Statistical Analysis of a Mobile-to-Mobile
Rician Fading Channel Model
Li-Chun Wang, Senior Member, IEEE, Wei-Cheng Liu, Student Member, IEEE, and Yun-Huai Cheng
Abstract—Mobile-to-mobile communication is an important ap-plication for intelligent transport systems and mobile ad hoc networks. In these systems, both the transmitter and receiver are in motion, subjecting the signals to Rician fading and different scattering effects. In this paper, we present a double-ring with a line-of-sight (LOS) component scattering model and a sum-of-sinusoids simulation method to characterize the mobile-to-mobile Rician fading channel. The developed model can facilitate the physical-layer simulation for mobile ad hoc communication sys-tems. We also derive the autocorrelation function, level crossing rate (LCR), and average fade duration (AFD) of the mobile-to-mobile Rician fading channel and verify the accuracy by simulations.
Index Terms—Double-ring with a line-of-sight (LOS) compo-nent channel model, LOS compocompo-nent, mobile-to-mobile channel model, Rician fading, scattering, sum-of-sinusoids approximation method.
I. INTRODUCTION
M
OBILITY significantly affects wireless networks. In tra-ditional cellular systems, the base station is stationary, and only mobile terminals are in motion. However, in many new wireless systems, such as intelligent transport systems and mobile ad hoc networks, a mobile directly connects to another mobile without the help of fixed base stations. Thus, how mobility affects a system of which both the transmitter and receiver simultaneously move becomes an interesting problem. From the propagation perspective, the scattering environment in the mobile-to-mobile communication channel is different from that in the base-to-mobile communication channel. In the former, both the transmitted and received signals are affected by the surrounding scatterers, whereas in the latter, only the mobile terminal is surrounded by many scatterers. It is the low height of the antenna that causes a ring of scatterers, and typically, high mobility units have a low antenna height. In a short-distance mobile-to-mobile communication link, it is likely that there Manuscript received August 1, 2007; revised March 16, 2008 and April 17, 2008. First published May 7, 2008; current version published January 16, 2009. This work was supported in part by the National Science Council under Con-tract NSC93-2213-E-009-097, ConCon-tract NSC93-2219-E-009-012, and ConCon-tract NSC96-2221-E-009-115-MY3 and in part by the Program for Promoting Academic Excellence of Universities, Ministry of Education, Taiwan, under Contract EX91-E-FA06-4-4. This paper was presented in part at the IEEE Vehicular Technology Conference, Stockholm, Sweden, May 2005. The review of this paper was coordinated by Prof. Z. Yun.L.-C. Wang and W.-C. Liu are with the Department of Communication Engineering, National Chiao Tung University, Hsinchu 300, Taiwan (e-mail: lichun@cc.nctu.edu.tw; wcliu.cm92g@nctu.edu.tw).
Y.-H. Cheng was with the Department of Communication Engineering, Na-tional Chiao Tung University, Hsinchu 300, Taiwan. He is now with Mobinnova Corporation, Taoyuan 33059, Taiwan (e-mail: yunhuai.cheng@gmail.com).
Digital Object Identifier 10.1109/TVT.2008.924999
exists a line-of-sight (LOS) or specular component between the transmitter and the receiver.
In the literature, most channel models for wireless com-munications were mainly developed for the conventional base-to-mobile cellular radio systems [2]–[5]. Whether these to-base channel models are applicable to the mobile-to-mobile communication systems remains unclear. Some, but not many, channel models had previously been studied. In [6], the theoretical performance of the mobile-to-mobile channel was developed. The authors in [7] introduced the discrete line spectrum method for modeling the mobile-to-mobile channel. However, the accuracy of this method was assured only for short-duration waveforms, as discussed in [8]. A simple but accurate sum-of-sinusoids method was proposed for model-ing the mobile-to-mobile Rayleigh fadmodel-ing channel in [8]. The inverse fast Fourier transform (IFFT)-based mobile-to-mobile channel model was also proposed in [9]. Although it is the most accurate method compared with the discrete line spectrum and sum-of-sinusoids methods, the IFFT-based method requires a complex elliptic integration. In [10], the authors presented an analysis of measured radio channel statistics and their possible influence on the system performances in outdoor-to-indoor mobile-to-mobile communication channels. However, in [6]–[11], the effects of the LOS are all ignored.
