Optical Wireless Links as an Alternative to Radio ... - IEEE Xplore

2002

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 33, NO. 9, SEPTEMBER 2015

Optical Wireless Links as an Alternative to Radio-Frequency for Medical Body Area Networks Ludovic Chevalier, Stephanie Sahuguede, Member, IEEE, and Anne Julien-Vergonjanne, Member, IEEE

Abstract—It is now established that optical wireless communications (OWC) technology is a promising alternative or a complement to radio-frequencies for indoor transmissions. Considering that using OWC permits the reduction of electromagnetic pollution in human environment, this technology can be also a good candidate for wireless body area networks (WBANs) in particular for medical applications such as health monitoring. In this paper, we investigate the use of on-body OWC for mobile medical WBAN. Based on transmission scheme exploiting diffuse optical reflections over the patient environment, we investigate a star BAN topology using spreading codes for multiple access. We have developed a theoretical analysis to determine the performance of such network considering that the patient is moving in the room. The achievable quality of service for a typical health monitoring application is reported and discussed regarding the performance required by medical applications. Index Terms—Diffuse transmission, infrared technology, mobile healthcare monitoring, optical wireless communication, optical CDMA, BAN.

I. I NTRODUCTION

T

ODAY, it is recognized that wearable medical devices incorporating wireless transmission capabilities are a key technology enabling individuals to monitor their health and thus to be engaged in their wellness management [1], [2]. By early stage detection, these devices can permit preventing diseases and thus allow reducing healthcare costs, that is a big challenge given the expected aging population increase. Besides, when they are integrated into medical center networks, these systems have also the possibility to decrease workload of medical personal, resulting in higher efficiency. A set of such devices connected to sensors and located near or inside the human body constitutes a Wireless Body Area Network (WBAN). The WBAN devices or nodes are scattered in and over the whole body and thus there are different transmission channels and frequency bands according node locations [3]. Recently, WBAN applications have evolved to cover short range wireless communicating objects in and around human body. Indeed, many objects worn on the body can be connected, watch or glasses for example. In 2012, the Task Group IEEE 802.15.6 published the first standard dedicated to WBAN and on-body communications [4]. Manuscript received May 27, 2014; revised November 7, 2014; accepted March 10, 2015. Date of publication May 13, 2015; date of current version August 17, 2015. The authors are with University of Limoges, XLIM UMR, Limoges 87000, France (e-mail: [email protected]; [email protected]; [email protected]). Digital Object Identifier 10.1109/JSAC.2015.2432527

The standards are based on Radio-Frequency (RF) technologies which have to face several challenges in terms of size, consumption, interference and reliability. Moreover, various results have shown that the on-body RF channel model is complex due to shadowing caused by the human body movement but also due to multipath fading resulting from reflections and scattering of electromagnetic waves on the objects around the human body [5]–[7]. Besides, in sensitive environment, electromagnetic radiation can be an issue such as in a hospital care unit where the risk of electromagnetic interferences with other medical devices and instrumentation has to be considered [8]. In addition, the question of prospective health effects of RF signals, in particular long exposure impact, is still open which could hinder the development of this technology [9]. Optical wireless technology can be a complementary solution to RF for WBAN and has the potential of reducing the amount of RF effects in patient vicinity. Actually, Optical Wireless Communication (OWC) systems based on infrared or more recently visible wavelength range ensure that there is no interference with existing RF networks or electronic equipment. For many years, OWC systems have been developed for indoor and outdoor applications [10]–[15]. Considering indoor communications, these systems have many advantages such as being low-cost, compact, easy to deploy, having high bandwidth (terahertz), no need for licenses and a great level of security because light cannot pass through walls [12]. Moreover, unlike RF channels, it is known that OWC links do not suffer from multipath fading and can be only affected by multipath distortion [13] especially for high data rates. As a result, OWC constitutes a good candidate for medical WBAN where applications occasionally require high data rates. Most of the time, the medical data needs induce low data rate transmissions, e.g., for continuous monitoring of physiological signs such as blood pressure, heart rate or body temperature [2], [16]. However, WBAN transmission requirements in terms of Quality of Service (QoS) involve studying robustness and reliability of optical wireless links in such context, in particular because of the expected Bit Error Rate (BER) generally lower than 10−10 [1], [2]. According WBAN topologies and architectures [2] and in the context of wearable health monitoring, it is possible to consider the use of some optical links as an alternative to RF: OWCs can be established either between medical nodes and the coordinator (case (a) in Fig. 1) or between the coordinator and an access point being part of indoor infrastructure (case (b) in Fig. 1). These two cases correspond to WBAN scenarios classified as S4 to S7 in IEEE standard [2], [4]. For mobile health monitoring

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CHEVALIER et al.: WIRELESS LINKS AS AN ALTERNATIVE TO RF FOR MEDICAL BODY AREA NETWORKS

Fig. 1. Possible uses of optical link in medical WBAN scenario.

