NFMIC Cooperative Communication Methods for ... - Semantic Scholar

JOURNAL OF NETWORKS, VOL. 7, NO. 9, SEPTEMBER 2012

1431

NFMIC Cooperative Communication Methods for Body Area Networks Mehrnoush Masihpour, Mehran Abolhasan and Daniel Franklin University of Technology Sydney Sydney, Australia [email protected]; [email protected]; [email protected]

Abstract—To achieve higher data rate or to extend the coverage range of a wireless communication system, cooperative relay has been seen as a promising solution. This concept has been integrated in many traditional wireless communication networks. However, it has not been extensively examined for near field magnetic induction communication (NFMIC) systems. This paper aims to apply cooperative relay to NFMIC in a sense that is applicable to body area networking, since NFMIC is stated to be a suitable physical layer for body area networks. We have shown that using idle NFMIC nodes as relaying terminals, the system performance will be enhanced, as compared to a point to point communication system. In this context we have proposed three relaying methods to enhance the data rate and the received signal power in a personal area network. The relaying strategies are denoted as MI-Relay, MAMI Relay1 and MAMI Relay2. In this paper, using theoretical studies and simulation results, we have compared the performance of the three strategies and we have shown that higher data rates can be achieved through MAMI Relay1. However, we have discussed that the separation distance between relaying nodes and the source or destination can be a key factor for relay node selection. Index Terms—NFMIC; propagation model; relay; cooperative communication; MI-Relay; magneto inductive waveguide; AM channel model

I. I NTRODUCTION Body Area Network (BAN) has recently been gaining interest of the scholars in the field of wireless communications [1]–[10]. BAN was formally approved by the IEEE 802 executive committee in November 2006 [1]. BAN refers to the communication between the nodes carrying be a person around or inside the body. BAN is a low power and short range communication technique, which needs to be highly reliable to provide connectivity within about 2 m around a human body [1], [3], [7], [11]. However, in some cases it might be required to be extended up to 5 m. BANs can be divided into two main categories know as wearable (on body) and implant (in body). Wearable BAN refers to a network of devices in the close proximity of human body, while implant BANs consist of embedded devices inside a person’s body. Embedded medical devices such as pace makers, hearing aids, endoscopy capsules and embedded blood pressure or glucose sensors are some examples of the BANs implant devices. A patient may carry more than one implant device. By contrast, wearable BANs have applications in entertainment industry, military as well as in hospitals for monitoring a patient’s condition. Moreover, BANs can be used for automatic treatment, auto dosing and diagnosing and also to improve

© 2012 ACADEMY PUBLISHER doi:10.4304/jnw.7.9.1431-1440

the management efficiency in hospitals. It also can be used to help people with disabilities such as object detection and route guidance for people with vision difficulties or aged population and assisting speech impaired persons and many more [1], [3], [6]. Since BANs are required to carry signals around the human body, their power consumption has to be less than a defined threshold to protect the human tissues [1]. Exposure to high levels of power, results in heating up the body tissues which can influence the human health. Therefore according to IEEE 802.15 standard, the power consumption of BAN needs to be extremely low and also compatible with body energy scavenging operation [1]. Low power emission level also leads to less interference with the other existing communication systems and results in higher reliability. A BAN also is required to have low implementation and maintenance costs, while provide simplicity and high security. The size of the BAN device is also another issue since they need to be carried, hence they must be light and compact [1], [3]. Different short range communication technologies have been proposed for BANs, which among those ZigBee, Bluetooth and Ultra Wide Band (UWB) are the techniques that have been used widely [1], [3], [9]. These technologies have some advantages and disadvantages. ZigBee and Bluetooth both operate at the 2.4GHz frequency band. However, while Bluetooth offers data rate up to 1 Mbps, ZigBee data rate is very limited and is around 250 kbps. Since these two technologies operate at the busy 2.4 GHz frequency band, they face critical interference issues. 2.4 GHz is also used by WiFi, microwave ovens and by other applications. Bluetooth has the highest emission power and power consumption among the three above mentioned techniques [1]–[3], [9]. The limitation in the number of the simultaneous operating piconets (equal to 7) is another drawback of Bluetooth. UWB has the smallest emission power and power consumption among the three and has a nominal data rate of 850 kbps (can be increased to 26 Mbps). Although UWB is advantageous over Bluetooth and ZigBee in terms of data rate and power consumption its negative aspect is high transmission losses by human body [1]. Thus, it makes it difficult to be used for embedded devices. UWB is capable of operating in 3.1 GHz up to 10.6 GHz. Although the higher the frequency, the higher achievable data, but it also results in higher transmission losses [1]. Recently, a new physical layer technology has emerged known as Near Field Magnetic Induction Communication (NFMIC), which has been seen as an emerging physical

