 Research
 Open Access
 Published:
New results for Shannon capacity over generalized multipath fading channels with MRC diversity
EURASIP Journal on Wireless Communications and Networking volume 2012, Article number: 336 (2012)
Abstract
In this article, we investigate the Shannon capacity for Lbranch maximal combining ratio (MRC) over generalized multipath fading channel. We derive closedform expressions of the maximal spectral efficiency over Rayleigh, Rician, Nakagamim, and Weibull multipath fading channel under flat fading conditions. The results are expressed in terms of Meijer Gfunctions, which can be evaluated numerically using mathematical tools such as Mathematica and Maple. We show, in particular, that the more the number L increases, the larger the Shannon capacity is. We deduce that four branches are sufficient in several cases to mitigate the fading effect and the channel model will approaches the one of AWGN.
Introduction
The channel capacity is an important parameter in the design of any communication system. It provides an upper bound of maximum transmission rate in a given channel. In 1948, Shannon derived the AWGN channel capacity[1, 2]. Recently, in wireless mobile communication system, the diversity techniques have been used to combat multipath fading and multiuser interference[3].
In last years, several articles have been published regarding the Shannon capacity of fading channels with various important diversity schemes, such as maximum ratio combining (MRC), postdetection equal gain combining (EGC), and selective combining (SC), in terms of generalized special functions. The capacity with MRC in correlated Rayleigh fading in terms of Poisson distribution and Exponential integral was obtained in[4, 5]. In[6, 7], an expression of the capacity of single branch receivers operating over Rician, Nakagamim, and Weibull fading channel was obtained in term of Meijer Gfunction. Some statistics properties, such as the probability density function (PDF) and the cumulative distribution function, of the instantaneous signaltonoise ratio (SNR) per symbol at the output of MRC receiver in correlated Nakagamim fading was derived in terms of Fox’s H and Gamma functions[8] in[9, 10]. A statistical analysis for the capacity over Nakagamim fading with MRC/SC/switch and stay combining (SSC) in terms of Meijer Gfunction was presented in[11]. In[12], the capacity expressions of correlated Nakagamim fading with sualbranch MRC, EGC, SC, and SSC were obtained in terms of Gamma function. Expressions for the capacity of generalized fading channel with MRC/EGC for MIMO/SISO systems based on moment generating function (MGF) approach was obtained in terms of Fox’s H and Meijer functions[13, 14]. Recently, a novel expression for the BER of modulations and Shannon capacity over generalizedK and Nakagamim fading channels in terms of Meijer Gfunction and its generalization[15] was investigated in[16, 17].
The equivalent channel model of a multipath fading channel using a MRC Rake receiver and flat fading has been approximated by a fading channel with fading amplitude is a square root of a sum of a square amplitude of each fading[18, 19]. The equivalent channel model in DSCDMA system with MRCRake receiver was investigated in[18].
In this article, we present novel closedform and analytical expressions, in terms of Meijer Gfunction, for the ergodic Shannon capacity for Lbranch MRCRake receiver over Rician, Rayleigh, Nakagamim, and simple approximation for Weibull multipath fading channel in the nonfrequency selective channels case. We generalize for Lbranch MRC the capacity expression given for single path case (L = 1) in[6, 7]. All the results are validated by numerical Monte Carlo simulations. The study include both DSCDMA system and nospreading system cases.
This article is structured as follows. In Section ‘Channel model’, the equivalent channel models of both DSCDMA communication system and system without spreading using a Rake receiver is introduced. In Section ‘Channel capacity’, the closedform expression of the channel capacity for multipath fading channel (case of Rayleigh, Rice, Nakagamim, and Weibull) is derived. The main results are summarized and some conclusions are given in Section ‘Conclusion’. For the convenience of the reader, an short appendix is added, regarding Meijer Gfunction.
Channel model
In this section, we present the equivalent channel model of communication systems using coherent MRC receiver in both system without spreading and Direct spread spectrum system (DSCDMA).
System with MRC diversity
Consider MRC diversity systems in flat fading environment. Let

x_{ i }, y_{ i }, b_{ i } be the i th transmitted symbol, i th combined received symbol, i th zeromean, N_{0}/2variance Gaussian noise added,

N_{0} is the noise power spectral density,

h_{ il } be the fading amplitude corresponding to the i th symbol and the l th antenna, assumed being i.i.d.,

