwidth eicient comparing to MQAM and MSK modulations. Figure 7 shows that the total energy is an increasing unction o T on-time or short distance (1 m - 3 m) and under optimized case, we observe about 7 db energy savings compared to the case where (T on-time = T). nergy per inormation bit (db mjoule) Total energy d=1m Total energy d=3m Total energy d=1 m Transmission nergy d =1m Transmission nergy d =3m Transmission nergy d =1 m Modulation rate, b Figure 8. nergy per bit versus Modulation rate or MFSK (AWGN). Curves plotted in Figure 8 represent the total energy and transmission energy as a unction o b. It is clear that the transmission energy decreases when b increases. Thereore, better energy eicient is obtained when constellation size is larger. The optimal data rate b in this case is 6. Nevertheless, based on the total energy measurements, the optimal value o b is 1.5 or d = 1 m and d = 3 m and or d = 1 m. Approximately 8% energy savings is achieved by using optimal b opt = 1.5 compared with the non-optimized case where T on-time = T (b = 6). This result agrees with [3]. 3.5 Minimum-Shit Keying (MSK) MSK can be viewed as a special orm o continuous phase-requency shit keying, (CFSK) where the deviation index is precisely equal to ½. A modulation index o.5 corresponds to the minimum requency spacing that allows two FSK signals to be coherently orthogonal. Where we consider the same coniguration as that used or MFSK modulation. The requency dierence is equal to 1/T s. A bound on the probability o error or MSK is written as [4]: 1 erc ( SNR ) (34) Thereore, we can deduce: SNR e (35) Next the energy per inormation bit at the receiver is: 1 rxb = NNSNR σ NN ln (36) e By ollowing the same process used or previous modulations: rxb = tx Gd rxbgd T = (37) Total energy per inormation bit (db mjoule) And, s Ton time tx MSK = NN σ ln 1 G d (38) nergy consumption per inormation bit is written as: NN ( ) G circuitton time synt start in bit MSK = 1+ 1 σ ln 1 e d Figure 9. Total energy per inormation, MSK (AWGN). (39) d=1m d=3m d=1m The plot o inbit-msk over T on-time in the case o MSK technique is presented in Figure 9. Not surprisingly, energy consumption is also an increasing unction o transmiton time and optimal T on-time =.1T. Furthermore, in the optimal case, or d = 1, 3 and 1 m we respectively obtain about 1, 9.5 and 5.5 db o energy savings compared to the non-optimized system (T on-time = T). 3.6 Modeling o nergy Aware Routing Our objective is to evaluate in terms o energy the perormance o realistic wireless sensor network in an indoor scenario. y S1 S x Figure 1. An example o random distributed sensors network o 1 m. 55

7 We consider a small scale network based on nodes capable o collecting and transmitting inormation to a central node. These sensors are deployed in non-deterministic mode (randomly) over an area o about 1 square meters and can have dierent sensitivities. Routing data rom the source sensor node to the destination one can use intermediate nodes to relay inormation (Figure 1). The energy consumed along the route is calculated as ollows [6]: n 1 n 1 i R = = ( tx + rx ( + 1)) on time i= 1 i= 1 (4) t i i T where, i (t) is the energy o node S i at time t, tx (i) is the transmission power o node S i, rx (i) is the receiving power o node S i and n is the number o node. The ormula (4) is used or energy calculation aware routing in the ollowing. 4 Comparison Results 4.1 oint to oint Communication Total energy per inormation bit (db mjoule) MQAM MSK MFSK MSK Figure 11. Comparison o dierent modulation techniques or node to node communication, d = 1 m. The total energy per inormation bit versus transmit-on time curves are shown in Figure 11. The simulations are presented in the case o our modulation techniques. We deduce that MSK permits or the best energy consumption comparing to the other modulation techniques. 4. Inter-Nodes Communication Through Relay Among the sensor nodes, we will evaluate energy consumption o communication between the node S 1 and the node S 5 (Figure 1). We can derive the expression o total energy consumption or each modulation technique or inter-nodes communication through relays rom above equations. From (17), (18), (3), (33), (39) and (4). Then, total energy consumed along the route is redrawn using optimal parameters deduced previously or the our modulation schemes. nergy per inormation bit (dbmjoule) Figure 1. Comparison o dierent modulations or inter-nodes communication at optimum constellation and transmit-on time. Figure 1 depicts the comparison o energy consumption during an inter-nodes communication or dierent modulations. In this scenario, we consider an inter-nodes communication through relay. Distance between nodes is randomly taken within a range o 1-1 m. We assume that there are about 3 intermediate nodes or routing inormation. The simulation results conirm that the MSK modulation is most energy eicient. It is observed that using MSK modulation in this scenario, we obtain about 16 db energy savings compared to MQAM, 31 db compared to MSK and 5 db compared to MFSK. 5 Conclusion The comparative analysis concludes that MSK modulation becomes more advantageous than its counterparts in an energy point o view. The results also disclose that, MSK may be a good choice or wireless sensor network, because this modulation schemes has a high bandwidth eicient and it has the advantage o being simple to generate, simple to demodulate and has a constant envelope. The obtained results can be used as a design guideline or coded modulation techniques in WSN. Reerences nergy per bit (dbmjoule) [1] Shih,., Cho, S.H., Ickes, N. and Min, R. (1) hysical ayer Driven rotocol and Algorithm Design or nergy icient Wireless Sensor Networks. MOBICOM 1, Rome, Italy, 15-1 July 1. [] Cui, S., Goldsmith, A. and Bahai, A. (5) nergy- Constrained Modulation Optimization. I Transactions on Wireless Communications, 4, [3] Costa, F.M. and Ochiai, H. (1) A Comparison o Modulations or nergy Optimization in Wireless Sensor Network inks. roceedings o the I Globecom Conerence. [4] roakis, J.G. () Digital Communications. 4th dition, McGrawHill, New York. [5] Rappaport, T.S. () Wireless Communications rinciples and ractice. nd dition. [6] atil, A.., Sharanya, B., Dinesh Kumar, M.. and Malavika, J. (13) Design and Implementation o Combined nergy Metric. International Journal o Computer and lectrical ngineering, 5. 56

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