- Research Article
- Open Access
Ergodic Capacity for the SIMO Nakagami- Channel
© Efstathios D. Vagenas et al. 2009
- Received: 10 February 2009
- Accepted: 1 July 2009
- Published: 19 August 2009
This paper presents closed-form expressions for the ergodic channel capacity of SIMO (single-input and multiple output) wireless systems operating in a Nakagami- fading channel. As the performance of SIMO channel is closely related to the diversity combining techniques, we present closed-form expressions for the capacity of maximal ratio combining (MRC), equal gain combining (EGC), selection combining (SC), and switch and stay (SSC) diversity systems operating in Nakagami- fading channels. Also, the ergodic capacity of a SIMO system in a Nakagami- fading channel without any diversity technique is derived. The latter scenario is further investigated for a large amount of receive antennas. Finally, numerical results are presented for illustration.
- Fading Channel
- Channel Capacity
- Diversity Technique
- Maximal Ratio Combine
- Ergodic Capacity
In recent years, the use of multiantenna systems provides large spectral efficiency for wireless communications in the presence of multipath fading environments. Multiple antennas can be used at the transmitter (MISO), the receiver (SIMO), or at both of them (MIMO). A SIMO system can be viewed as an antenna diversity scheme (diversity in space). Also, diversity combining is known to be a powerful technique to improve system performance in the presence of fading .
Several papers have been published regarding the capacity of SIMO systems operating in Nakagami environments. In , the channel capacity of a SIMO system in a Nakagami-m fading channel is presented with the assumption that all links between transmit and receive antennas are independent and identically distributed (i.i.d.). In , capacity with MRC and optimal power and rate adaptation is presented while in  Shannon capacity with MRC is derived. In both of them, the assumption that all links are correlated and not identically distributed Nakagami holds. In , capacity of Nakagami-m multipath fading channels with MRC was studied for different power and rate adaptation policies. Also, simple capacity formulas for correlated SIMO Nakagami-m channels were derived in . In , an analytical expression for the capacity of SIMO systems over nonidentically independent Nakagami-m channels was derived. Significant work has been done in , where ergodic capacities of MRC, EGC, SC, and SSC of dual branch diversity systems are presented in closed-form expressions. The capacity expressions were obtained by assuming correlated and identically distributed Nakagami-m links.
In this paper, we examine the ergodic capacity of a SIMO system operating in independent Nakagami-m channels. Specifically we derive closed-form expressions for the ergodic capacity of dual EGC, SC, and SSC systems. For the EGC and SSC cases, we extend the work in  by allowing the parameter m of the Nakagami-m distribution to take noninteger values. Moreover for the SSC case, a compact and quite flexible formula of the ergodic capacity for integer values of m is presented. For the SC case, we present a new expression for the ergodic capacity with the assumption that the Nakagami branches are not identical. Finally, we present for the first time in international literature the ergodic capacity of a SIMO system without using any diversity combining technique over independent nonidentical Nakagami-m branches. In addition, it is shown that when the number of receive antennas is large, the ergodic capacity of such a system can be very well approximated by the ergodic capacity of a Rayleigh channel.
The remaining of this paper is organized as follows. Section 2 introduces a SIMO system. Section 3 examines the ergodic capacity for each diversity scheme and for the case where none of diversity technique is applied. Section 4 presents some results, and Section 5 draws the conclusion.
Consider a SIMO system with receive antennas operating in independent Nakagami-m channels. The total power of the complex transmitted signal at a symbol period is constrained to be . The received signal vector at a random symbol period, assuming that the channel is constant over a symbol period, is given in a baseband representation as
where is the complex channel-gain vector ( means matrix transposition), is the complex antenna-gain vector, and n is the zero-mean complex additive white Gaussian (AWGN) vector with i.i.d. entries and variance . The received signal can be written as
where , and . Thus, the received signal-to-noise ratio (SNR) over a symbol period is
Assuming that the fading process is ergodic, the ergodic channel capacity is
where is the bandwidth of the channel, denotes the ensemble average over , and is the probability density function (PDF) of the SNR .