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In order to differentiate the communicating nodes, we will use in this work Optical Code Division Multiple Access (OCDMA) scheme because of its flexibility, ease of implementation and no need for synchronization among the nodes [13]. Besides, as the patient equipped with the WBAN sensors may be in motion, we will consider that the body positions in the environment and the node orientation are randomly distributed. In addition, the nodes are randomly distributed on the body to reflect the fact that they could be positioned anywhere. The paper is organized as follows. Section II describes the studied system and the WBAN scenario. The optical wireless channel model used in this study is presented in Section III. Section IV presents OCDMA scheme and the development of theoretical error probability of the communication system. Results in terms of probability of satisfying a given BER are presented in Section V as a function of node power and node number before concluding in Section VI. II. S YSTEM D ESCRIPTION

Fig. 2. Diffuse optical links to establish communications between the nodes and a coordinator placed on the body.

application, recent studies have explored the performance of OWCs between a central unit placed on a patient and a base station fixed in the indoor environment (case (b)) [17]–[20]. The published theoretical and experimental results have confirmed that optical wireless can be a suitable solution to transmit data related to healthcare at maximal data rates around 10Mbps. However, no work is reported on the communications between several nodes located on the body as in case (a). In this paper, we investigate this latter scenario by using diffuse optical links to establish communications between the nodes and a coordinator placed on the body (see Fig. 2). Actually, among the different optical wireless link configurations, the most performing one is the Line Of Sight (LOS). However, LOS scheme is not adapted to WBAN scenario because it is difficult to establish a direct optical link between two nodes considering the variety of human body morphologies and the body movements. Consequently, we consider Non-LOS (NLOS) scheme exploiting diffuse optical reflections over the environment. We have already investigated a static monitoring scenario where only one sensor placed on a patient lying on a bed is communicating with another node by using diffuse optical transmission [21]. Here, our main objective is to initiate the study for mobile WBAN by theoretically evaluating the performance and the robustness of OWC technique for medical monitoring scenarios.

We consider a WBAN scenario where a patient is equipped with N medical sensors, each coupled with an optical wireless emitter and communicating with a coordinator node including the optical receiver. As previously mentioned, a wearable system based on a LOS transmission with tracking devices to ensure node alignment, is not adapted to the simplicity criterion of BAN. Moreover LOS scheme can suffer from high degradation because of blocking experiments. Thus, we study the use of non-LOS links to be less sensitive to pointing and shadowing constraints. Each emitting node includes an ideal Infrared (IR) optical source of Lambertian order m = 1 producing optical beams as presented in Fig. 2. Because of the roughness of typical indoor environment surfaces, characterized by a reflectivity parameter ρ, it is possible to consider that diffuse reflections are generated when the beam hits the surface [13]. Then, the reflected signals are collected at the coordinator node by the optical receiver consisting in a photo-detector supposed to have a large Field of View (FOV) of 70 degrees and a physical surface A of 1 cm2 . To simplify the analysis, we assume that all the nodes are in the same plane. But, to deal with the fact that the sensors can be placed at different positions on the body, each node position is randomly and uniformly distributed over this plane surface representing a body shape of height 1.75 m as shown in Fig. 3. To account for body movements implying variations of sensor orientation, we consider in the study a two dimensional uniform distribution of the emitting nodes directions along the azimuth and elevation angles respectively φ and θ . An example corresponding to a node located at the ankle is shown in Fig. 3. Besides, we adda constraint on the impact of the patient body, which is supposed to be a blocking surface for emitted optical beams. On the other side, the coordinator node, including the optical receiver and represented by a circle in Fig. 3, is assumed to be fixed on the body surface. In this study, it is placed at a height of 1.5 m corresponding to patient shoulder and at a width of 32.5 cm from the right arm and could be integrated into a vest worn by the patient. This position was chosen because

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Fig. 3. Body shape and coordinator node position.

Fig. 5. PDF of the impulse response length.

An IR channel with IM/DD can be modeled by a linear system and the received signal y(t) is thus written as: y(t) = R.x(t) ⊗ h(t) + n(t)

Fig. 4. Hospital room.

it offers advantages over conventional one which are usually at the belt. Indeed, it seems clear that the receiver located at the shoulder can more easily collect reflected optical beams for patients with different health problems for example in the case of disabled patients in wheelchairs. Besides, as a first approach, the optical receiver direction is supposed to be oriented so as to be perpendicular to the patient body. Moreover, we also consider that it is uniformly distributed along the azimuth angle φ reflecting the fact that the patient can turn in all directions. Finally, we suppose that the patient is in motion within the indoor environment. To take into account this mobility, we use a two dimensional uniform distribution of the body shape positions in the studied room. In this study, we investigate two kinds of environment. The first one is an empty room of dimensions (x = 3 m, y = 4 m, z = 2.5 m) which matches the size of a typical hospital room for a single patient. The second environment has greater dimensions (x = 7 m, y = 5 m, z = 2.5 m) and includes obstacles such as beds and medical equipmentas shown in Fig. 4. This indoor environment is the same as the one described in the IEEE 802.15.6, which was used to evaluate the UWB channel model, known as CM3, for on-body communications [4], [5]. III. C HANNEL M ODEL Data are sent using Intensity Modulation and Direct Detection (IM/DD). The received signal thus depends on the incident optical power and the photo-detector responsivity R.