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layer for the applications where communication occurs inside or in close proximity of human body, underground such as tunnels, as well as underwater [12]–[22]. NFMIC uses near field magnetic flux for data transmission rather than radiating electromagnetic (EM) waves [11]. RF (Radio Frequency) based transmission systems radiate the EM waves, which is capable of travelling through the communication channel (communication channel is often air) far from the source. Unlike transmitted EM waves, which does not come back to the source when transmitted (radiative transmission), MI (magnetic induction) waves can come back to the source due to the mutual coupling (reactive transmission); since the communication link is established through magnetic coupling between two inductive coils (Figure 1). Although electromagnetic waves are suitable for long range communications, they may fail to address the requirements of short range communications. However, unique characteristics of NFMIC make it suitable for short range communication systems, particularly where the communication channel must take into account humidity, soil or body tissues. In such channel conditions, EM waves can be easily absorbed by the channel. In wearable BANs using EM waves, multipath effect caused by the human body is an issue [1], [5], [9]. Therefore, reliability and QoS (Quality of Service) can be degraded. However, the effect of the human body on the MI waves is different. MI waves can easily penetrate the tissue with minimal losses, thus multipath effect and signal absorption due to the human body is not as sever as EM-RF based systems [12]–[14]. The most important factor affecting the magnetic wave is the magnetic permeability of the material within the channel. Therefore, since water, soil and human body tissue have almost the same permeability as air, they have the same effect as air on the transmitted signal [20]–[22]. This characteristic of NFMIC can result in higher reliability and QoS, not only in BAN but also in tunnels and rocky and coastal regions. NFMIC has a number of advantages over RF for short range communication systems. For example, lower transmission power is used to provide communication within a couple of meters [15], [20], [21]. According to [20], NFMIC is about six times more power efficient than the bluetooth enabled type devices. Frequency reuse is also well facilitated. Since each user is assigned a frequency within their communi-

Fig. 1.

Peer to peer MI system model

© 2012 ACADEMY PUBLISHER

cation ‘bubble’ [11], the same frequency can be used for multiple users with minimal chance of interference. Since the transmitted signal loses its power rapidly with distance, even more than RF signals. This characteristic of the NFMIC results in a well sealed communication bubble. In other words, it is very difficult to be intercepted by unauthorised party or to interfere with some one else’s communication bubble. Moreover, NFMIC does not need to struggle with fading due to multipath, because of the rapid power decay with distance [20]. Although the high path loss (due to the higher rate of power degradation with distance) offers some benefits, it makes the communication distance very short (centimetre range) hence difficult to be used for the application where longer range is required. It also results in lower capacity. In RF communication systems to either improve the communication range or the system capacity and data rate, cooperative relaying has been used [23]–[26]. Cooperative relaying has been considered in the RF-based networks such as WiMAX and LTE to enhance the data rate, capacity and to lessen the complexity of the base stations serving the user devices. Different relaying modes are applicable to such systems. For instance in-band and out-of-band relaying modes [24], [26] or transparent and non transparent relaying are used to improve the network performance of a cellular system [24], [26]. However, from a signal processing perspective, there are three different relaying schemes to be used in RF communications, which are Amplify and Forwarding, Decode and Forwarding and Estimation and Forwarding [25]. Based on the schemes the relaying node may amplify or decode the receiving signal and resend it to the receiver. It may also decide on the required process to be applied to the signal based on the estimation of the channel. However, the concept of cooperative communication has not been widely explored for NFMIC systems. In this paper we have studied cooperative communication for NFMIC-enabled BAN nodes. The contribution of this paper is as follows: • Using idle nodes for cooperative communication to enhance the received signal power and data rate, as compared to a single hop point-to-point communication. • Proposition of three relaying strategies for NFMIC BAN denoted as MI Relay, MAMI Relay1 and MAMI Relay2. • Proposing a propagation model in a multi node BAN, equipped with the NFMIC enabled devices. • Analysing the effect of cooperative relaying nodes geometry and different relaying strategies on the system performance. II. BACKGROUND Magneto-inductive waveguides has recently been proposed [20]–[22], [27], [28] as a method of extending the range of MI communications systems (see Figure 2). The system consists of n relay nodes between transmitter and receiver. All nodes have been placed in a linear manner. Each relaying node relays the transmitted data from its nearest neighbour to the next relay until it reaches the final receiver. All the receiving nodes are passively powered. Sun and Akyildiz have studied magneto inductive waveguide for underground communications [20]–[22] such as in