To evaluate the performance of the physical layer, a sim-ple channel simulator, such as Jakes’ method in conventional cellular systems, is necessary. Related works on the mobile-to-mobile Rician fading channel include the following: In [12], a statistical model for a mobile-to-mobile Rician fading channel with Doppler shifts is presented. In [13], the model in [12] is employed to obtain the probability density function (pdf) of the received signal envelope, the time correlation function and radio frequency spectrum of the received signal, level crossing rates (LCRs), and average fade durations (AFDs).
This paper develops a sum-of-sinusoids mobile-to-mobile Rician fading simulator. First, the “double-ring with an LOS component” model is proposed to incorporate both the LOS and scattering effects. The double-ring scattering model was originally put forward [11], where the scatterers around the transmitter and the receiver were modeled by two independent rings. Second, the theoretical statistical property of the mobile-to-mobile Rayleigh channel is extended to the Rician fading case. The derived theoretical properties of the mobile-to-mobile Rician fading channel are employed to validate the accuracy of the proposed mobile-to-mobile Rician fading channel simulator involving a sum of sinusoids. Furthermore, the higher order sta-tistics of the mobile-to-mobile Rician fading simulator, such as the LCR and AFD, is discussed. Compared with [12] and [13], 0018-9545/$25.00 © 2009 IEEE
this paper provides, in addition, the simulation and theoretical comparisons for the autocorrelation function of the fading en-velope, the comparison between the fading envelope of double-and single-ring scattering models for different K factors, double-and the difference in the fading envelope of both the double- and single-ring scattering models for different K factors.
The rest of this paper is organized as follows: Section II describes the system model and the proposed “double-ring with an LOS component” scattering model. In Section III, the sum-of-sinusoids mobile-to-mobile Rician fading simulator is presented. Section IV analyzes the LCR and AFD. Section V shows the numerical results. In Section VI, concluding remarks are given.
II. SCATTERINGENVIRONMENT
This section describes a double-ring with an LOS
compo-nent scattering model for the mobile-to-mobile Rician fading
channel. For comparison purposes, the independent double-ring scattedouble-ring model for the mobile-to-mobile Rayleigh fading channel is also presented.
A. Traditional Double-Ring Scattering Model
In a mobile-to-mobile communication channel, the antenna heights of both the transmitter and receiver are below the surrounding objects; it is thus likely that both the transmitter and receiver experience rich scattering effects in the propa-gation paths. Reference [11] showed an independent two-ring scattering environment for characterizing the mobile-to-mobile Rayleigh fading channel. According to this scattering model, a sum-of-sinusoids method was suggested to approximate the mobile-to-mobile Rayleigh fading channel. The scatterers are assumed to be uniformly distributed. Let the transmitter and receiver move at the speeds of v1and v2, respectively. For all
M N independent paths, the amplitude of the normalized
com-plex signal received in the mobile-to-mobile Rayleigh fading channel can be expressed as
Y (t) = 1 M N M m=1 N n=1 exp[j(2πf1t cos αn + 2πf2t cos βm+ φnm)] (1)
where f1=|v1|/λ and f2=|v2|/λ are the maximum Doppler
frequencies that result from the motion of transmission (TX) and reception (RX), respectively.|v| denotes the length of a vector v, whereas λ is the carrier wavelength. In (1)
αn = 2nπ− π + θn 4N (2) βm= 2(2mπ− π + ψm) 4M (3)
where the angles of departure in each scattering path θn and
the angle of arrival ψm and φnm in Y (t) are all independent
uniform random variables over [−π, π). It was proved in [4] and [11] that the autocorrelation function of the complex envelope
Y (t) is equal to
RY Y(τ ) =
J0(2πf1τ )J0(2πf2τ )
2 (4)
Fig. 1. Scattering environment in a mobile-to-mobile system with an LOS component.
Fig. 2. Relative velocity v3from the TX with velocity v1to the RX with
velocity v2.
where J0(·) is the zeroth-order Bessel function of the
first kind.
