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8/12/2019 IEEE TVT PoissoSerial Amplify-and-Forward Relay Transmission Systems in Nakagami-mFading Channels With a Po

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 63, NO. 5, JUNE 2014 2183

Serial Amplify-and-Forward Relay Transmission

Systems in Nakagami-m Fading Channels

With a Poisson Interference FieldValentine A. Aalo,Senior Member, IEEE, Kostas P. Peppas,Member, IEEE, George P. Efthymoglou,Member, IEEE,

Mohammed M. Alwakeel, and Sami S. Alwakeel,Member, IEEE

AbstractIn this paper, the end-to-end performance of a wire-less relay transmission system that employs amplify-and-forward(AF) relays and operates in an interference-limited Nakagami-mfading environment is studied. The wireless links from one relaynode to another experience Nakagami-m fading, and the num-ber of interferers per hop is Poisson distributed. The aggregateinterference at each relay node is modeled as a shot-noise processwhose distribution follows an -stable process. For the considered

system, analytical expressions for the moments of the end-to-endsignal-to-interference ratio (SIR), the end-to-end outage probabil-ity (OP), the average bit-error probability (ABEP), and the aver-age channel capacity are obtained. General asymptotic expressionsfor the end-to-end ABEP are also derived. The results provideuseful insights regarding the factors affecting the performance ofthe considered system. Monte Carlo simulation results are furtherprovided to demonstrate the validity of the proposed mathematicalanalysis.

Index TermsAmplify-and-forward (AF), average bit-errorprobability (ABEP), channel capacity, cochannel interference,Foxs H-function, Meijers G-function, multihop relaying, Poissoninterference field.

I. INTRODUCTION

M ULTIHOP relaying has recently received considerableattention in the literature because of its potential toprovide more efficient and broader coverage in microwave and

bent-pipe satellites links, as well as cellular, modern ad hoc,

wireless local area, and hybrid wireless networks [1]. There-

fore, multihop relaying, which is designed for extended cover-

Manuscript received November 13, 2012; revised July 5, 2013 andOctober 12, 2013; accepted October 17, 2013. Date of publicationNovember 14, 2013; date of current version June 12, 2014. This work wassupported by the Sensor Networks and Cellular Systems Research Centerof the University of Tabuk. The review of this paper was coordinated byProf. J. Y. Chouinard.

V. A. Aalo is with the Department of Computer and Electrical Engineeringand Computer Science, Florida Atlantic University, Boca Raton, FL 33431USA , and also with SNCS Research Center, University of Tabuk, Saudi Arabia(e-mail: [email protected]).

K. P. Peppas is with the Institute of Informatics and Telecommunications,National Centre for Scientific Research Demokritos, 15310 Athens, Greece(e-mail: [email protected]).

G. P. Efthymoglou is with the Department of Digital Systems, University ofPiraeus, 18534 Piraeus, Greece (e-mail: [email protected]).

M. M. Alwakeel is with the Sensor Networks and Cellular Systems ResearchCenter, University of Tabuk, Tabuk 71491, Saudi Arabia (e-mail: [email protected]).

S. S. Alwakeel is with the Department of Computer Engineering, King SaudUniversity, Riyadh 11543, Saudi Arabia, and also with the Sensor Networksand Cellular Systems Research Center, University of Tabuk, Tabuk 71491,Saudi Arabia (e-mail: [email protected]).

Digital Object Identifier 10.1109/TVT.2013.2291039

age and throughput enhancement, has been adopted in several

wireless standards [2][4]. In a multihop relaying system,

intermediate idle nodes that are closer to the transmitter than the

destination operate as relays between the source node and the

destination node when the direct link between the source node

and the destination node is deeply faded or highly shadowed.

Various protocols have been proposed to achieve the benefits

of multihop transmission. One of them is the so-called amplify-

and-forward (AF) protocol, in which the received signal is

simply amplified and forwarded to the receiver without per-

forming any decoding [5]. The performance of multihop AF

relaying systems in series has been addressed in many past

works based on the assumption that the system performance

is limited by Gaussian [6], [7] or generic noise [8]. On the other

hand, practical relaying systems generally employ frequency

reuse, which results in cochannel interference. The impact of

cochannel interference on the performance of AF relay systems

in a fading environment has been studied in many recent works,

assuming a fixed number of interfering signals that are Rayleigh

or Nakagami-mdistributed at each relay node and at the desti-nation node. (See [9][18] and references therein for examples.)