pipe lines or tunnels. In [20], [21], they have discussed that when EM-RF communication occurs underground, it faces three major problems; high path loss, dynamic channel condition and large antenna size. They claim that by using NFMIC technique the problems with dynamic channel condition, which results in high error rate, can be mitigated. The antenna size is also addressed by using small coils of small radius for data transmission. They proposed a pathloss model for a peer to peer NFMIC. They also extend the work to model the path loss for a multi-node magneto inductive waveguide based on their peer to peer pathloss model. They claim that applying magneto inductive technique to underground communications can highly improve system performance. They have examined the model at frequencies 300 MHz and 900 MHz where communication medium is soil containing different levels of water content [20], [21]. In their papers, Sun and Akyildiz have compared conventional EM systems with existing point to point MI and the MI waveguide. They have shown that the improved MI waveguide results in significant improvement in terms of capacity and communication range [20], [21]. They suggest that in such environments, MI has a constant channel condition while in EM the pathloss may rapidly change by changing the water content in the soil. This is because in MI the path loss depends on the magnetic permeability of the channel which is the same for air, soil and water, while path loss in EM depends on the permittivity of the channel [20], [21]. They also have shown that although increasing the operating frequency results in EM path loss to increase, it leads to lower MI path loss. In [22], they propose two deployment algorithms for WUSNs (Wireless Underground Sensor Networks). The authors investigate the deployment of magneto inductive waveguide to connect WUSN nodes. They have proposed two deployment algorithms denoted as MST (Minimum Spanning Tree) and TC (Triangle Centroid). While MST uses minimum

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spanning tree to connect all nodes, TC is based on Voronoi diagram and it divides the whole network into non overlapping triangle cells [22]. They discuss that TC algorithm has a better performance in terms of robustness to the network failure since it is k-connected (k > 3), while MST is only 1-connceted [22]. In other words, in case of a node failure in MST the whole network may lose the connectivity while in TC even when k-1 node fails to operate, there is still connectivity in the whole network. Although their contribution is well suited for underground communications, it is not applicable in BAN. The conventional linear magneto waveguide model can not be directly applied to a BAN where all nodes are distributed randomly in space around or inside a human body. However, our approach is slightly different and we investigate NFMIC for a BAN. In this paper we propose a propagation model for a BAN using MI devices in different deployment scenario. Also we discuss the relay selection strategies in such scenarios. In our previous work [27]–[31], we have proposed a channel model for a peer to peer NFMIC in. In [30], we have shown how ferrite cored-coils can be used to enhance the communication range of an NFMIC system. In [28], we have studied the conventional waveguide channel model and we discussed that the waveguide model might work inversely after a specific point (waveguide distance threshold). In other words, by increasing the relaying nodes, the total communication range will be decreased due to the power reflection within the system. In [27], we investigated the voltage excitation methods for a waveguide system and we have proposed three methods of excitation known as AEE (Array Edge Excitation) and ACE (Array Centre Excitation) and CAE (Collinear Array Excitation). In [27], we have shown that ACE can provide longer communication range than the other two methods. However, Syms, Solymar and Shamonina have studied the waveguide model from a different perspective; they have shown how optimally terminate the waveguide transmission line to minimise the power reflection [18], [19]. They studied the waveguide model to minimise the propagation losses due to reflection that leads to better performance of the magneto inductive waveguide [18]. However, in [19], they have investigated how different geometrical arrangement of the magneto inductive waveguide results in different magneto inductive devices with different properties. Devices such as filters, mirrors, Fabry-Perot resonators, Bragg gratings and tappers have been discussed in their paper [19]. III. OVERVIEW OF A POINT TO POINT NFMIC SYSTEM A. Perfect antenna alignment

Fig. 2.

Magnetic waveguide and circuit model


The block diagram of a peer to peer magnetically inductive communication system and the equivalent circuit model is shown in Figure 1. The transmitter and receiver are two coils centred on a single axis [11]. r is the radius of the coil and x is the separation distance between them. Transmitting antenna coil sends the information to the receiving coil through the mutual inductive coupling. There is no need for an individual source of power at the receiver since transmitting coil induces

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the voltage in the receiving circuit by means of the receiver coil (i.e. receiving nodes are passively powered). As long as they are at each others magnetic field, they can communicate. The relationship for the current flowing to the transmitting circuit and the induced current in the receiving circuit at the angular frequency ω for the receiver (R) and the transmitter (T) is [11]: v 0 + RS ) 1 + j (2QTω+Δω 0