(1)

where x(t) is the transmitted signal, h(t) represents the impulse response of the optical channel, and n(t) is an Additive White Gaussian Noise (AWGN). The impulse response of diffuse optical channel can be obtained using ray launching methods to entirely model the indoor environment and to take into account all the optical beam reflections. To achieve this purpose, a ray-based simulator developed at the XLIM Laboratory is used [22]. It is based on classical ray-launching technique associated to Monte Carlo algorithm. This method was implemented to determine the impulse response of the optical wireless link between one node and the coordinator for the WBAN configurations described in Section II, i.e., considering node locations and orientations on the body and body positions in the different rooms. Thanks to these calculations, we have reported in Fig. 5 the Probability Density Function (PDF) of the impulse response length considering different environments with the same ceiling height z = 2.5 m as presented in Section II, as to know an empty room of dimensions (4 m × 3 m), and an empty room of dimensions (7 m × 5 m) with and without the presence of obstacles. For the ray-launching method implementation, the number of reflections per optical beam has been limited to 3 and all the surface reflection coefficients are set to ρ = 0.8 [13], considering a wavelength of 875 nm. As expected, it can be first noticed that for the emptyrooms, the increase of the room size induces a shift in the impulse response length PDF of nearly 5 ns. This means that optical beams are propagating over a larger distance in the largest room, so the propagation time is higher. Concerning the presence of obstacles, we can remark that it leads to an increase in the mean length of about 1ns compared to the free obstacle room case. Moreover, the PDF curve corresponding to the room with obstacles is about 30% wider than for the empty room. This can be explained by the fact that the optical beam reflections on the obstacles lead to additional paths. Finally, as


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Fig. 7. OCDMA receiver scheme.

IV. T HEORETICAL E RROR P ROBABILITY

Fig. 6. PDF of the optical gain H0 for the mobile WBAN scenario.

shown in Fig. 5, we note that the maximal impulse response length is around 52 ns for the room of dimensions (4 m × 3 m) and around 56 ns for the room of dimensions (7 m × 5 m), which is approximately the same magnitude order as the values we canfind in the literature for optical diffuse channels [10], [13]. Based on these results, and considering that for health monitoring application, the data rates are generally lower than 100 kbps [2], [16], we can neglect the impact of Inter-Symbol Interference (ISI). In the following, we will consider that data are sent with minimal temporal spacing of 70 ns, in order to avoid ISI. This means we can achieve a theoretical maximal data rate of 14.3 Mbps. The impulse response is thus only characterized by its static gain H0 : h(t) = H0 .δ(t)

(2)

Considering the same settings as the one previously used to obtain the impulse response length of the optical wireless channel, the optical gain PDFs have been plotted in Fig. 6, considering an empty room of dimensions (4 m × 3 m), and an empty room of dimensions (7 m × 5 m) with and without the presence of obstacles, for surfaces reflection coefficients set to ρ = 0.8. First, we can remark that the gain PDFs have a high spreading of about 14 dB, because of diffuse propagation. In addition, regarding the two empty rooms, we can note that the mean value of the optical gain for the smallest room is 2.2 dB higher than for the bigger one. It means that the size of the room has a significant impact on the optical gain. This is linked to longer distance propagation in the biggest room, as explained previously. Furthermore, the optical gain PDF corresponding to the room with obstacles is about 20% wider than the one for the empty room, and shows a mean value of the optical gain higher of 1 dB. It can be explained by the presence of additional paths linked to reflections on obstacles. The optical gain distribution obtained in presence of obstacles in the room of dimensions (7 m × 5 m × 2.5 m) will be used in Section V to evaluate the WBAN transmission performance. This will permit evaluating the worst case regarding the two different room sizes presented here, and considering a realistic case regarding the presence of the obstacles.