However, in a practical wireless environment, the number

of interfering signals at each relay may be a random variable

as well. Moreover, in many wireless networks, the interfer-

ing signals also experience attenuation due to path loss and

shadowing, whereas their location and activity around the

receiving node may vary randomly [19]. Specifically, in the

emerging heterogeneous cellular systems, the positions of many

infrastructure elements are unknowna priori,and the presence

of unplanned network deployments should be considered by

system designers. Moreover, due to the random spatial positions

of the interferers, it is more insightful to provide performancemetrics that are averaged over fast fading and spatial position

of each interferer.

Inspired by the seminal work in [20], in the emerging hetero-

geneous cellular systems, a promising approach to model inter-

ference is to treat the locations of some network elements (e.g.,

cognitive radios and femto base stations) as points distributed

according to the spatial Poisson point process (PPP). This model

offers analytical flexibility and can provide insightful informa-

tion on theeffect of critical statisticalphysical parameters on the

system performance. For these reasons, network interference

modeling based on PPP spatial models has attracted the interest

of many researchers. Specifically, in [21] and [22], PPPs have

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2184 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 63, NO. 5, JUNE 2014

been used to model cochannel interference from macrocellular

base stations. Cross-tier interference from femtocells was dis-

cussed in [23] and [24], whereas in [25], cochannel interference

in ad hoc networks was investigated. Cochannel interference as

a generic source of interference was addressed in [26] and [27].

In [28], a unified framework for interference characterizations

and analysis in the unlicensed frequency bands was presented,assuming that interferers can have any power spectral density

and are distributed according to a Poisson process in space

and frequency domains. The performance of diversity receivers

in a Rayleigh fading environment and network interference

from a Poisson field of interference sources was addressed in

[29]. In [30], a simplified interference model for heterogeneous

networks to analyze downlink performance in a fixed size cell

in a Poisson field of interferers was proposed. In [31], the

performance of multiantenna systems in a Poisson field of

interferers was addressed.

To the best of our knowledge, although the PPP interfer-

ence model has been used extensively in a variety of wireless

networks to account for the randomness in the number, the

location, and the activity of the interferers, this model has

rarely been applied to the relay and destination nodes of a

multihop relay network. Two recent examples include [32]

and [33]. Specifically, in [32], analytical expressions for the

outage probability (OP) and average bit-error rate of dual-

hop AF relaying, using the best relay in a 2-D Poisson field

of relays, were derived. In [33], the random access transport

capacity of multihop AF relaying in a Poisson interference field

was addressed. In this paper, we analyze the performance of

multihop AF systems in the presence of a Poisson distributed

interference field, in which the relay is assumed to possess per-

fect channel state information. The interference model adoptedin this paper is based on the assumption that the number of

interferers is a Poisson distributed random variable, whereas

the terminals are randomly distributed over the network area

and undergo Nakagami-mfading. Moreover, the wireless linksbetween relay nodes are assumed to be subject to Nakagami-mfading as well. It is also noted that the interference model under

consideration takes into account the randomness in the number

and location of the interferers and the effect of path loss for the

interfering signals. The main contributions of this paper are as

follows.

Using the theory of Foxs H-functions and MellinBarnes

integrals, a novel closed-form expression for the probabil-ity density function (pdf) of the aggregate interference is

first derived. This result is afterward used to obtain closed-

form expressions for important statistics of the signal-

to-interference ratio (SIR) of each hop, i.e., the pdf, the

cumulative distribution function (cdf) of the SIR, and the

moment-generating function (MGF) of the inverse SIR.

Exact analytical expressions for the uth moment of theend-to-end SIR are derived.

Exact analytical expressions and closed-form lower

bounds for the OP are derived. These bounds become tight

at high values of SIR.