(1)

√ jωk LT LR iT iR = (RLR + RL ) 1 + j (2QRω+Δω 0

(2)

iT =

(RLT

and the received power is [11]: 2

PR =

|iR | RL 2

(3)

The mutual coupling between the coils or coupling coefficient (k) is a function of the transmitting and the receiving coil radii and the distance between them. At a distance d, the coupling coefficient is [11]: k (x) =

r12 r22 3 √ r1 r2 d2 + r12

(4)

B. Relative lateral misalignment In reality achieving a perfect antenna alignment is difficult and this results in some degrees of performance reduction in terms of achievable communication range or data rates. There are two main sources of performance degradation known as angle and lateral misalignment. However, to study any distance dependent differences within our proposed relaying network, we consider that the antennas have perfect angular alignment with respect to each other (it is considered in this work that only lateral displacement exists, and is inevitable in a 3D placement). When there is lateral misalignment Δ (Figure 3), the x and y component of the receiver plane are parallel to the transmitting antenna coil plane. Therefore, they have no contribution in flux cutting through the receiving coil. In fact, the dominating component will be the z-component [32]. According to [32], the power transfer function in this case is, 2 2 4 μ20 ·NT2 ·NR ·rR ·ω 2 ·m2 (rT ·m)−(2−m)Δ PRx ·E RT x = 64.RT x ·RRx ·rT ·Δ3 · Δ · K + 2−2m (9) where K and E are the complete elliptic integrals of the first and second kind respectively, and m is the elliptic modulus and is always a positive value between 0 and 1 [32]. The equivalent equations for this three parameters are shown in the following equations: π/2

(10)

1 − m2 sin2 γ · dγ ; 0 ≤ m ≤ 1

(11)

0

E (m) =

dγ

;0≤m≤1

K (m) =

Where rT and rR are the radius of the transmitting and receiving coil respectively.The transmitter quality factor is a function of the source resistance RS , resistance of the transmitting coil RLT , angular frequency ω and the inductive value of the transmitting coil LT [11]:

1 − m2 sin2 γ

π/2 0

ω0 LT QT = RLT + RS

(5)

Similarly the quality factor of the receiver is [11]: ω0 L R QR = RLR + RL

(6)

m=

4 · rT · Δ 2

(rT + Δ) + d2

;0 ≤ m ≤ 1

To simplify the power transfer function, the Q-factor is substituted in the power equation and therefore it becomes PRx = RT x QT QR k 2 .

In this equation RL is the load resistance, RLR is the resistance of the receiving coil. NT and NR are the number of turns of the transmitting and receiving coils respectively. The efficiency of the transmitting and receiving antenna can be expressed as: ηT =

RS RL ; ηR = RS + RLT RL + RLR

(7)

Therefore, the power at the receiver, as a function of the antenna characteristics, is derived as [11], [29]: PR = PT ηT ηR QT QR k 2 (d)

(8)

As can be seen from Equation 4 and 8, the transmitted signal loses its power with the sixth power of the communication distance. Therefore the impact of the path loss is more critical and severe than the EM RF-communications. This results in degradation of the transmitted signal rapidly with distance.


(12)

Fig. 3.

Lateral Misalignment (adapted from [32])


In this case, the coupling coefficient is expressed as, 2 2 rR Δ 2 lT l R k2 = ΔK + (rT m)−(2−m)Δ E 2 2 2−2m 2 2 3 16π ((rT +Δ) +d ) rT Δ (13) In a personal area network, which a user carries multiple devices, idle devices can be used to assist in communication in order to enhance the received signal power and consequently the system capacity or communication range. In such networks, often a few nodes are at the idle status since it is rare that all the devices would communicate with each other simultaneously. Therefore the idle nodes can be used as cooperative relay terminals to enhance the data rate also the communication distance without the need for increasing the transmission power. Multiple antenna technique also can be used to achieve the same objective, but it increases the size of the device which is not desirable in a BAN, especially for implant devices where the size of the embedded device needs to be very small. Thus, our work aims to use idle nodes as relaying nodes between the transmitter and the final receiver to enhance the total performance of the system in terms of the end-to-end channel data rate. Next section will discuss our proposed cooperative system applicable to BANs consisting of four nodes. IV. NETWORK MODEL A BAN may be seen as one or more cluster of nodes, where all the nodes within a cluster can communicate with each other. However, if a receiver is located at the edge of the communication range of the transmitter, the received signal strength may be very low, and subsequently the data rate. Therefore, to enhance the end to end throughput, one or more idle devices are used to function as relaying nodes. The proposed cooperative relay network consists of: a transmitter (source), a receiver (final destination) and one (in MI Relay method), or two (in MAMI Relay 1 and 2 methods) intermediate nodes, which act as cooperative relay nodes. The source and destination are separated from each other by a distance d. A direct line of sight exist between the transmitter and receiver, but the receiver is assumed to be at the communication range of the transmitter, hence it receives low signal power (in case of point to point communication). However, it is assumed that there are two idle devices between source and sink, which can be utilised to assist the communication by providing an indirect path from the transmitter to the receiver over which information may be relayed. It will be shown that compared to a point to point communication,the system performance can be significantly improved by using the intermediate nodes as relay nodes. The transmitter is separated from the relay 1 and 2 by a distance xT x,R1 (x-component of the distance) and xT x,R2 respectively, and the receiver is located at a distance xR1,Rx and xR2,Rx from relay 1 and 2 respectively. Relay 1 (R1) is assumed to be located closer to the transmitter and R2 is placed closer to the receiver such that any distancedependent differences in performance may easily be evaluated. Both the source and destination have a direct link with relay 1 and 2. To avoid frequency spectrum contention, it is assumed that the network uses Time Division Multiple Access (TDMA)