L be the number of diversity channels,

E_{ s } be the average symbol energy.
The instantaneous combined received symbol energytonoise at the output of the MRC is \gamma =\frac{{E}_{s}}{{N}_{0}}\sum _{l=1}^{L}{h}_{\mathit{\text{il}}}^{2}[19, 20], and then the normalized fading amplitude of channel is given by:
where \mathbb{E}\left[.\right] denotes the expectation operator. The multipath channel model with MRC diversity can be written as
DSCDMA system
Let \left(\right)close="">\n \n \n \n x\n \n \n i\n \n \n (\n k\n )\n \n \n \n and \left(\right)close="">\n \n \n \n y\n \n \n i\n \n \n (\n k\n )\n \n \n \n be, respectively, the i th transmitted and received code symbol of the k th user over a multipath fading channel of the uplink DSCDMA system. In[18], it is shown (see Figure1) that for random spreading sequences, the combination of the inner interleaver/deinterleaver pair, the quadrature spreader, the transmit/receive filter pair, the frequency up/down converter pair, the fading multipath channel, and the Rake receiver can be accurately modeled by the memoryless channel of input \left(\right)close="">\n \n \n \n x\n \n \n i\n \n \n (\n k\n )\n \n \n \n and output \left(\right)close="">\n \n \n \n y\n \n \n i\n \n \n (\n k\n )\n \n \n \n given by:
where:

\left(\right)close="">\n \n \n \n b\n \n \n i\n \n \n (\n k\n )\n \n \n \n represents the zeromean, unitvariance Gaussian noise added to the i th transmitted code symbol of the k th user,

\left(\right)close="">\n \n \n \n \n \n h\n \n \n il\n \n \n (\n k\n )\n \n \n \n \n \n is the fading amplitude associated to the k th user, the l th path and the i th symbol (the \left(\right)close="">\n \n \n \n h\n \n \n il\n \n \n (\n k\n )\n \n \n \n are complex numbers). The amplitudes are assumed independent identically distributed (i.i.d.)