Exact analytical expressions and tight lower bounds for the

average bit-error probability (ABEP) of digital modulationschemes and exact analytical expressions for the average

TABLE IMATHEMATICALO PERATORS ANDF UNCTIONS

channel capacity are derived in terms of single integrals.

Such integrals can be efficiently evaluated by employing

Gauss quadrature techniques.

An asymptotic error rate performance analysis is pre-

sented. This provides insights into the parameters affecting

system performance under the presence of interference.

The proposed analysis is tested and verified by numerically

evaluated results accompanied with Monte Carlo simulations.

The remainder of this paper is structured as follows. In

Section II, some important properties of the Foxs H-function,

which are frequently used throughout this paper, are sum-

marized. Section III outlines the system and the interference

models. In Section IV, the statistical properties of the end-to-

end SIR are investigated. In Section V, analytical expressions

for theuth moment of the end-to-end SIR, the OP, the ABEP,and the average channel capacity are presented. In Section VI,

the various performance results and their interpretations

are presented. Finally, concluding remarks are presented in

Section VII. For the convenience of the reader, a comprehensive

list of the mathematical operators and functions used in this

paper is presented in Table I.

II. MATHEMATICAL P RELIMINARIES

Throughout this paper, Foxs H-function is used to obtainanalytical expressions for the statistics of the end-to-end SIR

and for the important performance metrics of interest, such

as the OP, the ABEP, and the average channel capacity. Here,

known results on Foxs H-function are summarized to make this

paper more accessible.

Definition 1: The Foxs H-function is defined as

[36, Eq. (1.2)]

Hk,np,q

x

(ap, Ap)(bq, Bq)

=

1

2

C

kj=1(bj + Bjs)p

j=n+1(aj + Ajs)

nj=1(1 ajAjs)qj=k+1(1 bjBjs)

xsds (1)


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whereC is a suitable contour separating the poles of(bj+Bjs)from the poles of(1 ajAjs).

Note that, for Aj =Bj =1, the Foxs H-Function reducesto the more familiar Meijers G-function [35, Eq. (8.2.1)]. The

following identities presented serve as a direct consequence of

the definition of the H-function by the application of certain

properties of gamma functions.Property 1: There holds the formula [36, Eq. (1.58)]

Hk,np,q

x

(ap, Ap)(bq , Bq)

= Hn,kq,p

1

x

(1 bq, Bq)(1 ap, Ap)

. (2)

Property 2: The following reduction formulas are valid

[36, Eqs. (1.56, 1.57)]:

Hk,np,q

x

(a1, A1), . . . , (ap, Ap)(b1, B1), . . . , (bq1, Bq1), (a1, A1)

=Hk,n

1

p1,q1 x (a2, A2), . . . , (ap, Ap)(b1, B1), . . . , (bq1, Bq1) (3)provided thatn 1 andq > kand

Hk,np,q

x

(a1, A1), . . . , (ap1, Ap1), (b1, B1)(b1, B1), . . . , (bq, Bq)

=Hk1,np1,q1

x

(a1, A1), . . . , (ap1, Ap1)(b2, B2), . . . , (bq , Bq)

(4)

provided thatk 1 andp > n.Therth-order derivative of Foxs H-function can be obtained

using the following property.

Property 3: Identity (5), shown at the bottom of the page,

holds [36, Eq. (1.83)], whereh >0.Throughout this paper, integral transforms of Foxs

H-function are used to derive the main results. The Mellin and

Laplace transforms of the Foxs H-function are of particular

interest. An important property of the H-function states that

the Mellin transform of the product of two Foxs H-functions

is also a Foxs H-function, as summarized in the following

theorem.