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for channel allocation for each transmission. However, the transmission system requires precise synchronization, which is beyond the scope of this work. V. NFMIC COOPERATIVE RELAY METHODS FOR BAN - L O S In this section, we propose three relaying models; LoS-MI Relay, MAMI (Master/Assistant Magnetic Induction)-Relay1 and MAMI-Relay2. We assume that the system uses a TDMA (time division multiple access) method to allocate the available channel to each transmitting node. However, it is assumed that all nodes operate in half duplex mode. In other words, each device can either transmit or receive at a specific time slot. This work is based on the physical channel model discussed in Section III, however, we extend the work to apply it to a multiple section cooperative MI network. The following sub sections discuss the three relaying methods and compare the three approaches in terms of final received power and the endto-end throughput. A. LoS-MI Relay Figure 4 illustrates an LoS MI-Relay system. In LoS-MI Relay, the receiver receives the transmitted data through two independent paths: directly from the source and also via a relaying node. This is performed through two steps or two time phases: Phase1: transmitter broadcast the message to all nodes and each node including the final receiver receive the signal. Phase2: selected relay -either relay1 or relay2- send the message to the final receiver, and the target receiver combines the two copies of received signal. Phase1: the transmitter broadcasts the message to all nodes. R1, R2 and Rx, which are at the listen state, receive the transmitted signal. However, the received signal strength is different at each node. Since the final receiver is assumed to be around the edge of communication, the received power at the target receiver may be minimum among all receiving nodes at this stage. Let the gain of transmitting and relaying antenna i (Ri ) be defined as:

Fig. 4.

LoS-MI Relay

GT x = Q T x η T x

(14)

GRi = QRi ηRi

(15)

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Similarly the gain of receiver is defined as: GRx = QRx ηRx

(16)

Where QRx and ηRx are the quality factor and efficiency of final receiver. The received signal power at each relaying node is estimated using Equation 17 and 18: Tx = PT x GT x GR1 kT2 x,R1 PR1

(17)

Tx PR2 = PT x GT x GR2 kT2 x,R2

(18)

and the received signal power at the final receiver at this stage is: Tx PRx = PT x GT x GRx kT2 x,Rx (19) The coupling coefficient is estimated using Equation 20, where i denotes the transmitting node index and j denotes the receiving node: 2 ki,j = Si,j · Wi,j (20) where: Si,j =

rj2 · Δ2i,j · li · lj

2

16.π 2 · (ri + Δi,j ) + x2i,j

Wi,j = Δi,j

2

(21) · ri · Δ3i,j

(ri · mi,j ) − (2 − mi,j ) Δi,j ·K + ·E 2 − 2mi,j

In this case mi,j receiving node j):

2

(22) is (for the given transmitting node i and

mi,j =

4 · ri · Δi,j

2

(ri + Δij ) + x2i,j

(23)

where 0 ≤ mi,j ≤ 1, and Δi,j is the lateral misalignment between node i and j (Figure 3) and xi,j is the separation distance between node i and j on the x-axis. Phase2: transmitter goes to idle state and Rx is still in the listen mode. However, selected relay (R1 or R2) transmits the received signal -received at phase 1- to the receiver. At this stage, the power received by the destination through relay i is: Ri Tx 2 = PRi GRx GRi kRi,Rx (24) PRx Tx where PRi = PT x GT x GRi kT2 x,Ri . It further simplifies to: Ri 2 PRx = Gt G2Ri kT2 x,Ri kRi,Rx

capacity theorem (Equation 27), the channel capacity at the receiver for MI Relay method is (when the relay is performed through relay i): Ri CRx