L is the Rake receiver branch number,

g is the spreading factor,

I _{0} is the total noise power spectral density (including multiple access interference, thermal noise, and multipath fading),
For a cell with K users where the channel energy of each user is normalized to 1 \left(\mathbb{E}\left[{\left({A}_{\mathit{\text{iL}}}^{\left(k\right)}\right)}^{2}\right]=1\right), the channel model (3) becomes:
where {A}_{\mathit{\text{iL}}}^{\left(k\right)}=\sqrt{\frac{\sum _{l=1}^{L}\phantom{\rule{0.3em}{0ex}}{\left{h}_{\mathit{\text{il}}}^{\left(k\right)}\right}^{2}}{\sum _{l=1}^{L}\phantom{\rule{0.3em}{0ex}}\mathbb{E}\left[{\left{h}_{\mathit{\text{il}}}^{\left(k\right)}\right}^{2}\right]}}.
Remark 1
From (4) and (1), we can see that the equivalent fading amplitude in both DSCDMA and general case of system without spreading using MRC technique is the same. Consequently, the spectral efficiency is the same in the two cases.
For simplicity of notation, and regardless of the user and bit index, we use I_{0} as the total noise power, the A_{ L } as the equivalent fading amplitude, and h_{ l } as the l th path fading amplitude (that is, we drop the index i and index k).
Channel capacity
The Shannon capacity of a fading channel is the average of AWGN channel capacity where the input is multiplied by the normalized fading amplitude r. In the case of a flat fading, r is assumed to be constant over the symbol duration. Consequently, the energy by symbol becomes E = E_{ s }r^{2}, and the average capacity of a fading channel is a function of the bandwidth W, the instantaneous received SNR \gamma =\stackrel{\u0304}{\gamma}{r}^{2}
where \stackrel{\u0304}{\gamma}=\frac{{E}_{s}}{\mathrm{TW}{I}_{0}} is the average received SNR, T is the symbol period, and f(r) denotes the probability density function (PDF) of the fading amplitude random variable R.
In the following, we give the exact Shannon capacity (5) for the channel models described in the previous section in the case where all \left(\right)close="">\n \n \n \n \n \n h\n \n \n il\n \n \n (\n k\n )\n \n \n \n \n \n are Rayleigh, Rician, Nakagamim or Weibull distributed random variables (RVs).
Rayleigh multipath fading channel
The Rayleigh multipath fading channel is a model of a channel where the receiver can’t receive a direct signal line of sight (LOS) from the source. All received signals are diffracted, reflected or diffused. In this case, the fading of j th path is given by
where X_{j 1} (inphase component) and X_{j 2} (quadrature component) are independent normally distributed RVs with mean 0 and the same variance σ^{2}.
Consequently, the RV \sqrt{\sum _{j=1}^{L}\phantom{\rule{0.3em}{0ex}}\sum _{k=1}^{2}\phantom{\rule{0.3em}{0ex}}{\left({X}_{\mathit{\text{jk}}}/\sigma \right)}^{2}} is a central chi distribution of 2L degrees of freedom, and its pdf is given by
where \Gamma \left(L\right)={\int}_{0}^{+\infty}{t}^{L1}{e}^{t}\mathit{dt} denotes the gamma function[8].
Thus, the PDF of the normalized fading amplitude \frac{1}{\sqrt{2L}\sigma}\sqrt{\sum _{j=1}^{L}\phantom{\rule{0.3em}{0ex}}\sum _{k=1}^{2}{X}_{\mathit{\text{jk}}}^{2}} can be expressed as
From (5), the equivalent channel capacity is
Using the change of variables \gamma =\stackrel{\u0304}{\gamma}{r}^{2}, and the equality Γ(L) = (L − 1)![8], the above expression can also be expressed as
Let {G}_{p,q}^{m,n}\left[x\left\begin{array}{l}{a}_{1},\dots ,{a}_{n},\dots ,{a}_{p}\\ {b}_{1},\dots ,{b}_{m},\dots ,{b}_{q}\end{array}\right.\right] be the Meijer Gfunction[21]where m ≤ q, n ≤ p, and (a_{ i })_{1 ≤ i ≤ p}, (b_{ i })_{1 ≤ i ≤ q} are two complex sequences. Using the transformation formulas (42), (43), and (46) listed in Appendix Appendix 1:
and:
and (see (46) of the Appendix Appendix 1):
we obtain the exact expression of the normalized average capacity (maximal spectral efficiency):
For singlepath Rayleigh fading channel (L = 1),the expression (13) is exactly that found by Sagias et al.[6] using the single branch receiver (SBR). This is due to the fact that the single finger Rake receiver and SBR have identical function.