Considering a star WBAN topology, we investigate OCDMA schemebased on the assignment of a specific code to each BAN node to perform multi-user communications. This is a technique well investigated for indoor wireless IR channels [24] and which potential in terms of flexibility and ease of implementation has been shown. We suppose that each emitting node employs an on/off keying (OOK) modulation to transmit independent and equiprobable binary data. At the emission, each node datum is multiplied by a specific code which is a unipolar Optical Orthogonal Code (OOC) sequence specified by (F, W) with F the sequence length, W the weight and with maximal cross-correlation and auto-correlation equal to 1 [25]. OOCs are not strictly orthogonal, thus the main performance limitation is the Multiple Access Interference (MAI). To mitigate the MAI, one of the simplest ways is using a Hard Limiting (HL) device before correlation [26].We use this type of receiver as presented in Fig. 7. In addition, we consider in the following that there is no ISI at the chip level, which is satisfied if the chip time Tc = Tb /F (Tb = 1/D being the bit time) is higher than 70 ns as presented in Section III.This means that the code length F and the data rate D have to be chosen so that F × D < 14.3 Mbps. At the emission, each emitted data bi is spread by the corresponding binary code ci before being sent over the optical wireless channel. Moreover, we consider an ideal chip synchronous case, which is the worst MAI case. At the reception, the electrical signal on each chip time yj can be expressed as the summation of the N received user data present in this chip: yj = R.

N−1

bi ci,j Hi Pti + nj = dj + Aj + nj

(3)

i=0

where ci,j is the value of ci code on the jth chip (0 or 1 for an OOC), bi is the emitted bit from node i, Pti the emitting power of node iover the chip time, and nj is an AWGN component over the jth chip time. dj represents the desired node contribution and Aj the MAI contribution in the jth chip. The photodiode responsivity R is set to 1 in the following. The first stage of the electrical receiver is based on a Chip Level HLtaking a hard decision on each chip by considering a threshold level sc . Thus, the output signal at each chip time denoted as zj can be expressed as: 0 if yj < sc zj = (4) 1 if yj ≥ sc Then, this binary spread signal is correlated with the OCDMA code of the desired node before being integrated over the bit time to recover the signal over the marked chip times. Finally the decision device of threshold level S provides

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the decided data. If we denote Z the variable obtained after integrating the binary spread signal zj over the W marked chips, the bit error probability Pe can be expressed as: Pe =

1 1 P(Z ≥ S|b0 = 0) + P(Z < S|b0 = 1) 2 2

(5)

by using the numeration index u to count i elements within the W ones. Considering that nj is an AWGN of variance σ 2 , we can express:

p y(u) | b0 =0 ≥ sc = p A(u) + nj ≥ sc l= α

Considering that zj is equal to 0 or 1, Z obtained by the summation of zj over the W marked chips, is an integer value between 0 and W. Thus, we can write:

p y(u) | b0 =0

S W 1 1 Pe = p(Z = i|b0 = 0) + p(Z = i|b0 = 1) 2 2 i=S

l= α

(6)

where S, respectively S, represent the upper integer part of S, respectively its lower integer part. We can calculate Pe0 and Pe1 terms by considering all possible interference patterns α defined as: α = (α1 , α2 , . . . , αW )

(7)

where αj is the number of interference on the jth marked chip. Let us denote l the total number of interferences that occurred on the pulsed mark chips, l = W j=1 αj . With N different nodes, l can take values from 0 to N − 1. Pe0 can thus be expressed as: W N−1

i=S l=0 W αj =l j=1

p Z = i| b0 =0 .p(l, α ) l= α

W l (N

(N − 1)! − 1 − l)! W j=1 (αj )!

l W2

N−1−l W2

2F

2F

1−

l= α

ability that there are exactly i values among the W pulsed mark chips before thresholding greater or equal than sc and the (W − i) others are lower than sc , knowing the interference pattern α . Knowing α , for b0 = 0, the amplitude of the W marked chips can be written as: αj

l= α

Hm Ptm + nj

(10)

m=1

l= α

all possible cases

i p y(u) | b0 =0 ≥ sc l= α

u=1

×

W u=i+1

Pe1 =

S N−1

N−1

i=0 l=0 W αj =l j=1

p Z = i| b0 =1 .p(l, α ) l= α

(14)

The difference is in the yj term, where the desired node contribution dj is present: yj | b0 =1 = dj + Aj + nj l= α

= H0 Pt0 +

αj

Hm Ptm + nj

(15)

m=1

p Z = i| b0 =1 = l= α

(11) p y(u) | b0 =0 < sc l= α

all possible cases

i p y(u)| b0 =1 ≥ sc l= α

u=1

×

W u=i+1

p y(u) | b0 =1 < sc l= α

(16)

and finally,

p y(u) | b0 =1 ≥ sc = p A(u) + H0 Pt0 + nj ≥ sc l= α

sc − A(u) + H0 Pt0 1 = erfc √ 2 σ 2

(17)

1 A(u) + H0 Pt0 − sc = erfc √ 2 σ 2

(18)

p y(u) | b0 =1 < sc = p A(u) + H0 Pt0 + nj < sc l= α

where Hm are optical gain values of the interfering nodes. So, we can express: p Z = i| b0 =0 =

(13)