= Bf f0 log2

; Bf =

B f0

(27)

2 2 2 2 + − Q + Q Qi + Q2j + 4Q2i Q2j i j B √ Bf = = f0 2Qi Qj (28) In the NFMIC relay network noise analysis, it is assumed that the noise affecting the system is primarily thermal noise. It is because, whereas RF communications where the principle source of noise is the interference from other spectrum users, in short-range NFMIC this problem is not as critical. Thus, thermal noise is considered in this work, and its power is calculated using the Johnson noise equation: NP ower = kT B; (W att)

(29) −23

In this equation, k is Boltzmann’s constant (1.38 × 10 ) and B is the communication bandwidth. The system is assumed to be operating on a person’s body, therefore, the temperature will be around 37◦C (310◦K). B. LoS-MAMI Relay1 In LoS-MAMI Relay1, both intermediate nodes are used to improve the system performance even more than LoSMI Relay. LoS-MAMI Relay1 is based on a Master/assistant model. In this method, one of the idle devices is selected to act as a relay master, and another node as a relay assistant. In fact, relay assistant is used to relay the data from transmitter to the relay master, hence, the received signal quality at the relay master is boosted. Hence, it provides a higher received signal power at the final receiver. In this method, the relay assistant can relay the data from the transmitter to the final destination

where Gt = GRx GT x . Finally, receiver combines the received signals, received from the two paths. Therefore, based on the selected relaying node (i = 1 or 2), the final received signal power can be estimated using the following equations:


As can be seen from Equation 27, higher received signal power for a given noise level results in a higher channel capacity. In this equation Bf is the 3dB-fractional bandwidth, f0 is the operating frequency and N shows the system noise. The 3dB-fractional bandwidth can be estimated if the quality factor of the antennas are known [39]:

(25)

Ri Tx Ri PRx total = PRx + PRx ; 2 = PT x GT x GRx kT2 x,Rx + PT x GT x G2Ri GRx kT2 x,Ri kRi,Rx t 2 2 2 2 G kT x,Rx (xT x,Rx ) + GRi kT x,Ri kRi,Rx ] (26) The signal power seen by the receiver can be used to determine the channel capacity. According to the Shannon-Hartley

P Ri 1 + Rx−total N

Fig. 5.

LoS- MAMI Relay1


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as well. However, if the final receiver is out of the range of the final destination, the relay assistant is used only to relay the data from the transmitter to the relay master (LoS-MAMI Relay2). This method will be discussed in Section V-C. Figure 5 shows a LoS-MAMI Relay system, in which the transmitted signal is received by the receiver through three paths. Phase1: the transmitter broadcasts the signal. Rx, R1 and R2 receive the transmitted signal. The power received at each node is shown in the Equations 17, 18 and 19. Phase2: at this stage, the relay assistant send the data to the relay master as well as the target receiver. Power received at relay master at stage2 (S2) is: Ra−S2 Tx 2 Tx PRm = PRa GRa GRm kRa,Rm + PRm

(30)

LoS-MAMI Relay 2 is different from LoS-MAMI Relay1 at stage 2, when the relay assistant transmits the signal. In LoS-MAMI Relay 2, the relay assistant transmits the signal only to the relay master instead of sending it to both the receiver and relay master. This method can be applied when the relay assistant is out of the direct range of the target receiver. However, it may be used when there is a LoS between the final destination and the relay assistant. In this scenario (Figure 6), transmission to Rx is done through three time phases: Phase 1: transmitter broadcasts the signal to all nodes (Rm, Ra, Rx). The power received by each node at this stage is shown in Equations 36 (at the relay assistant), 37 (at the relay master), 19 (at the final receiver):

Tx PRa = PT x GT x GRa kT2 x,Ra (36) Tx where PRa = PT x GRa GT x kT2 x,Ri . It further simplifies to:

Ra−S2 2 PRm = PT x GT x GRa GRa GRm kT2 x,Ra kRa,Rm + kT2 x,Rm ] Tx = PT x GT x GRm kT2 x,Rm (37) PRm (31) However, the power received at the final receiver at this Phase 2: relay assistant send the data to the relay master stage, through the relay assistant is: but not to the receiver. As mentioned previously, this case may Ra−S2 Tx 2 be applied when the relay assistant has no direct line of sight = PRa GRx GRa kRa,Rx PRx (32) with the final receiver. However, Ra may be used to enhance Ra−S2 2 PRx = Gt G2Ra kRa,Rx kT2 x,Ra the transmitted signal to the Rx through the relay master. At Phase 3: the relay master, which has received the signal this stage, the received signal power by Rm via Ra is: from the original transmitter, as well as the relay assistant, Ra Tx 2 = PRa GRa GRm kRa,Rm (38) PRm combines the two received signals and sends it to the final destination. Therefore, the received signal power at the final Since the transmission power of the relay assistant at this receiver at this stage, via Rm is: stage is equal to its total received power by the transmitter Ra−S2 Rm 2 = PRm GRm GRx kRm,Rx PRx

(33)

Finally, the target receiver combines the three copies of the received signal. Hence, the final received signal power at the final receiver is: Ra−S2 Tx Rm = PRx PRx + PRx + t 2 2 2 = G kTx,Rx + GRa kRa,Rx kT2 x,Ra + 2 2 + kT2 x,Rm GRa GRm kT2 x,Ra kRa,Rm GRa GRm kRm,Rx

M AM I1 PRx−total M AM I1 PRx−total

(34) Therefore, the channel capacity for LOS-MAMI Relay1 is estimated as: M AM I1 PRx−total M AM I1 Ctotal (35) = Bf f0 log2 1 + N C. LoS-MAMI Relay2

at stage 2, therefore, the received power by the relay master from the relay assistant can be expressed as: Ra 2 PRm = PT x G2Ra GT x GRm kRa,Rm kT2 x,Ra

(39)

However, the total received power seen by Rm, at stage 2 will be: S2 Tx Ra PRm = PRm + PRm ; S2 PRm = PT x GT x GRm kT2 x,Rm + (40) 2 kT2 x,Ra PT x G2Ra GT x GRm kRa,Rm It can also be shown as: S2 2 = PT x GT x GRm kT2 x,Rm + G2Ra kRa,Rm kT2 x,Ra (41) PRm Phase 3: relay master sends the message to the receiver. Therefore, the received power by the receiver at stage 3, through relay master is: Rm S2 2 = PRm GRx GRm kRm,Rx PRx

(42)

The received power by Rx through the relay master at this stage, is simplified to: 2 Rm 2 2 kT x,Rm + G2Ra kRa,Rm = PT x Gt G2Rm kRm,Rx kT2 x,Ra PRx (43) Finally, at this phase, the final receiver combines the two copies of the received signal via the transmitter and the relay master. Hence, the total received power at the final receiver is: Fig. 6.

LoS- MAMI Relay2


M AM I2 Tx Rm PRx−total = PRx + PRx

(44)

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Tx Rm By substituting the equivalent equations for PRx and PRx (Equation 19 and 42) in above equation, it can be expressed as: M AM I2 2 = Gt kT2 x,Rx + G2Rm P Rx−total kRm,Rx (45) 2 2 2 2 kT x,Rm + GRa kRa,Rm kT x,Ra )

Therefore, the total capacity of the system according to Shannon-Hartley theorem is: M AM I2 PRx−total M AM I2 Ctotal (46) = Bf f0 log2 1 + N VI. SIMULATION Matlab has been used to simulate the propagation model for each of the three proposed multihop methods. In the simulation, the transmission power is defined as 200 uW, which is sufficient power for short range communications systems such as in sensor networks, and BANs. The receiver sensitivity is 10 nW, which leads to 18 cm communication range for the peer to peer line of sight scenario in this study. The antenna coils have radius of 0.5 cm, 0.8 cm length and the number of turns is 10. The operating frequency is set to 13.56 MHz, since this frequency is designated ISM frequencies and also it ensures that the communication is well within the near field region. The wavelength of 13.56 MHz is 22 m, which implies that the near field and farfield boundary is approximately 3.5 m. For a BAN, the required communication range is often less than this amount, hence 13.56 MHz meets the criterion. Since it is common to form magnetic coils with copper wire, it is also assumed in this study that copper wire are used in the antenna coils. The resistance of copper wire per unit of length is R0 = 2.16 (Ω) [20]. According to [20], this results in the self resistance of inductors to be 2πN rR0 (Ω), where r is the coil radius and N is the number of turns. However the load and source resistance values are set to 50 Ω since it is a practical value for voice and data communications over short distances. This leads to the total efficiency of 98%. The system is assumed to be homogenous and all the nodes use identical antennas which results in identical quality factors. The coils quality factor is 830, where a high magnetic permeable material is used for the core of the coils (such as ferrite or manganese zinc). The permeability of the ferrite is 0.0008 H.m−1 . However, the location of each node is chosen in which the transmitter and the target received have no direct link with each other and have no misalignment in respect to each other. Transmitter is located at the reference location Tx (x y z)=(0 0 0). The two relay nodes are located at a distance between transmitter and receiver and have the same lateral misalignment in respect to Rx and Tx. In this analysis, identical lateral misalignment are chosen to measure the performance of the relaying method based on the separation distance only. The effect of lateral and angular misalignment will be considered in the futhure work. R1 is located close to the transmitter R1(2 2 5) and R2 is placed closer to the receiver (close to the communication edge of Tx) R2(5 -2 -5). The location of the receiver is changed from