The Figures2a,b depict the effect of fingers number L on the average Shannon capacity obtained analytically from (13) and via Monte Carlo simulation from (5) by generating 2500 Rayleighdistributed random values. It is shown that as L increases, the capacity increases and converges to that of the AWGN channel. These curves show again that the values L = 4 appears to be practically sufficient to achieve the AWGN channel capacity and to eliminate the fading effect.
The Figure3 shows the PDF of the Rayleigh multipath flat fading amplitude for L = 3, 4, and 6. The curves show that for great values of L, the PDF is infinite for r = 1(no fading). Thus, the channel studied converge to the AWGN one.
Rician multipath fading channel
In this case of fading, the mobile receive, in addition to the other non LOS components, a direct signal from the source. The fading of the j th path is a Rician distributed and can be modelized by:
where X_{j 1} (inphase component) and X_{j 2} (quadrature component) are independent normally distributed RV with the same variance σ^{2} and means s_{ j }cosγ_{ j } and s_{ j }sinγ_{ j }, respectively, (γ_{ j } is a random real number and s_{ j } is the LOS amplitude of the j th path Rician fading). Thus, the normalized A_{ L } is:
Let’s note \beta ={\left(\sum _{j=1}^{L}\phantom{\rule{0.3em}{0ex}}{\left({s}_{j}/\sigma \right)}^{2}+2L\right)}^{1/2}. The RV β A_{ L } is a noncentral chi distribution of 2L degrees of freedom, and noncentrality parameter \lambda ={\left(\sum _{j=1}^{L}\phantom{\rule{0.3em}{0ex}}{\left({s}_{j}/\sigma \right)}^{2}\right)}^{1/2}. Its PDF is known to be[22]
where I_{L−1}(.) is a modified Bessel function of the first kind of order L⏱−⏱1[8].
Using the Jacobian transformation method, the PDF of A_{ L } is given by
The Shannon capacity for the equivalent channel (3) is then
Let’s note \varphi =\frac{\mathit{\lambda \beta}}{\sqrt{\stackrel{\u0304}{\gamma}}}. Using the change of variable \gamma =\stackrel{\u0304}{\gamma}{r}^{2}, we deduce that
Since the modified Bessel function of the first kind can be written as the infinite series ([23], BesselAiryStruveFunctions/BesselI/06/01/01/)
the normalized Shannon capacity can also be written as
This formula generalizes the capacity expression founded by Sagias et al.[6] in the case of one path. It generalizes also our first result corresponding to the normalized Rayleigh multipath fading channel. Indeed, for Rayleigh fading, all LOS amplitudes s_{ j } equal zero (\lambda =\varphi =0,\frac{{\beta}^{2}}{2}=L), and then we find the above expression (13).
The two Figures4a,b show the normalized average Shannon capacity of a Rician multipath fading channel obtained analytically from (21) and via simulation from (5). The average energies associated with each path are given in Table1. By simulation, the series in expression (21) will converge after the 10th first terms for L = 2,3 and after 30th first terms for L = 4 which contribute to the computational complexity reduction.
Since the received power in the case of Rician fading is greater than that in the case of Rayleigh, so the required Rake receiver finger number to reach the AWGN capacity must be less or equal to 4.
The Figure5, shows the evolution of the PDF (17) as function as the number of resolvable paths L. This Figure has been plotted for the values given by the Table1. As L is greater, the normalized amplitude of Rician multipath fading approaches to 1. Furthermore, the Rake receiver may eliminate practically all fading and the couple channel plus Rake receiver has a behavior like that of a gaussian channel.
Nakagamim multipath fading channel
Let N be the Nakagamim distributed RV of average energy E[N^{2}] = 2σ^{2}, and fading parameter m=\frac{{\left(2{\sigma}^{2}\right)}^{2}}{E\left[{\left({N}^{2}2{\sigma}^{2}\right)}^{2}\right]}\ge \frac{1}{2}. The PDF of N is given by[24]
The square of a Nakagami distribution Ω = N^{2} is a gamma distribution Γ(α,β) of parameters α = m and \beta =\frac{2{\sigma}^{2}}{m} and PDF
In the case of this fading, we show the expression of the channel capacity for two cases:

The received average energies are equal \left({\sigma}_{i}=\sigma ,\phantom{\rule{1em}{0ex}}\forall i\u2a7dL\right),

The received average energies are not necessarily equal. This case generalizes the first one.
Case 1: received average energies are equal
Let (N_{ l })_{1≤l≤L} be RVs Nakagamim distributed of the same average energy 2σ^{2}. Since the distribution of the of two independent gamma RVs of parameters (α_{1}β) and (α_{2}β) is a gamma distribution of parameters (α_{1} + α_{2}β)[25], the RV \sum _{l=1}^{L}{\left{N}_{l}\right}^{2} is a gamma distribution of parameters (\mathit{\text{mL}},\frac{2{\sigma}^{2}}{m}) and mean 2L σ^{2}.
Furthermore, \frac{1}{\sqrt{2L}\sigma}\phantom{\rule{0.3em}{0ex}}\sqrt{\sum _{l=1}^{L}\phantom{\rule{0.3em}{0ex}}{\left{N}_{l}\right}^{2}} is a normalized Nakagamim distribution of fading parameter mL and PDF
It follows the expression of the normalized capacity of the equivalent channel model given by the expression (3) is[6]:
This expression generalizes again that of Sagias et al. and that given by (13). Indeed, for m = 1,(25) reduces to the average capacity of the Rayleigh fading equivalent channel given by (13) and for L = 1 we got the channel capacity of the Nakagami fading channel (one path) shown in[6]. In order to justify the limit of three fingers in Rake receiver, we present in both Figure6a,b, for a given value of m, the normalized capacities of Nakagamim multipath fading channel obtained analytically from (25).
It’s clear that for m ≥ 1 (Figures2a and6a,b), L = 4 appears to be sufficient to approach the AWGN channel.
In other ways, Figure7a shows the effect of Nakagami fading parameter m on the maximal spectral efficiency for the given value of L. The greater is m, the better is the spectral efficiency and approaches to the AWGN one. The Figure7b depict the average capacity computed by MonteCarlo simulation generating 2500 Nakagamim distributed random values to validate the analytical expression as presented above in (25).
Practically, for 3path channel and m=3,the fading channel behaves like an AWGN channel.
In Figure8, the PDF of the normalized fading amplitude given by (24) in the case of m = 1. 5 and both L = 4 and L = 3, is plotted as a function as fading amplitude. The multipath fading in this case is equivalent of Nakagami fading channel (one path) with parameter mL (6 and 4.5, respectively). As mL increases, the fading amplitude approaches to 1 and then the channel is approximatively equivalent to the AWGN one.
Case 2: received average energies are not equal
Let {\left({N}_{i}\right)}_{i\u2a7dL} be L independent Nakagamim RVs of average energies \left(\right)close="">\n \n 2\n \n \n \sigma \n \n \n i\n \n \n 2\n \n \n \n, and the same fading parameter m. The square of the RV N_{ i } is a gamma distribution \Gamma \left(m,{\beta}_{i}=\frac{2{\sigma}_{i}^{2}}{m}\right). Furthermore, the PDF of the sum \sum _{i=1}^{L}{N}_{i}^{2} of gamma RVs is given by[25]
where \beta =\frac{2{\sigma}^{2}}{m}=\underset{1\u2a7di\u2a7dL}{\text{min}}{\beta}_{i}, \phantom{\rule{1em}{0ex}}{\u03f5}_{k}=\frac{{\delta}_{k}}{{\beta}^{k}\Gamma \left(\mathrm{Lm}+k\right)} and δ_{ k } is computed recursively by this formulas:
Thus, the PDF of the normalized fading amplitude Z=\frac{1}{\xi}\sqrt{\sum _{i=1}^{L}{N}_{i}^{2}}, where \xi =\sqrt{2\sum _{i=1}^{L}{\sigma}_{i}^{2}} is given by:
The Shannon capacity of the Nakagamim multipath fading channel in the case of unequal average energies is then:
where {C}_{k}=\frac{{\xi}^{2k}{\u03f5}_{k}}{{\stackrel{\u0304}{\gamma}}^{k+\mathrm{Lm}}}{\int}_{0}^{+\infty}{\text{log}}_{2}\left(1+\gamma \right){\gamma}^{k+\mathrm{Lm}1}{e}^{\frac{\gamma {\xi}^{2}}{\beta \stackrel{\u0304}{\gamma}}}\mathrm{d\gamma .} Using the transformation formulas (10), (11), and (12), we obtain:
Thus:
where:
This expression generalizes (25). Indeed, in the case of the same average energies (σ_{ i } = σ), \varphi =\frac{\mathit{\text{mL}}}{\stackrel{\u0304}{\gamma}} and δ_{ k } = 0(k > 0).
The Figure9a compares the normalized Shannon capacity, computed analytically from (31), for the Nakagami3 3path fading channel and average energies 2{\sigma}_{i}^{2}=\frac{1}{4},\frac{1}{4},\frac{1}{2}. The capacity will converge after the K = 15th first terms of the infinite series presented above in (31), and is upper bounded by AWGN capacity. Figure9b shows the convergence of capacity based on infinite series (31) to the simulated one computed from (5).