B. Double-Ring With an LOS Component Scattering Model
In some situations, certain LOS components exist between the transmitter and the receiver. Fig. 1 shows the proposed “double-ring with an LOS component” scattering model. In addition to the two scattering rings, an LOS component is added between the transmitter and the receiver. It is complex to present the LOS component by a mathematical formula, particularly when both the transmitter and receiver are in motion. Therefore, we use the concept of relative motion to simplify the problem. Fig. 2 shows the relative velocity v3 of
the transmitter to the receiver if the velocity of the receiver is set to be zero. In the figure, θ3 is the angle between v3 and
the LOS component. The relative velocity of the transmitter v3
can be derived as follows:
|v3| =
(|v1| cos θ12− |v2|)2+ (|v1| sin θ12)2 (5)
θ3= θ1+ θ13 (6)
where θ12 is the angle between vectors v1 and v2, θ1 is the
angle between vector v1 and the LOS component, and the
angle between vectors v1and v3is
θ13= cos−1 |v1|2+|v3|2− |v2|2 2|v1||v3| . (7) Thus, the LOS component of the mobile-to-base station case can be expressed as
where K is the ratio of the specular power to the scattering power, f3 is the Doppler frequency caused by v3, and the
initial phase φ0is uniformly distributed over [−π, π).
III. SUM-OF-SINUSOIDSRICIANFADINGSIMULATOR According to the “double-ring with an LOS component” scattering model shown in Fig. 1, a new sum-of-sinusoids Rician fading simulator for the mobile-to-mobile communica-tion is developed.
A. Signal Model for Double-Ring With an LOS Component Scattering
Because Rayleigh fading is a special case of Rician fading without the specular component, the received complex signal of the mobile-to-mobile Rician fading channel is equivalent to the sum of the scattering signal and an LOS component. Therefore, with reference to (1) and (8), the received complex envelope of the mobile-to-mobile Rician fading channel can be written as
Z(t) = Y (t) + √
K exp [j(2πf√ 3t cos θ3+ φ0)]
1 + K . (9)
The complex signal Z(t) is decomposed into the in-phase component Zc(t) and the quadrature component Zs(t). Then,
it follows that Z(t) = Zc(t) + jZs(t) (10) where Zc(t) = Yc(t) + √ K cos(2πf√ 3t cos θ3+ φ0) 1 + K (11) Zs(t) = Ys(t) + √ K sin(2πf√ 3t cos θ3+ φ0) 1 + K (12) Yc(t) = {Y (t)} (13) Ys(t) = {Y (t)} . (14) B. Second-Order Statistics
The second-order statistical properties of Z(t) are then de-rived. The autocorrelation function of Zc(t) can be calculated as
RZcZc(τ ) = E [Zc(t)Zc(t+τ )] = 1 1+K 1 M NE M m=1 N n=1 cos (2π(f1cos αn + f2cos βm)t+φnm) × N p=1 M q=1
cos (2π(f1cos αp+f2cos βq)
×(t+τ)+φpq)
+KE [cos(2πf3t cos θ3+φ0)
× cos (2πf3(t+τ ) cos θ3+φ0)] + K M NA+ K M NB (15)
where E is the statistical expectation operator
A = E M m=1 N n=1
cos (2π(f1cos αn+ f2cos βm)t + φnm)
× cos (2πf3(t + τ ) cos θ3+ φ0) = 0 (16) B = E cos(2πf3t cos θ3+φ0) M m=1 N n=1
× cos (2π(f1cos αn+f2cos βm)(t+τ )+φnm)
= 0. (17) Because φnm, θn, ψm, and φ0 are mutually independent
random variables, RZcZc(τ ) can further be simplified as
RZcZc(τ ) = 1 1 + K 1 2N ME N n=1 cos(2πf1τ cos αn) × M m=1 cos(2πf2τ cos βm) − N n=1 sin(2πf1τ cos αn) × M m=1 sin(2πf2τ cos βm) + KE [cos(2πf3t cos θ3+ φ0) × cos (2πf3(t + τ ) cos θ3+ φ0)] = 1 1 + K ⎡ ⎢ ⎣2 π π 2 0 cos(2πf1τ cos α) dα × 1 π π 0 cos(2πf2τ cos β) dβ − 2 π π 2 0 sin(2πf1τ cos α) dα 1 π × π 0 sin(2πf2τ cos β) dβ ⎤ ⎦ + K 2(1 + K)cos(2πf3τ cos θ3). (18) Consequently RZcZc(τ ) = J0(2πf1τ )J0(2πf2τ ) + K cos(2πf3τ cos θ3) 2(1 + K) (19)
Fig. 3. Single-ring scattering environment for a mobile-to-mobile Rician fading channel.
is obtained. Similarly, other time correlation functions of Z(t) can be obtained as follows:
RZsZs(τ ) = J0(2πf1τ )J0(2πf2τ ) + K cos(2πf3τ cos θ3) 2(1 + K) (20) RZcZs(τ ) = K sin(2πf3τ cos θ3) 2(1 + K) (21) RZsZc(τ ) =− K sin(2πf3τ cos θ3) 2(1 + K) (22) RZZ(τ ) = J0(2πf1τ )J0(2πf2τ ) + K exp(j2πf3τ cos θ3) 1 + K . (23) Similar derivation and results for mobile-to-base Rician fading channels can be found in [14]–[16].