Theorem 1: The following integral identity is valid

[36, p. 60], [35, Eq. (2.25.1.1)]:

0

x1Hs,tu,v

x (cu, Cu)(dv, Dv)

Hk,np,q

xr

(ap, Ap)(bq , Bq)

dx

=Hk+t,n+sp+v,q+u

r

(ap+v, Ap+v)(bq+u, Bq+u)

(6)

where,, and are complex numbers;r >0; and

(ap+v, Ap+v) ={(an, An), (1 dvDv, rDv)

(an+1, An+1), . . . , (ap, Ap)}

(bq+u, Bq+u) =

{(bk, Bk), (1

cu

Cu, rCu)

(bk+1, Bk+1), . . . , (bq, Bq)}provided that the following conditions are satisfied:

a =n

j=1

Ajp

j=n+1

Aj+k

j=1

Bjq

j=k+1

Bj >0

b =t

j=1

Cju

j=t+1

Cj +s

j=1

Djv

j=s+1

Dj >0

r >0

|arg

|< b/2

|arg

|< a/2

{} + r min1jk

{bj/Bj}+ min1hs

{dh/Dh} >0

{} + r max1jn

{(aj 1)/Aj}

+ max1ht

{(ch 1)/Ch} 0, > 0,{}+ max1in [(1/Ai)({ai}/Ai)] > 0, and | arg a| < (a ), wherea is definedin Theorem I.

Proof: See [36, p. 51].

Finally, power series expansion of the Foxs H-function,

which are useful in deriving asymptotic results for important

performance metrics of interest, are discussed. Specifically, the

following theorem holds [37, Eq. (3.4)].

Theorem 3: Let us assume that the poles of (1 ajAjs), j =1, . . . , n, and (bj + Bjs), j =1, . . . , k do not

ri=1

x

d

dx ci

xsHk,np,q

zxh

(a1, A1), . . . , (ap, Ap)(b1, B1), . . . , (bq, Bq)

= xs

Hk,n+rp+r,q+r

zxh (c1 s, h), . . . , (cr s, h), (a1, A1), . . . , (ap, Ap)(b1, B1), . . . , (bq , Bq), (c1 s +1, h), . . . , (cr s +1, h)

(5)


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coincide. Then, forq

j=1 Bjp

j=1 Aj >0, x =0, or forqj=1 Bj

pj=1 Aj =0, 0< |x| 1, the diversity order is determined by bnanddecreases asvn increases (bn decreases).

Using (56), the corresponding asymptotic value for

Eeq{erfc(cieq)} and, henceforth, PEcan be obtained withthe help of [35, Eq. (8.4.16/2)] as in

Eeq

erfc(cieq)

1

Nn=1

Bn(ms,nbn)bn(bn)(ms,n)

cbni 12

+ bn

, ifms,n > bn

1

Nn=1

(ms,nbn )Bms,nbn

n

bnms,n(ms,n)(ms,n)cms,ni

12

+ ms,n

, ifms,n < bn

. (57)

E. Average Channel Capacity

The average channel capacity of an N-hop system is obtainedas [60, Eq. (10)]

Cavg= W

Nlog(2)

0

1

t(1 exp(t))M1eq (t)dt (58)

where W is the bandwidth. By employing a J-point GCQtechnique,Cavgcan be approximated as

Cavg= W

Nlog(2)

Jj=0

wjtj

(1 exp(tj))N

n=1

M1n (tj)

(59)

where weightswj and abscissastj are given in (52).

6

By reexpressing (56) as fn() at

for 0+

, where a and t aresuitable parameters, and employing [59, Proposition 1], it becomes evident thatthe diversity order of the considered system is equal to t+1.


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Fig. 1. OP of two-, three- and four-hop AF systems versus SIR per user for

th = 0 dB, ms,1 = ms,2 = 2.2, mI= 1, = 103, and various values

ofvn.

Fig. 2. OP of two-, three-m, and four-hop AF systems versus SIR per user forth = 0 dB,ms,1 = ms,2 = 3, mI =1, vn = 3, and various values of.

VI. NUMERICAL AND C OMPUTERS IMULATIONR ESULTS

Here, various performance results obtained using the

ABEP and average channel capacity expressions presented in

Section V for multihop AF relaying operating over Nakagami-mfading channels with cochannel interference will be presented.