5 cm (clos to R2) to 18 cm (edge of the communication range of Tx) on the horizontal axis. Therefore, any distancedependente differences can be measured. In the following section, the performance of each LoS relaying techniques will be compared with each other, as well as to a conventional point-to-point communication (when there is no cooperative communication). Since the existing range exttion method for NFMIC (linear wabeguide) is not directly comparable with our proposed cooperative strategies for NFMIC, the performance of the three methods are compared against a direct link pointto-point communication. In fact the aim of this section is to show that by using the proposed cooperative communication techniques as compared to a point-to-point communication, the performance can be improved significantly. It is also shown that the optimum selection of each relay to act as relay master and assistant based on their separation distance can impact the overall performance. The results are shown and discussed in the following section.

A. Result analysis Figure 7 shows the achieved data rates by applying LoS-MI relay technique. As can be seen here, if the node closer to the sink is selected to relay the data, slightly higher data rates can be achieved. However, as shown in Figure 7, when there is cooperative communication, achieved data rate is significantly higher. For example at the edge of communication (at 18 cm), receiver achieves an additional 125 kb/s data rate if data is receives through two different paths (direct and relay path), compared to a point to point communication. Figure 8 and 9 show the achieved data rates against the communication distance for LoS-MAMI Relay1 and 2. The Figures show that, these two methods achieve higher data rates if the relay assistant is chosen to be located closer to the source. It may also be seen here, that applying either of these relaying techniques can improve the achieved data rates considerably. However, in MAMI Relay2, if the relay master and assistant are chosen improperly, the achieved data rates degrade notably (about 25 kb/s at the edge in this scenario). This value is about half for MAMI Relay1 (in case of improper master/assistant relay selection). Figure 10 shows a comparison between the three discussed LoS MI cooperative relaying models. As it can be seen from the graphs, the best method is MAMI-Relay1, where the relay master is chosen to be closer to the receiver (Rm=R2). However, if relay is performed through a relay master closer to the transmitter, losses will be higher. As can be seen from the statistics, MAMI-Relay2, where relay master is closer to the transmitter, achieves almost the same performance improvement as the MI-Relay through the closer node to the transmitter. However, MAMI-Relay2 achieves slightly higher channel capacity. Figure 10 also illustrates that the worst case scenario is MI-Relay relaying through the node closer to the transmitter (R1). Figure 10 also suggest that the MAMI Relay 1 and 2 achieve very similar data rates when Rm=R2, and also the highest among all; while if Rm=R1, MAMI Relay 1 outperforms MAMI Relay2.


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VII. C ONCLUSION

In this paper three NFMIC relaying strategies are proposed for BAN, where a direct line of sight exist between the transmitter and the final receiver. The relaying techniques are denoted as MI-Relay, MAMI-Relay1and MAMI-Relay2. The signal propagation for the mentioned relaying methods are studied, and it is shown by theoretical analysis and simulation that using idle NFMIC devices within a BAN as relay nodes can improve the end-to-end data rate and the received signal strength dramatically. The performance of the proposed relaying techniques is compared against each other and it is concluded that MAMI-Relay1 provides higher data rate and received signal power at the final receiver as compared to the other two methods. It is also discussed that the distance of each relaying node to the transmitter or receiver can be used to determine the optimum relay selection strategy. It is shown that as the distance of the relaying nodes with the transmitter increases, the achieved throughput also increase in MI Relay method. In MAMI Relay1 and , the optimum performance is achieved when the relay master is the node closer to the receiver. However, the performance of MAMI Relay 2 is more sensitive to the selection of the master and assistant node.

Fig. 8.

LOS-MAMI Relay1-achieved data rate

Fig. 9.

LOS-MAMI Relay2-achieved data rate

VIII. RESULT FIGURES

Fig. 7.

LOS-MI Relay-relay


Fig. 10.

RSS and achieved distance comparison between the three methods

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