C. Signal Model With Single-Ring Scattering
For comparison purposes, the Rician fading channel model developed from the single-ring scattering model is shown [6]. Note that the single-ring model developed for mobile-to-base channels may not be directly used for mobile-to-mobile chan-nels. In Fig. 3, scatterers are distributed around the mobile terminal, and there exists an LOS component between the TX and the RX.
In this model, the received signal is the sum of signals from each scattering path with an LOS component. It was shown in [16] that the theoretical autocorrelation function of the complex envelope of the fading signal Z(t) for the single-ring model is
RZZ(τ ) =
J0(2πf1τ ) + K exp(j2πf3τ cos θ3)
1 + K . (24)
We will see later in the numerical results that the new double-ring with an LOS component scattedouble-ring model is more accurate than the single-ring model through the simulation.
IV. HIGHERORDERSTATISTICS
A. LCR
The fading envelope is denoted as a(t), the derivative of the fading envelope as ˙a(t), the pdf of the fading envelope as pa(a),
and the pdf of the slope of the fading envelope as pa˙( ˙a). Then,
the LCR LR of the fading envelope |Z(t)| with respect to a
specified level R can be calculated by [17]
LR= ∞
0
˙apa, ˙a(R, ˙a) d ˙a (25)
where pa, ˙a(a, ˙a) is the joint distribution function of a and ˙a.
Now, the key issue is to find the joint distribution pa, ˙a(a, ˙a).
From [18] and [19], we know that the joint distribution of the fading envelope and envelope slope of a Rician fading signal can be expressed as [20] pa, ˙a(a, ˙a) = 1 2πb2 exp − ˙a2 2b2 · a b0 exp −a2+ s2 2b0 I0 as b0 (26) where s2= E [Zc(t)]2+ E [Zs(t)]2 Ωp= E[a2] = s2+ 2b0 s2=KΩp K + 1 2b0= Ωp K + 1 (27)
where In(·) is the modified nth-order Bessel function of the
first kind. Ωp is the square mean of the fading envelope, s2is
the power of the specular component, and 2b0is the scattered
power. Note that (26) only holds when the frequency of the specular component fs equals the carrier frequency fc. This
means that the Doppler shift of the specular component is zero. This situation only occurs when the impinging angle θ3is fixed
at 90◦or 270◦.
From (26), it is implied that a and ˙a are mutually indepen-dent. Thus, we have
pa˙( ˙a) = 1 2πb2 exp − ˙a2 2b2 (28) pa(a) = a b0 exp −a2+ s2 2b0 I0 as b0 . (29) Then, LRcan be simplified as
LR= pa(R) ∞
0
˙apa˙( ˙a) d ˙a
= pa(R)
b2
2π (30)
where b2=−d2RZZ(τ )/dτ2|τ =0[19]. Recall that the
(23). After derivation, b2can be expressed as b2= 2π2f2 1 + f22+ 2K cos2θ3f32 K + 1 . (31)
Note that b2 here is different from that in [16], which is b2=
2π2b
0f32(1 + 2 cos2θ3). Because we consider the
mobile-to-mobile double-ring model here, b2 is a function of f1, f2,
and f3, but b2 in [16] only associates with a single Doppler
frequency f3.
When θ3is 90◦or 270◦, substituting (27) and (31) into (30)
yields LR= 2(K + 1)R Ωp b2 2πexp −K −(K + 1)R2 Ωp · I0 2R K(K + 1) Ωp . (32)
For the general case where θ3can take a random value, the LCR
has no closed-form solution. In [16], the LCR with uniform im-pinging angles was shown for the mobile-to-base Rician chan-nels. For the special case of the single-ring model (i.e., f1= f3
and f2= 0) with θ3being 90◦or 270◦, b2can be simplified as
that in [16], and (32) can be simplified to [16, eq. (16)]. From [16, eq. (15a)] with an assumption that θ3is uniformly
distributed on [0, 2π), we can also have
LR= 2(1 + K) πΩp Rf3· exp −K−(1 + K)R2 Ωp · π 0 1 + 2 R ΩpK 1 + K cos 2θ 3· cos α · exp 2R K(1 + K) Ωp
cos α−2K cos2θ3·sin α
dα.