In particular, the following performance evaluation results have

been obtained: 1) Pout versus SIR per user (obtained using(42), (46), and (47) with (18) and (A-4); see Figs. 1 and 2);

2) PE versus SIR per user (obtained using (48)(51) (53), and(57) with (31), (B-3), (35), and (37); see Figs. 3 and 4); and

3) Cavg versus SIR per user (obtained using (59) with (B-3)and (31); see Figs. 5 and 6). To validate the accuracy of the

aforementioned expressions, comparisons with complementaryMonte Carlo simulated performance results are also included

Fig. 3. ABEP of two- and three-hop AF systems employing 16-QAM with

Gray encoding versus SIR per user for ms,1 = ms,2 = 3, mI= 1, vn = 3,and various values of.

Fig. 4. ABEP of two- and three-hop AF systems employing 16-QAM withGray encoding versus SIR per user for ms,1 = ms,2 = 2.3, mI =1, andvarious values ofvn and .

in these figures. In the theoretical analysis, the limit R was considered for mathematical tractability. In the simulation

model, a circular disk of radius R= 300 m was consideredaround each receiving node and interfering terminals placed

according to a spatial Poisson process with node density

n = for n = 1, . . . , N . It is noted that the limitation of thevulnerability circle to radiusR will provide slightly better re-sults than the infinite case, which further improves the accuracy

of the lower bounds. In addition, without loss of generality, for

all numerical results, the Nakagami fading parameter for the

interferers is chosen to be unity (Rayleigh), i.e.,mI=1, since,in practice, the interferers may undergo more severe fading than

the desired signals. Finally, it is assumed that E{n} =1 anddistancesdn are normalized to unity.


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Fig. 5. Averagechannel capacity of two-, three-, andfour-hop AF systems ver-sus SIR per userforms,1 =ms,2{2.5, 1},mI= 1, vn=2.6,and = 10

3.

The Pout performance of two-, three- and four-hop re-laying systems as a function of average SIR per user isshown in Figs. 1 and 2. In particular, in Fig. 1, it is as-

sumed thatth= 0 dB,ms,1= ms,2= 2.2,vn = {2.6, 4} andn = 10

3, whereas in Fig. 2, th= 0 dB, ms,1= ms,2= 3,vn = 3, and = {103, 6 104}. Moreover, to obtain suf-ficient numerical accuracy, typical values of the parameters

A, P, and Q in (42) are A= 25, P =50, and Q= 60. Asobserved from these figures and as expected, Pout improves

with increasing and vn, or decreasing and N. Moreover,the performance evaluation results show that the theoretical

Pout curves are sufficiently close to those obtained by meansof computer simulations and that the lower bound on Pout isquite tight, particularly at high values of.

The PEperformance of two- and three-hop relaying systems,employing 16-QAM signaling as a function of , is shownin Figs. 3 and 4. In particular, in Fig. 3, it is assumed that

vn = 3, ms,1= ms,2= 3, and = {102, 103, 6 104},whereas in Fig. 4, vn = {3, 4}, ms,1= ms,2= 2.3, and ={103, 104}. Regarding the impact of,vn,, andN on PEperformance, similar findings to that reported in Figs. 1 and

2 may be verified. Our conducted numerical experiments haveshown that, to obtain approximation accuracy at the sixth and

beyond significant digits, J 50 must be chosen in (51). Onthe other hand,L = 15 points are enough to obtain sufficientlyaccurate results when (53) is used. Finally, it is clear that the

asymptotic PEcurves correctly predict the diversity order ofthe considered system for all tested cases of interest and that

the lower bounds on PEare tight at high values of.In Figs. 5 and 6, the average channel capacity for the con-

sidered system versus is presented. In particular, in Fig. 5,the average channel capacity of two-, three-, and four-hop AF

systems versusforms,n ={2.5, 1},vn = 2.6, and = 103 isillustrated. In Fig. 6, it is assumed that ms,1= ms,2= 2.3,vn =

{3.2, 4.2}, and ={102, 103}. As it can be observed, similarfindings to those mentioned in Figs. 14 may be verified.

Fig. 6. Average channel capacity of two- and three-hop AF systems versusSIR per user for ms,1 = ms,2 = 2.3, mI = 1, vn = {3.2, 4.2}, and ={102, 103}.

VII. CONCLUSION

In this paper, the performance of a multihop AF relay system

in the presence of a random number of interferers that are

randomly distributed around each node has been addressed.