Then,

(9) The terms p Z = i| b0 =0 are obtained considering the prob-

yj | b0 =0 = Aj + nj =

(12)

So, with (8), (9), (11), (12) and (13), the term Pe0 is entirely defined. The same reasoning can be done for Pe1 :

(8)

where p(l, α ) is the probability to have l active interfering nodes with the interference pattern α and is obtained as follows [26]: p(l, α ) =

A(u) − sc 1 = erfc √ 2 σ 2

i=0

1 1 = Pe0 + Pe1 2 2

Pe0 =

sc − A(u) 1 √ = erfc 2 σ 2

< sc = p A(u) + nj < sc

So Pe1 is entirely defined by (9), (14), (16), (17), and (18). Finally, one can obtain the theoretical error probability Pe for a given WBAN configuration with N nodes considering fixed node positions and orientations and fixed patient position in the room. Pe is entirely determined thanks to (6), (8) and (14). In order to simplify the following study, all the interfering nodes in the BAN are supposed to have the same transmission


Fig. 9. Optimal values of the HL threshold.

Fig. 8. Analytical mobile WBAN error probability validation.

power Pint . The transmission power of the desired node will be noted as Pt . In addition, we have fixed S to W in the following since it corresponds to the optimal threshold considering that the decision variable Z is an integer. The determination of Pe can be performed for any WBAN configuration as described in Section II, i.e. considering random emitting node positions and orientations and random patient locations. Then, the distribution of the error probability Pe can be deduced for the investigated WBAN scenario. V. P ERFORMANCE A NALYSIS A. Validation We express the performance in terms of blocking probability Pb , i.e., the probability of having a Pe higher than a targeted error probability P0 . Pb = p(Pe > P0 )

(19)

Indeed, the large variations of the optical gain distribution, as shown in Fig. 6, induce large Pe distribution. Thus, evaluating the system performance by taking the mean value of Pe distribution is not a good metric, whereas the blocking probability better reflects Pe variations. In all this section, the studied environment will be the room of dimensions (7 m × 5 m × 2.5 m) with obstacles as shown in Fig. 4. The validation of the theoretical error probability calculation is done by comparing the variations of Pb as a function of P0 obtained by the theoretical process described previously and by numerical simulations. Results reported in Fig. 8, are obtained for an OOC of length F = 43 and a weight W = 3. The total number of nodes is N = 3 having the same transmission power Pt = Pint = 5 mW. We assume a classical noise power spectral density value of N0 = 6.4.10−23 W/Hz [23] and the results are plotted for a given value of the limiter threshold sc : sc =

Hmean.Pt 2

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(20)

where Hmean is the mean value of the optical gain of the link between the targeted transmitting node and the receiver. This non-optimal value permits obtaining simulation results with moderate calculation time with the chosen system parameters. We can verify in Fig. 8 that the theoretical curve and the simulated one are close. This permits the validation of the analytical error probability development. B. Optimal Threshold Determination Using the analytical process previously presented, the optimal threshold sc can be determined for any OOC length F and weight W values and any number of nodes N. The determination of these values of sc , normalized with Hmean.Pt , is presented in Fig. 9 for several OOC. We can first observe that the value of the optimal threshold does not depend on the length of the code. However, this value is varying with the number of nodes in the network and with the weight of the code. On top of that, it can be noticed that if the number of nodes in the network is higher than the weight of the code, the value of sc is constant and does not vary anymore with W and F. Thus, the value presented in Fig. 9 will be used in the following, assuming that the hard limiter knows the mean value of the optical gain Hmean of the link between the targeted transmitting node and the receiver. C. Analysis in Terms of Power For medical BAN, the QoS is generally a strong issue because of the transmission of vital information [2]. Even in unfavorable conditions, the QoS layer has to ensure critical services. QoS usually depends on several parameters linked to the service and that must satisfy compromise as the packet loss rate, latency and power consumption. Here, to discuss the results we assume a given QoS defined by a maximal link blocking probability Pb of 10−3 . We first investigate the impact on the performance of desired node emitting power per chip pulse Pt , regarding the interfering nodes one Pint . We have plotted in Fig. 10 the analytical error probability Pe corresponding to Pb = 10−3 for different Pt /Pint ratios (20% and 150%) as a function of Pt . The results are presented for

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Fig. 10. Error probability for mobile WBAN with N = 5 nodes.