For all the cases listed below, we will assume that all links between transmitter and receivers are Nakagami-m distributed. From , their PDF is
where is the Gamma function [10, eqution (8.310.1)], , and .
3.1. Ergodic Channel Capacity of Nakagami-m Fading Channel with MRC
Taking into account the above system description and assuming that the receiver has full channel state information (CSI), we choose the phases of , appeared in (2), as . Also we choose . This means that all the signals at the receiver can be added cophasely and weighted according to the channel gain. Thus, (3) becomes
This SNR arises from the MRC diversity technique [1, equation (9.1)]. Substituting the PDF of (6) in (4) gives the ergodic capacity of the Nakagami-m fading channel using MRC. Closed-form expressions have been presented in [3, equation (20)], [4, equation (16)] for the general case where links are correlated and not identically Nakagami-m distributed. If the links follow i.i.d. Nakagami-m variables, the referred equations reduce to [2, equation (36)]. When the parameter of i.i.d Nakagami-m branches takes integer values, the ergodic capacity is given by [5, equation (26)]. A good approximation for the ergodic capacity, where links are independent and not identically distributed, was given in [7, equation (16)]. Also a useful expression for the PDF of for correlated and not identically distributed links can be found in [11, equation (18)].
3.2. Ergodic Channel Capacity of Nakagami-m Fading Channel with Coherent EGC
Taking into account the system description discussed in Section 2 and assuming that the receiver has full CSI, we choose phases and modulus , appeared in (2), as , for all . Thus (3) becomes
This SNR arises using the coherent EGC diversity technique [1, equation (9.188)]. Substituting the PDF of (7) in (4) gives the ergodic capacity of the Nakagami-m fading channel using coherent EGC diversity technique. Finding analytically the PDF of (7) and consequently the channel capacity seems to be a very difficult problem. In , the sum of i.i.d Nakagami-m variables was studied.
The PDF of the sum of two i.i.d. Nakagami-m variables is given by [12, equation (4)]. From [13, page 130], we obtain the PDF transformation for two random variables , related as . Using that PDF transformation in (7) (here ) with the help of [12, equation (4)], we calculate the PDF of the SNR . Thus, the PDF of the SNR of a dual branch EGC system over i.i.d. Nakagami-m fading channels can be written as
where is the average received SNR, and denotes the confluent hypergeometric series, as in [10, equation (9.21.1)]. Closed-form expressions for the capacity of a dual branch equal gain combiner with correlated identically distributed Nakagami-m branches have been presented in [8, equation (8)]. In the following paragraph, we extend that ergodic capacity expression for i.i.d. Nakagami-m branches where the Nakagami parameter m is not necessarily an integer.
The ergodic capacity of a dual-branch EGC system over i.i.d. Nakagami-m fading channels ( and ) is given by (see Appendix A)
where is a generalized hypergeometric series, [10, equation (9.14.1)], and denotes the digamma function, [10, equation (8.36.1)]. For integer values of the parameter m, (9) is reduced to (see Appendix A)
where is the upper incomplete gamma function, as in [10, equation (8.350.2)]. Taking into account [12, equations (8), (9) and (10)] and following the same procedure as in Appendix A (derivation of (9), (10)), we can derive the ergodic capacity of an equal gain combiner for three, four, and M i.i.d Nakagami-m branches. However it is impractical for the purpose of this paper to present all those tedious mathematical formulations. Nevertheless the impact of diversity on the capacity can be clearly depicted by using two branch schemes.