The interference model considered the effects of a random

number of interferers that are uniformly distributed in the

vicinity of each of the cascaded relays and the destination

node. Analytical expressions for the u-moment of the end-to-end SIR, analytical expressions and tight lower bounds on theOP and ABEP of M-ary modulation schemes were derived.Moreover, a simple asymptotic expression for the ABEP, valid

at high SIR values, and single-fold integral expressions for the

exact average channel capacity were also derived. The proposed

theoretical analysis is supported by numerically evaluated re-

sults compared with extensive Monte Carlo simulations, which

validated the accuracy of the analytical expressions and the

tightness of the proposed bounds. In many wireless networks,

the interfering signals experience attenuation due to path loss

and shadowing, whereas their location and activity around the

receiving node may vary randomly. Therefore, the analysis in

this paper considering such scenarios is useful to the systemdesign engineer for performance evaluation purposes.

APPENDIXA

EVALUATION OFFn() I N T ERMS OF THEMEIJERS G -F UNCTION

Assuming rational values ofbn and using the MellinBarnesrepresentation of the Foxs H-function, Fn() can be ex-pressed as

Fn() = 1

(ms,n)2C

(s)(ms,n+ bns)

(1+ bns)

(

Bn

bn)sds.

(A-1)


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Assuming thatbn = pn/qn, (A-1) can be written as

Fn() = (2)1

(ms,n)

C

(s)

ms,n+ pnsqn

Bn

pnqn

s

1+ pnsqn

ds

s=qnu= qn(ms,n)2

C1

(qnu) pn ms,npn

+ upn

1pn

+ u

Bqnun pnudu. (A-2)By applying the Gauss multiplication formula for the gamma

function [34, Eq. (8.335)]

(nx) = (2)12 (1n)n(nx

12)

n1k=0

x +

k

n

. (A-3)

Fn() can be finally expressed in terms of the MeijersG-function as

Fn() =pms,n1n

(ms,n)

qn

(2)qn1

12

C1

qn1k=0

u + kqn

pn1=0

u +ms,n+

qn

pn1j=0

u + 1+jqn

Bn

qn

qnpnu

du

=pms,n1n

(ms,n) qn

(2)qn1

Gpn+qn,0pn,pn+qnBn

qn

qnpn (pn, 1)(pn, ms,n), (qn, 0)

.

(A-4)

APPENDIXB

EVALUATION OF M1n (t) I N T ERMS OF THEMEIJERS G -F UNCTION

Assuming rational values ofbn and using the MellinBarnesrepresentation of the Foxs H-function,Mn1(t) can be ex-pressed as

M1n (t) = (2)1

(ms,n)

C

(s)(ms,n+ bns)(Bntbn)sds.

(B-1)

Assuming thatbn = pn/qn, (B-1) can be written as

M1n (t) = (2)1

(ms,n)

C

(s)

ms,n+

pns

qn

Bnt

pnqn

sds

s=qnu=

qn(ms,n)2 C1

(qnu)pn ms,npn

+ u Bqnun tpnudu. (B-2)

By applying the Gauss multiplication formula for the gamma

function,M1n (t) can be finally expressed in terms of theMeijers G-function as

M1n (t)

=pms,n1n

pnqn(2)pn+qn21

(ms,n)2

C1

qn1k=0

u +

k

qn

pn1=0

u +

ms,n+

qn

Bn

qn

qn tpn

pnudu

= p

ms,n1n

(ms,n)

pnqn

(2)pn+qn2

Gpn+qn,00,pn+qn Bnqn qn

tpn

pn (pn, ms,n), (qn, 0) .(B-3)

ACKNOWLEDGMENT

The authors would like to thank the anonymous reviewers

and the associate editor for their help in improving the presen-

tation of this paper.

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Valentine A. Aalo (S89M92SM05) was bornin Nigeria on March 23, 1959. He received the

B.S., M.S., and Ph.D. degrees from Southern IllinoisUniversity, Carbondale, IL, USA, in 1984, 1986, and1991, respectively, all in electrical engineering.