Fig. 11. Error probability for mobile WBAN for different OOCs.

three different OOC lengths: F = 43, F = 121 and F = 7200, considering a weight W = 3 and with N = 5 emitting nodes. Assuming a maximal chip time Tc of 70 ns allowing no ISI effect as presented in Section III, these values of F correspond to maximal data rates respectively equal to 332 kbps, 118 kbps, and 2 kbps. The number of nodes used here is N = 5. It can be first noticed in Fig. 10 that, as expected, the error probability decreases as the power Pt increases. In addition, it is interesting to remark that whatever the transmission power Pt is, the Pt /Pint ratio has no impact on the performance. This is linked to the use of HL device in front of the receiver which limits the interfering power. Furthermore, for each code length F, respectively 43, 121 and 7200, if Pt is higher than a minimal transmission power Ptmin, respectively 57 mW, 70 mW and 100 mW, Pe reaches a floor value linked only to the MAI effect, respectively 10−4 , 10−5 and 10−10 . These error probability floors correspond to the values obtained in classical noiseless OCDMA link using a HL before conventional correlation [26]. We can note that Ptmin value is increasing, whereas Pe floor is decreasing with F. This can be explained regarding the probability p that two different nodes interfere [26]: p=

W2 2F

(21)

As F is increasing, p decreases, and thus the Pe floor value decreases. These results illustrate the tradeoffs between data rate, Pe , and Pt . For example in Fig. 10, a Ptmin value of 70 mW is needed to satisfy 5 nodes WBAN with a maximal data rate of 118 kbps and Pe of 10−5 . However, the Pe requirements for medical WBAN are generally much lower and around 10−10 [2]. A classical way to improve the performance is by considering Forward Error Correction (FEC) schemes. For example, it has been shown that using a low density parity check (LDPC) codes of rate 0.8 can significantly reduce the BER in an OCDMA transmission [29]. Thus, with the OOC(121,3) and for the same Ptmin value of 70 mW, using such LDPC code induces a slightly lower data rate (94 kbps) but permits highly decreasing the Pe floor value to 10−10 .

Moreover, it can be noticed, that the values of Ptmin show a significant margin for flexibility regarding the maximal authorized values which is 300 mW for a wavelength of 875 nm [27]. However, these values of Ptmin are still high regarding the impact on the lifetime of the system and the requested data rates. Moreover, they have to be compared to the maximal transmission power authorized if UWB techniques are used, as to know 0.11 mW [30]. This significant difference shows that it is best to consider WBAN based on OWC as a complement or alternative to RF techniques in specific cases. For example if the environment is sensitive to RF interference issues, such as a hospital, or if the maximal authorized power for RF solutions is not enough to ensure the transmissions, or if the security of information is at stake and transmissions need to be confined in a specified indoor environment. D. Analysis in Terms of Node Number In order to assess the OOC parameter impact on the performance which depends on the number of nodes in the network, we have plotted in Fig. 11 the variations of the error probability Pe for the given blocking probability Pb of 10−3 , as a function of the number of WBAN nodes N for different couples (F, W). For each couple (F, W) and value of N, the corresponding value of Ptmin has been determined by simulation. The weight W takes two values (3 and 4) and the code length F is varying between 43 and 359 which correspond to data rates from 40 kbps to 332 kbps. These results show that, as expected for an OCDMA system using OOC, increasing F or W improves the performance. For N > W, MAI effect is preponderant and the performance tends to the theoretical bound of HL receiver [26], because of the power value we have fixed. On the other side, for N ≤ W it can be noticed that low error probabilities can be achieved even considering short length codes. For example, with F = 43 and W = 3, it is possible to have a 3 node WBAN satisfying the Pe requirements for medical WBAN as we obtain an error probability of 10−11. This (F, W) couple with N = 3 corresponds to Ptmin = 57 mW and to a data rate of 332 kbps. Note that such scenario corresponds to a typical health monitoring application as shown


TABLE I T YPICAL H EALTH M ONITORING N ETWORK

on Table I [2], so we can conclude that the WBAN needs are largely achieved in this case. For a higher number of nodes, in order to meet the Pe requirements, we can see in Fig. 11 that W has to be increased. If we consider a WBAN with N = 4 for example, we can obtain with W = 4 an error probability lower than 10−12 with F = 121 i.e., a data rate of 118 kbps. However, by increasing W, the transmitted power per bit is also increased and so the lifetime of the system is reduced. Another solution would be to increase the code length while keeping the weight value to W = 3. In Fig. 11, we can see in this case that the error probability is around 2.10−7 with F = 359 corresponding to a data rate of 40 kbps. To attempt the required Pe , tradeoffs have thus to be realized. Another solution to satisfy error probability needs can be performing MAI mitigation by using FEC as suggested previously or cancellation receivers, but at the cost of complexity increase. Finally, it is possible to modify also the blocking probability Pb of 10−3 . Increasing the maximal value of Pb would lead to lower values of Ptmin, and higher values of data rates. However, it would impact the upper layer and retransmission mechanisms and so the tradeoffs with latency and energy consumption have to be discussed. These results have been obtained for all nodes emitting with the same power that constitutes a worst case. For any other case, one can use our analytical expression to assess the theoretical performance of OWC technology for mobile WBAN. VI. C ONCLUSION We have investigated in this paper the use of on-body OWC in order to develop medical mobile WBAN. Optical wireless links based on diffuse reflections over indoor environment, known to be robust to shadowing effects, have been studied to perform communications between the medical WBAN nodes and the coordinator one. We have defined a scenario where a patient equipped with the WBAN nodes on his body, is moving within a room. The diffuse optical channel has been modeled based on a ray-launching method which allows accounting for room elements such as obstacles and considering the distribution of node locations and orientations and patient positions in the environment. For such a channel, we have analyzed the theoretical performance of an OCDMA multiple access scheme using OOCs and HL receiver. A theoretical expression of the mobile WBAN error probability has been established and validated by simulation. It permits evaluating the optical wireless link blocking probability considering WBAN mobility. Regarding the probability to satisfy a BER of 10−10 as a QoS criterion, we have shown that typical health monitoring application requirements for a three nodes BAN considering data rates lower than