(33) When θ3is 90◦or 270◦, (33) can be simplified to (32).
B. AFD
According to the definition in [17], the AFD ¯τRfor a
speci-fied level R is ¯ τR= P (a≤ R) LR . (34) Since the envelope of the signal is Rician distributed, ¯τRcan be
expressed as ¯ τR= 1− Q√2K, 2(K+1) Ωp R LR (35)
Fig. 4. Real part of the autocorrelation of the complex envelope Z(t), where
N = M = 8 for K = 0, 1, 3, and 9.
where the Marcum’s Q-function is defined as
Q(a, b) = ∞ b x exp −x2+ a2 2 I0(ax) dx. (36) V. NUMERICALRESULTS
This section first validates the proposed sum-of-sinusoids mobile-to-mobile Rician fading simulator and then compares the correlation functions, pdf, and LCR and AFD of the pro-posed model with the theoretical values. Consider that the max-imum Doppler frequencies for TX and RX are 100 and 20 Hz, respectively, and θ1= π/3, θ12= π/5. From these values, we
can find that θ3= 1.1865.
A. Effects of the Rician Factor
Fig. 4 shows the correlation properties of the proposed sum-of-sinusoids mobile-to-mobile simulator. The solid line in the figure represents the theoretical value, whereas the dashed line represents the simulation results of the proposed channel model. Clearly, the two values match quite well for different Rician factors. Furthermore, for the same delay time τ , the magnitude of the channel correlation RZZ(τ ) is proportional
to the magnitude of the Rician factor K. With reference to (23), it can be seen that for a large enough delay time τ ,
J0(2πf1τ )J0(2πf2τ )≈ 0 and J0(2πf1τ )J0(2πf2τ )
K exp(2πf3τ cos θ3). Thus, it follows that
{RZZ(τ )} K 1 + K exp(j2πf3τ cos θ3) = K 1 + K cos(2πf3τ cos θ3). (37) Therefore, the maximum amplitude of the autocorrelation function RZZ(τ ) is proportional to (K/1 + K) because
−1 ≤ cos(2πf3τ cos θ3)≤ 1. As K increases, the peaks of
Fig. 5. Real part of the autocorrelation of the fading envelope of double- and single-ring scattering models for K = 1.
B. Comparison of a Double-Ring With an LOS Component Model and a Single-Ring Model
This part compares the proposed mobile-to-mobile Rician channel model developed from the double-ring with an LOS component scattering model with that developed from the single-ring scattering model [14] for different Rician factors and different numbers of scatterers. The main purpose of the comparison is to demonstrate that it is more suitable to employ the double-ring scattering model to characterize the mobile-to-mobile communication channel, i.e., the single-ring model developed for mobile-to-base channels may not be directly used for mobile-to-mobile channels. Fig. 5 show the correlation of the double-ring model with eight scatterers, the single-ring model with eight scatterers, the single-ring model with 64 scat-terers, and the theoretical correlation functions for K = 1. Obviously, the double-ring model perfectly matches the ideal curve for [RZZ(τ )] and yields better performance than the
single-ring model, even when 64 scatterers are used in the single-ring model. The difference between the two scattering models is significant.
C. LCR and AFD
Fig. 6 shows the LCR of a mobile-to-mobile Rician channel fading envelope obtained using the sum-of-sinusoids method and that from theoretical analysis. As can be seen, the LCR de-creases with the increase in the Rician factor. This phenomenon can be explained by the fact that channel fading has a greater correlation with a larger amount of LOS components. Once the correlation arises, the change in channel fading decreases.
Fig. 7 shows the analytical and simulated values of the normalized AFD for different Rician factors. As shown in the figure, the larger the Rician factor, the larger the AFD. This property is caused by the higher correlation of the fading envelope for a larger Rician factor. Thus, if the signal envelope fades below a specified level, it is less likely that it will exceed the level.
The numerical results for the LCR and AFD show some devi-ation of the simuldevi-ation from the theoretical values, particularly
Fig. 6. Normalized envelope LCR for mobile-to-mobile Rician fading. The solid line denotes the theoretical results, whereas the dashed line denotes the simulation results, where ρ = R/ Ωp.