The Figure10 depicts the PDFs of the normalized 3path fading amplitude in both constants and various average energies (2{\sigma}_{i}^{2}=\frac{1}{4},\frac{1}{4},\frac{1}{2}). The curves have been plotted for m = 3, respectively, from (24) and (28). By simulation, the PDF (28) will converge after the 15th first terms of the series. Furthermore, in the two cases, the fading amplitude of the multipath channel approaches to 1.
Weibull multipath fading channel
Weibull fading, based on the Weibull distribution, is a simple statistical model of fading both in indoor and outdoor wireless communications.
A Weibull distribution W_{ β } with shape parameter β can be transformed to a Rayleigh distribution R and vice versa:
Let λ be the scale parameter of W_{ β }. The PDF of the Weibull distributed RV of parameter β with mean E\left[R\right]=\mathrm{\lambda \Gamma}\left(1+\frac{1}{\beta}\right) and average energy E\left[{R}^{2}\right]={\lambda}^{2}\Gamma \left(1+\frac{2}{\beta}\right) is given by:
Furthermore, the square of a Weibull distribution Ω = W^{2} is a Weibull distribution of shape parameter \frac{\beta}{2} and mean E\left[\Omega \right]={\lambda}^{2}\Gamma \left(1+\frac{2}{\beta}\right). Thus, the normalized \left(\right)close="">\n \n \n \n A\n \n \n L\n \n \n 2\n \n \n \n distribution in the case of Weibull Lpath fading channel is a sum of L i.i.d Weibull distribution of the same parameters. Its PDF is generally unknown excepted some easy cases[26]. In[27], it has been shown that the sum of Weibull RV can be closely approximated by the αμ distribution where (\alpha =\frac{\beta}{2} and μ = L) where the PDF is given by:
where
Furthermore:
The PDF of the approximated normalized fading A_{ L }is then:
By replacing (38) into (5) and using the same change of variable \gamma =\stackrel{\u0304}{\gamma}{\omega}^{2}, the approximated average Shannon capacity for the Weibull Lpath fading channel can be approximated by:
This integral can be solved in closedform ([23], /HypergeometricFunctions/MeijerG/21/02/03/01/),[28]:
where
and \Phi \left(p,l\right)=\frac{p}{l},\frac{p+1}{l},\dots ,\frac{p+l1}{l} and l,k are the two small positive integers coprime such that \frac{l}{k}=\frac{\beta}{2}.
This formulas generalizes the capacity obtained for Rayleigh multipath fading channel (13) by setting \beta =2(k=l=1,\lambda =\frac{1}{L}), and the Shannon capacity of Weibull fading channel (one path) given by Sagias et al. for L = 1[6].
The Figure11a shows the effect of the Weibull fading parameter β on the Shannon capacity of Weibull 4path fading channel, plotted for the values of l and k given by the Table2 from the expression (40).
As the number β increases, as the fading disappears (expression (33)), and the capacity (40) becomes closer to that of the AWGN for four Rake receiver fingers and \beta \u2a7e2.8.
The Figure11b depict the comparison between the analytical and simulation expressions by generating 2000 Weibulldistributed random numbers. It is shown that the approximated Shannon capacity given in (40) is very closed to the exact one.
The Figure12 shows the approximated PDFs of the normalized 4path fading amplitude for the values of β given by the Table2. The curves have been plotted from (38) and show that the multipath fading amplitude is close to 1 for large values of the shape parameter.
Conclusion
In this article, we have derived the closedform expression of the channel capacity over Nakagamim, Rician and Rayleigh multipath flat fading channel with Lbranch MRC receiver and an tight approximation for Weibull case in terms of Meijer Gfunctions. The DSCDMA cellular system case was also considered. The results were validated using MonteCarlo Simulations for all multipath fading channels studied. The plotted curves show that as L increases, the capacity approaches the AWGN channel capacity. Furthermore, four branches are sufficient, in all cases, to eliminate the fading effect and then to achieve the maximum capacity.
Appendix 1
It is convenient to recall notations and definitions concerning Meijer Gfunction (see[21, 23, 28–30]). Let a_{1},…,a_{ n },…,a_{ p } and b_{1},…,b_{ m },…,b_{ q } be complex numbers which we designate by (a_{ p })and (b_{ q }), respectively, for 0 ≤ m ≤ q,0 ≤ n ≤ p. The Gfunction of a complex variable z is given by a MellinBarnes type integral:
where
We require the conditions that a_{ j } − b_{ k } is not zero or a positive integer for j = 1,…,n k = 1,…,m. In the integrand, an empty product is interpreted as unity. The path of integration L if one of the following:

(i)
Left loop beginning at −∞ + λi and ending at −∞ + δi for λ < δ encircling once all the poles −b _{ j }−l (for j = 1…,m,l = 0,1,…) leaving the poles 1−a _{ j } + l(for j = 1…,n,l = 0,1,…) to the right.

(ii)
Right loop beginning at ∞ + λi and ending at ∞ + δi for λ > δ encircling once all the poles 1−a _{ j } + l (for j = 1…,m,l = 0,1,…) leaving the poles b _{ j }−l (for j = 1…,n,l = 0,1,…) to the left.

(iii)
A line with indentation beginning at λ−i ∞ ending at λ + i ∞ (for some real λ) separating the poles of the integrand g like the cases (i) and (ii). We refer to [29, 30] for the existence of G(z).

For any x ([23], /07.34.03.0228.01),
{e}^{x}={G}_{0,1}^{1,0}\left[x\left\begin{array}{c}0\end{array}\right.\right](42) 
For any x ([23], /07.34.03.0456.01),
ln\left(1+x\right)=\underset{2,2}{\overset{1,2}{G}}\left[x\left\begin{array}{c}1,1\\ 1,0\end{array}\right.\right](43) 
For −Π < argx ≤ 0 the modified Bessel function of the first kind ([23], /07.34.03.0230.01),
{I}_{n}\left(x\right)={i}^{n}{G}_{0,2}^{1,0}\left[\frac{{x}^{2}}{4}\left\begin{array}{c}n/2,n/2\end{array}\right.\right](44) 
The Mellin transform of a Gfunction is ([23], /07.34.21.0009.01),
\underset{0}{\overset{\infty}{\int}}{x}^{s1}{G}_{p,q}^{m,n}\left[\mathrm{yx}\left\begin{array}{c}\left({a}_{p}\right)\\ \left({b}_{q}\right)\end{array}\right.\right]\mathrm{dx}={y}^{s}g\left(s\right)(45) 
The Mellin transform of a product of two Gfunctions is ([23], /07.34.21.0011.01),[28],
\begin{array}{cc}\underset{0}{\overset{\infty}{\int}}\hfill & {x}^{\alpha 1}{G}_{u,v}^{s,t}\left[\mathrm{\sigma x}\left\begin{array}{c}\left({c}_{u}\right)\\ \left({d}_{v}\right)\end{array}\right.\right]{G}_{p,q}^{m,n}\left[\mathrm{\omega x}\left\begin{array}{c}\left({a}_{p}\right)\\ \left({b}_{q}\right)\end{array}\right.\right]\mathrm{dx}\hfill \\ ={\sigma}^{\alpha}{G}_{p+v,q+u}^{m+t,n+s}\left[\frac{\omega}{\sigma}\left\begin{array}{c}\left({a}_{n}\right),1\alpha {d}_{1},\dots ,1\alpha {d}_{v},{a}_{n+1},\dots ,{a}_{p}\\ \left({b}_{m}\right),1\alpha {c}_{1},\dots ,1\alpha {c}_{v},{b}_{m+1},\dots ,{b}_{q}\end{array}\right.\right]\hfill \end{array}(46)