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100Kbps can be theoretically achieved using OWC. The results permit considering a new possible application of OWC technology which can be an alternative or a complement for conventional radio-based WBAN. Such OWC-based solutions are only suitable for indoor systems because of diffuse propagation, especially in very sensitive environment where RF exposures of patients and medical staff, or where RF interferences are strong issues. Several fields of interest still have to be investigated, such as the tradeoff between performance, data rate and complexity. In particular, it is important to determine the consumption power of the OCDMA scheme studied here, regarding the minimal transmission power needed to ensure a satisfying QoS, and so optimizing the system lifetime which is of main concern for WBAN. Finally, practical experiments have to be performed to confirm the OWC potentialities for WBAN we have theoretically shown in this study. R EFERENCES [1] A. Milenkovic, C. Otto, and E. Jovanov, “Wireless sensor networks for personal health monitoring: Issues and an implementation,” Comput. Commun., vol. 29, no. 13/14, pp. 2521–2533, Aug. 2006. [2] S. Movassaghi, A. Abolhasan, M. Lipman, J. Smith, and A. Jamalipour, “Wireless body area networks: A survey,” IEEE Commun. Surveys Tuts., vol. 16, no. 3, pp. 1658–1686, 3rd Quart. 2014, doi: 10.1109/SURV.2013. 121313.00064. [3] B. Latré, B. Braem, I. Moerman, C. Blondia, and P. Demeester, “A survey on wireless body area networks,” Wireless Netw., vol. 17, no. 1, pp. 1–18, Jan. 2011. [4] Standard for Local and Metropolitan Area Networks—Part 15.6: Wireless Body Area Networks, IEEE Std.802.15.6 2012. [5] K. Takizawa, T. Aoyagi, and R. Kohno, “Channel modeling and performance evaluation of UWB-based wireless body area networks,” in Proc. IEEE ICC, Jun. 2009, pp. 1–5. [6] M. Hämäläinen, A. Taparugssanagorn, J. Iinatti, “On the WBAN channel modeling for medical applications,” in Proc. EUCAP, 2011, pp. 2967–2971. [7] M. Cheffena, “Time-varying on-body wireless channel model during walking,”EURASIP J. Wireless Commun. Netw., vol. 2014, pp. 1– 11 2014. [8] M. Periyasami, “Electromagnetique interference on critical medical equipments by RF devices,” in Proc. Int. Conf. Commun. Signal Process., Apr. 3–5, 2013, pp. 78–82. [9] V. S. Benson et al., “Mobile phone use and risk of brain neoplasms and other cancers: Prospective study,” Int. J. Epidemiology, vol. 42, no. 3, pp. 792–802, 2013. [10] J. B. Carruthers, “Wiley Encyclopedia of telecommunications,” in Wireless Infrared Communications. New York, NY, USA: Wiley, 2003. [11] K. Borah, A. C. Boucouvalas, C. C. Davis, S. Hranilovic, and K. Yiannopoulos, “A review of communication-oriented optical wireless systems,” EURASIP J. Wireless Commun. Netw., vol. 2012, pp. 91-1–91-28, Mar. 2012. [12] H. Elgala, R. Mesleh, and H. Haas, “Indoor optical wireless communication: potential and state-of-the-art,” IEEE Commun. Mag., vol. 49, no. 9, pp. 56–62, Sep. 2011. [13] S. Arnon, et al., Advanced Optical Wireless Communication Systems. Cambridge, U.K.: Cambridge Univ. Press, 2012. [14] Z. Ghassemloy, W. Popoola, and S. Rajbhandari, Optical Wireless Communications, System and Channel Modeling With MATLAB. Boca Raton, FL, USA: CRC Press, pp. 11–18, 2013. [15] J. Fadlullah and M. Kavehrad, “Indoor high-bandwidth optical wireless links for sensor networks,” J. Lightw. Technol., vol. 28, no. 21, pp. 3086–3094, Nov. 1, 2010. [16] M. Paksuniemi, et al., “Wireless sensor and data transmission needs and technologies for patient monitoring in the operating room and intensive care unit,” in Proc. 27th Annu. Int. Conf. Eng. Med. Biol. Soc., 2005, pp. 5182–5185. [17] S. S. Torkestani, S. Sahuguede, A. Julien-Vergonjanne, and J. P. Cances, “Indoor optical wireless system dedicated to healthcare application in a hospital,” IET Commun., vol. 6, no. 5, pp. 541–547, Mar. 27, 2012.