Fig. 7. Normalized AFD for a mobile-to-mobile Rician fading channel for
K = 1, 3, 7, and 10.
for small K (1 and 3). The simulation curves consistently fall below the analytical curves, which do not occur for the larger values of K. This is because when K is small, the scatterers will dominate the double-ring model. The simulation can only produce finite scatterers, which cannot approach the ideal case enough; thus, the deviation occurs. When K is large, the LOS term dominates the double-ring model; hence, the problem of finite number of scatterers is not very significant compared with the cases of small values of K.
VI. CONCLUSION
In this paper, a sum-of-sinusoids-based mobile-to-mobile Rician fading simulator has been developed. The double-ring scattedouble-ring model was proposed to characterize the mobile-to-mobile communication environment with LOS components. Furthermore, the theoretical correlation functions of the mobile-to-mobile Rician channel were derived, and its accuracy was verified by simulations. The LCR and AFD of the
mobile-to-mobile Rician fading channel were derived. Finally, it was proved that the proposed sum-of-sinusoids approximation developed from the double-ring with an LOS component model can approach the theoretical value more closely than the single-ring model at a slightly higher cost of computational loads.
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Li-Chun Wang (S’92–M’96–SM’06) received the
B.S. degree from the National Chiao Tung Univer-sity, Hsinchu, Taiwan, in 1986, the M.S. degree from the National Taiwan University, Taipei, Taiwan, in 1988, and the M.Sc. and Ph.D. degrees from Georgia Institute of Technology, Atlanta, in 1995 and 1996, respectively, all in electrical engineering.
In 1995, he was affiliated with Bell Northern Re-search of Northern Telecom, Inc., Richardson, TX. From 1996 to 2000, he was with AT&T Laboratories, where he was a Senior Technical Staff Member with the Wireless Communications Research Department. Since August 2000, he has been an Associate Professor with the Department of Communication Engineering, National Chiao Tung University. He has authored more than 40 journal and 100 international conference papers. He is the holder of three U.S. patents. His current research interests are in the areas of adaptive/cognitive radio networks and cross-layer optimization for cooperative MIMO systems.
Prof. Wang served as an Associate Editor of the IEEE TRANSACTIONS ON
WIRELESSCOMMUNICATIONSfrom 2001 to 2006 and as a Guest Editor of the Special Issue on “Mobile Computing and Networking” of the IEEE JOURNAL ONSELECTED AREAS INCOMMUNICATIONS in 2005 and on “Radio Re-source Management and Protocol Engineering in Future IEEE Broadband Networks” of the IEEE Wireless Communications Magazine in 2006. He was the organizing Chair of the MIMO Symposium for the First International Wireless Communications Mobile Computing Conference (IWCMC 2006) and the Technical Program Committee (TPC) Vice Chair of the IEEE VTS Asia Pacific Wireless Communications Symposium in 2006 and 2007. He is the TPC Co-Chair of the 2010 IEEE Vehicular Technology Conference. He was a corecipient (with G. L. Stüber and C.-T. Lea) of the 1997 IEEE Jack Neubauer Best Paper Award from the IEEE Vehicular Technology Society.
Wei-Cheng Liu (S’04) received the B.S. and M.S.
degrees in electrical engineering from the National Tsing Hua University, Hsinchu, Taiwan, in 1999 and 2001, respectively. He is currently working toward the Ph.D. degree with the Department of Communi-cation Engineering, National Chiao Tung University, Hsinchu.
After receiving the M.S. degree, he served his mil-itary service in Cheng Gong Ling, Taichung, Taiwan. In 2002, he was a GSM Layer 1 Software Engineer with Compal Communications, Inc., Taipei, Taiwan. His current research interests are in the areas of MIMO Rician channels in mobile ad hoc networks, cross-layer rate and power adaptation for wireless LANs, performance analysis for UWB systems, space–time–frequency code design, and cooperative network coding.
Yun-Huai Cheng was born in Taiwan in 1981. He
received the B.Sc. degree in electrical and control engineering and the M.Sc. degree from the National Chiao Tung University, Hsinchu, Taiwan, in 2003 and 2005, respectively.
He is currently with Mobinnova Corporation, Taoyuan, Taiwan. His research interests are in the field of wireless communications.