References
Shannon CE: A mathematical theory of communication. Bell Syst. Tech. J 1948, 27: 379423; 623–656.
Gallager RG: Information Theory and Reliable Communication. John Wiley and Sons, Inc., New York; 1968.
Simon MK, Alouini MS: Digital Communication Over Fading Channels. Wiley, New York; 2005.
Alouini MS, Goldsmith A: Capacity of Rayleigh fading channels under different adaptive transmission and diversitycombining techniques. IEEE Trans. Veh. Technol 1999, 48: 11651181. 10.1109/25.775366
Mallik RK, Win MZ, Shao JW, Alouini MS, Goldsmith AJ: Channel capacity of adaptive transmission with maximal ratio combining in correlated Rayleigh fading. IEEE Trans. Wirel. Commun 2004, 3(4):11241133. 10.1109/TWC.2004.830823
Sagias NC, Tombras GS, Karagiannidis GK: New results for the Shannon channel capacity in generalized fading channels. IEEE Commun. Lett 2005, 9(2):9799. 10.1109/LCOMM.2005.02031
Sagias NC, Karagiannidis GK, Zogas DA, Mathiopoulos PT, Tombras GS: Performance analysis of dual selection diversity in correlated Weibull fading channels. IEEE Trans. Commun 2004, 52: 10631067. 10.1109/TCOMM.2004.831362
Abramowitz M, Stegun IA: Handbook of Mathematical functions,. 55 (National Bureau of Standards  U.S. Government Printing Office, 1972)
Karagiannidis GK, Sagias NC, Tsiftsis TA: Closedform statistics for the sum of squared Nakagamim variates and its applications. IEEE Trans. Commun 2004, 54(8):13531359.
Ansari IS, Yilmaz F, Alouini MS, Kucur O: New results on the sum of gamma random variates with application to the performance of wireless communication systems over Nakagamim fading channels. IEEE Int. Workshop on Sig. Proc. Advan. in Wireless Comm. accepted in SPAWC’12, available in http://arxiv.org/pdf/1202.2576.pdf
Sagias NC, Lazarakis FI, Alexandridis AA, Dangakis KP, Tombras GS: Higher order capacity statistics of diversity receivers. Wirel. Personal Commun 2011, 56(4):649668. 10.1007/s1127700998376
Khatalin S, Fonseka JP: Capacity of correlated Nakagamim fading channels with diversity combining techniques. IEEE Trans. Veh. Commun 2006, 55(1):142150. 10.1109/TVT.2005.861206
Di Renzo M, Graziosi F, Santucci F: Channel capacity over generalized fading channels: a novel MGFbased approach for performance analysis and design of wireless communication systems. IEEE Trans. Veh. Technol 2010, 59(1):127149.
Yilmaz F, Alouini MS: A unified MGFbased capacity analysis of diversity combiners over generalized fading channels. IEEE Trans. Commun 2012, 60(3):862875. Available at http://arxiv.org/abs/1012.2596
Hai NT, Yakubovich SB: The Double MellinBarnes Type Integrals and their Applications to Convolution Theory. World Scientific, Singapore; 1992.
Ansari IS, AlAhmadi S, Yilmaz F, Alouini MS, Yanikomeroglu H: A new formula for the BER of binary modulations with dualbranch selection over generalizedk composite fading channels. IEEE Trans. Comm 2011, 59: 12911303.
Xia M, Xing C, Chung Y, Aissa S: Exact performance analysis of dualhop semiblind AF relaying over arbitrary Nakagamim fading channels. IEEE Trans. Wirel. Commun 2011, 10(10):34493459.
Cideciyan RD, Eleftheriou E, Rupf M: Concatenated ReedSolomon/convolutional coding for data transmission in CDMABased cellular systems. IEEE Trans. Commun 1997, 45: 12911303. 10.1109/26.634693
Stuber GL: Principles of Mobile Communications. Kluwer Academic Publishers, Mass; 1996.
Proakis JG: Digital Communications. McGrawHill, New York; 1995.
Prudnikov AP, Brychkov YuA, Marichev OI: Integrals and Series, Volume 3: More special functions. Gordon and Breach Science Publishers, New York; 1990.
Johnson NL, Kotz S, Balakrishnan N: Continuous Univariate Distributions. John Wiley & Sons, Inc., New York; 1995.
Wolfram: The Wolfram functions site. Internet (online), http://functions.wolfram.com
Nakagami M: The mDistribution, a general formula of intensity of rapid fading. In Statistical Methods in Radio Wave Propagation. Edited by: Hoffman WC. New York:Pergamon Press, London; 1960:336.
Moschopoulos PG: The distribution of the sum of independent Gamma random variables. Annals Inst. Stat. Math. Part A 1985, 37: 541544. 10.1007/BF02481123
Rinne H: The Weibull distribution. CRC Press, Boca Raton; 2009.
Santos Filho JCS, Yacoub MD: Simple precise approximations to Weibull sums. IEEE Commun. Lett 2006, 10(8):614616. 10.1109/LCOMM.2006.1665128
Adamchik VS, Marichev OI: The algorithm for calculating integrals of hypergeometric type functions and its realization in REDUCE system. In Proc. Int. Conf. on Symbolic and Algebraic Computation,. Tokyo, Japan; 1990:212224.
Mathai AM, Saxena RK: Generalized hypergeometric functions with applications in statistics and physical sciences. Notes of Mathematics Series No. 348, Heidelberg, Germany, (1973)
Erdélyi A, Magnus W, Oberhettinger F, Tricomi FG: Higher Transcendental Functions. McGrawHill, New York; 1953.
Author information
Authors and Affiliations
Corresponding author
Additional information
Competing interests
The authors declare that they have no competing interests.
Authors’ original submitted files for images
Below are the links to the authors’ original submitted files for images.
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
About this article
Cite this article
Bouanani, F.E., BenAzza, H. & Belkasmi, M. New results for Shannon capacity over generalized multipath fading channels with MRC diversity. J Wireless Com Network 2012, 336 (2012). https://doi.org/10.1186/168714992012336
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/168714992012336
Keywords
 Shannon capacity
 Spectral efficiency
 DSCDMA
 Multipath fading channels
 Meijer Gfunctions
 Wireless communication
 Rake receiver
 MRC diversity