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[18] S. S. Torkestani, et al., “Performance and transmission power bound analysis for optical wireless based mobile healthcare applications,” in Proc. 22nd Int. Symp. PIMRC, 2011, pp. 2198–2202. [19] A. M. Khalid, G. Cossu, and E. Ciaramella, “Diffuse IR-optical wireless system demonstration for mobile patient monitoring in hospitals,” in Proc. 15th ICTON, Jun. 23–27, 2013, pp. 1–4. [20] W. Noonpakdee, “Adaptive wireless optical transmission scheme for health monitoring system,” in Proc. IEEE 3rd ICCE-Berlin, Sep. 9–11, 2013, pp. 161–164. [21] L. Chevalier, S. Sahuguede, A. Julien-Vergonjanne, P. Combeau, and L. Aveneau, “Investigation of wireless optical technology for communication between on-body nodes,” in Proc. 2nd IWOW, Oct. 21, 2013, pp. 79–83. [22] A. Behlouli, P. Combeau, L. Aveneau, S. Sahuguède, and A. Julien-Vergonjanne, “Efficient simulation of optical wireless channel, Application to WBANs with MISO link,” Procedia Comput. Sci., vol. 40, pp. 190–197, 2014. [23] J. M. Kahn and J. R. Barry, “Wireless infrared communications,” Proc. IEEE, vol. 85, no. 2 pp. 265–298, Feb. 2007. [24] B. M. Ghaffari, M. D. Matinfar, and J. A. Salehi, “Wireless optical CDMA LAN: digital implementation analysis,” IEEE J. Sel. Areas Commun., vol. 27, no. 9, pp. 1676–1686, Dec. 2009. [25] F. R. K. Chung, J. A. Salehi, and V. K. Wei, “Optical orthogonal codes: Design, analysis, and applications,” IEEE Trans. Inf. Theory, vol. 35, no. 3, pp. 595–604, May 1989. [26] S. Zahedi and J. A. Salehi, “Analytical comparison of various fiberoptic CDMA receiver structures,” J. Lightw. Technol., vol. 18, no. 12, pp. 1718–1727, Dec. 2000. [27] IEC 60825-1, Safety of Laser Products—Part 1: Equipment Classification, Requirements, and User’s Guide, 1.2 ed. IEC, Geneva, Switzerland, 2001. [28] M. Patel and J. Wang, “Applications, challenges, and prospective in emerging body area networking technologies,” IEEE Wireless Commun., vol. 17, no. 1, pp. 80–88, Feb. 2010. [29] S. Sahuguède, A. Julien-Vergonjanne, and J. P. Cances, “Performance of OCDMA system with FEC based on interference statistical distribution analysis,” Eur. Trans. Telecomm., vol. 21, no. 3, pp. 276–287, 2010. [30] “First report and order regarding UWB transmission,” Fed. Commun. Comm., Washington, DC, USA, Tech. Rep. ET docket 98-153, Feb. 2002.

Ludovic Chevalier received the M.Eng. degree from the Ecole Nationale Supérieure d’Ingénieurs de Limoges (ENSIL) in France, in 2012. He is currently pursuing the Ph.D. degree at the XLIM Laboratory, University of Limoges where he is working on optical wireless communications applied to medical body area networks.

Stephanie Sahuguede (S’07–M’09) received the M.Sc. and M.Eng. degrees from the “Ecole Nationale Supérieure d’Ingénieurs de Limoges” (ENSIL) Limoges University, France, in 2006, and the Ph.D. degree in high frequencies and optical telecommunications from Limoges University in 2009. Currently, she is as an Associate Professor at ENSIL. Her research activities include error correction codes, optical CDMA, wireless optical communications and communication systems for e-Health.

Anne Julien-Vergonjanne (M’05) received the Ph.D. degree in microwave and optical communications from Limoges University, in 1987, and the “Habilitation àDiriger des Recherches” (HDR) from Limoges University, in 2006. She is currently a full Professor at the National School of Engineers of Limoges (ENSIL) specialty in Electronics & Telecommunications and develops research activities in the XLIM laboratory, mixed structure between the University of Limoges and CNRS (UMR 7252). Her research activities are in the fields of digital signal processing applied to optical communication systems and networks and communication systems for e-Health. She is a member of IEEE Communication Society.