In the summer of 1994 and 1995, he was a Fac-ulty Research Associate with the Satellite Commu-nications and Networking Group, Rome Laboratory,

Griffiss Air Force Base, Rome, NY, USA. Since1991, he has been with Florida Atlantic University,Boca Raton, FL, USA, where he is currently a Pro-

fessor with the Department of Computer and Electrical Engineering and Com-puter Science. His current research interests include wireless communications,channel modeling, diversity techniques, cooperative relay networks, wirelesssensor networks, and radar signal processing.

Dr. Aalo is a member of Tau Beta Pi and several IEEE societies. He served

as an Associate Editor for the IEEE T RANSACTIONS ON C OMMUNICATIONS

from 2000 to 2011.

Kostas P. Peppas (M11) was born in Athens,Greece, in 1975. He received the Diploma in electri-caland computer engineering andthe Ph.D. degreeinwireless communications from the National Techni-cal University of Athens, Greece, in 1997 and 2004,respectively.

From 2004 to 2007, he was with the Departmentof Computer Science and Technology, University ofPeloponnese, Tripoli, Greece. Since 2008, he hasbeen a Researcher with the Institute of Informaticsand Telecommunications, National Centre for Sci-

entific Research Demokritos, Athens. He is the author of more than 50journal and conference papers. His current research interests include digitalcommunications over fading channels, multiple-inputmultiple-output systems,wireless and personal communication networks, and system-level analysis anddesign.

George P. Efthymoglou (S94M98) was born inAthens, Greece, on April 22, 1968. He received theB.S. degree in physics from the University of Athens

in 1991 and the M.S. and Ph.D. degrees in electricalengineering from Florida Atlantic University, BocaRaton, FL, USA, in 1993 and 1997, respectively.

From 1997 to 2002, he was with Cadence DesignSystems, where he was engaged in the modeling,simulation, and performance evaluation of third-generation wireless systems. Since 2002, he has beenwith the Department of Digital Systems, University

of Piraeus, Piraeus, Greece, where he is currently an Associate Professor. Hisresearch interests include digital communication systems, with emphasis on

the performance evaluation of wireless systems in the presence of fading andinterference.

Mohammed M. Alwakeel was born in Tabuk,Saudi Arabia, in 1970. He received the B.S. degree in

computer engineering and the M.S. degree in electri-cal engineering from King Saud University, Riyadh,Saudi Arabia, in 1993 and 1998, respectively, and thePh.D. degree in electrical engineering from FloridaAtlantic University, Boca Raton, FL, USA, in 2005.

From 1994 to 1998, hewas a CommunicationsNet-

work Manager withThe National Information Center,Saudi Arabia. From 1999 to 2001, he was with KingAbdulaziz University, Jeddah, Saudi Arabia. From

2009 to 2010, he was an Assistant Professor and the Dean of the Collegeof Computers and Information Technology, Tabuk University, where he iscurrently the Vice-Rector for Development and Quality. His current researchinterests include teletraffic analysis, mobile satellite communications, sensornetworks, and cellular systems.

Sami S. Alwakeel(M13) received the B.Sc. degree(with honors) from King Saud University, Riyadh,Saudi Arabia, and the M.Sc. and Ph.D. degrees fromStanford University, Stanford, CA, USA.

He is currently a Professor with the Departmentof Computer Engineering, College of Computer andInformation Sciences (CCIS), King Saud University(KSU), where he is a founding member and had

served as the Dean from 2003 to 2009. He is alsoa Visiting Scholar with the College of Engineering,Florida Atlantic University, Boca Raton, FL, USA.

He is also one of the founding members of the Smart Electronic Company atKSU and of the Cellular System Research Center, Tabuk University, Tabuk,Saudi Arabia. He is the author of several college and high school textbooks andof articles on networking, computers, and the information technology societyin scientific journals and conferences and in technical and culture magazines.He has worked as a consultant to many Saudi private sector companies andgovernment agencies and contributed to the development and establishment ofmany computer colleges and departments in the Kingdom of Saudi Arabia.

Dr. Alwakeel is one of the founder members of the Saudi Computers Society.

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