3.3. Ergodic Channel Capacity of Nakagami-m Fading Channel with SC
We assume a combiner that chooses the branch with the highest SNR (or equivalently with the strongest signal assuming equal noise power among the branches). Thus, we choose the antenna gains appearing in (2) as if for all and 0 otherwise. Thus, (3) becomes
This is the widely known SC diversity technique as in [1, Chapter (9.8)]. The PDF of the SNR of two correlated identically distributed Nakagami-m channels is given in [1, equation (9.235)], and the resulting ergodic capacity for m integer is presented in [8, equation (19)].
From [14, equation (14)] and using the PDF transformation for two random variables , related as (here ), we can calculate the PDF of the SNR of two independent and not identically distributed Nakagami-m branches as follows:
In order to find the ergodic capacity of a dual SC system, we have to solve the integral resulting by substituting (12) in (4). Unfortunately, this integral cannot be solved analytically when the Nakagami parameters , take noninteger values. But, assuming that , take integer values, the ergodic capacity of a dual-branch SC system over independent nonidentically distributed Nakagami-m fading channels is given by (see Appendix A)
If the branches are identically distributed ( and ), (13) reduces to
3.4. Ergodic Channel Capacity of Nakagami-m Fading Channel with SSC
We consider a diversity system, for which, when the SNR of the currently connected branch falls below a predetermined threshold, the receiver switches to and stays with another branch, regardless of whether the SNR of that branch is above or below the predetermined threshold. This is the widely known SSC diversity technique as in [1, page 419]. In particular, we choose the antenna gains appearing in (2) as if the SNR at the branch is above a predetermined threshold and 0 otherwise. If the SNR at the branch is below the predetermined threshold , then we choose randomly an where , .
The ergodic capacity of a dual-branch SSC system over i.i.d. Nakagami-m fading channels is given by (see Appendix A)
where is Meijer's- function as defined in [10, page 1032]. For integer values of the parameter m, (16) is reduced to (see Appendix A)
3.5. Ergodic Channel Capacity of Nakagami-m Fading Channel with No Diversity Combining Technique
We suppose that the receiver has no CSI and no complexity (cannot make any signal processing). Thus, the system operates without any diversity technique used. Thus, for all i and the random variable (appearing in (3)) is a sum of Nakagami-m random phase vectors. Consequently, (3) becomes
In order to find the PDF of (18), the PDF of the modulus of the sum of Nakagami-m random phase vectors is necessary. In , that PDF was derived for integer values of the Nakagami parameter m. Using that result, we write the modulus of the sum of Nakagami-m random phase vectors as a sum of weighted Nakagami-m PDFs (see Appendix B).
Thus, using in (18) the PDF transformation for two random variables , related as (here ), we can derive with the help of (B.6) the PDF of the SNR as a sum of weighted gamma PDFs, that is,
where is the PDF of a gamma-distributed random variable as in [13, page 87]. The ergodic channel capacity of a SIMO system without any diversity technique, over independent nonidentically distributed Nakagami-m branches, is given by (see Appendix A)
Herein we will examine the case that the number of receive antennas is large. In that case the random variable (appearing in (3)) tends to be a complex Gaussian random variable, according to the Central Limit Theorem [13, page 278], that is,
where and are the quadrature components of a Nakagami-m vector which follow the PDF according to [16, equation (6)]. That PDF has zero mean, and its variance equals to . According to the Central Limit Theorem, and are zero mean Gaussian random variables with variance . Thus, can be approximated by a Rayleigh distribution, as defined in [13, page 90], with its parameter . Taking into account the random variables transformation in (18), the resulting SNR follows an exponential distribution [13, page 85], that is,
where . Substituting (22) in (4) and using Theorem 3, we obtain
Thus, when L is large (asymptotic analysis), the ergodic capacity of the SIMO system can be approximated by the simple formula of (23), which is in fact the capacity of a Rayleigh channel [2, equations (21), (22)].
Total power of a transmitted symbol
Variance of Gaussian noise
Average received SNR
predetermined threshold of SNR
PDF of received SNR
Meijer's-G function, [10, page 1032]
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