Abstract
We show that channel capacity of N-transmitter M-receiver antenna systems is approximately normal for both Raleigh fading and Ricean environments whether or not antennas are correlated. We give the distribution and percentiles of capacity as a power-series in \((MN)^{-1/2}\) when M or M/N is fixed, both for the case of fixed total power transmitted and also for the case, where total power transmitted increases with N.
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Appendices
Appendix A
Here, we give some results for the complex normal, introduced by Wooding [20], and for the central and non-central complex Wishart. We write
if
with \(\mathbf{A}\) and \(\mathbf{B}\) both \(M \times M\). This is sometimes referred to as the circular complex normal to distinguish it from the case of arbitrary cov\(\left( {\mathbf{X} \atopwithdelims ()\mathbf{Y}} \right) \). So,
and \(\mathbf{Z}\) has density
for \(\mathbf{z}\) in \(\mathcal {C}^M\). Also for \(\mathbf{r}\), \(\mathbf{s}\) in \(\mathcal {C}^M\) with transposes \(\mathbf{r}^T\), \(\mathbf{s}^T\), if \(\mathbf{t} = \mathbf{r}+j\mathbf{s}\), \(T = \mathbf{r}^T \mathbf{X} + \mathbf{s}^T \mathbf{Y} = \left( \mathbf{t}^+ \mathbf{Z} + \mathbf{Z}^+ \mathbf{t} \right) / 2\) then
and so
We write \(\mathbf{Z} + {{\varvec{\mu }}} \sim \mathcal{CN}_M \left( {{\varvec{\mu }}}, \mathbf{V} \right) \). Turin [21] showed that for \(\mathbf{Q}^+ = \mathbf{Q}\) in \(\mathcal{C}^{M \times M}\) and t in \(\mathcal C\),
where
Although not stated, this requires that \(\lambda _1 {\mathcal Re} (t) <1\), where \(\lambda _1\) is the maximum eigenvalue of \(\mathbf{V}^{1/2} \mathbf{Q} \mathbf{V}^{1/2}\).
For \(\mathbf{Z}_1, \ldots , \mathbf{Z}_N\) independent \(\mathcal{CN}_M \left( \mathbf{0}, \mathbf{V} \right) \) the (central) complex Wishart is defined as
Goodman [22] proved
Theorem A. 1
Suppose \(\mathbf{T}^+ = \mathbf{T}\) lies in \(\mathcal{C}^{M \times M}\). Then
Again, the condition \(\lambda _1 < 1\) is implicit, where now \(\lambda _1\) is the maximum eigenvalue of \(\mathbf{V}^{-1/2} \mathbf{T} \mathbf{V}^{-1/2}\). He also gave parallels to real theory for complex multiple coherence, correlation and conditional coherence. His Sect 6 considers the case \(\mathbf{X}(t) : \mathcal{R} \rightarrow \mathcal{R}^M\) a stationary Gaussian process with mean zero; define its Fourier transform \(\mathbf{Z} (\omega ) : \mathcal{R} \rightarrow \mathcal{C}^M\) by
For any given \(\omega \), \(\mathbf{Z}(\omega ) \sim \mathcal{CN} \left( \mathbf{0}, \mathbf{V}(\omega ) \right) \) for a certain \(\mathbf{V}(\omega )\). For \(\omega _1 \ne \omega _2\), \(\mathbf{Z} \left( \omega _1 \right) \) and \(\mathbf{Z} \left( \omega _2 \right) \) are independent.
For z a scalar, set \(\overline{z} = z^+\), the complex conjugate. From a version of (A.1), Reed [23] (using \(\mathbf{H} = \mathbf{V}^T / 2\)) proved
Theorem A. 2
We have
summed over all r! permutations \(p_1 \cdots p_r\) of \(b_1 \cdots b_r\).
He noted as a corollary that
Setting
(A.4) gives
and so on. Note that \(|Z|^2 = \chi ^2_{2M} /2 = G_M\), where \(G_M\) is a gamma random variable with mean M and density \(x^{M-1} \exp (-x) / (M-1)!\) on \((0, \infty )\).
From (A.3) with \(N=1\) one can prove
Theorem A. 3
We have
summed over all \((r-1)!\) permutations \(p_1 \cdot p_r\) of \(b_1 \cdots b_r\) giving connected expressions. (By connected we disqualify breaking \(1 \cdots r\) into two or more groups. For example, \(V_{a_1 b_1} V_{a_2 b_2}\) breaks 12 into 1 and 2; \(V_{a_1 b_2} V_{a_2 b_1} V_{a_3 b_4} V_{a_4 b_3}\) breaks 1234 into 12 and 34.
Here, the joint cumulants for complex random variables \(U_1, U_2, \ldots \) are defined as for real random variables. For example, \(\kappa \left( U_1, U_2 \right) = EU_1 U_2 - EU_1 EU_2\) not \(EU_1 \overline{U}_2 - EU_1 E\overline{U}_2\). Setting \(k_{1 \cdots r}\) equal to the left hand side of (A.5), this gives
We now give a ‘brute force’ extension of Theorem A. 2 from \(\mathbf{Z}\) to \(\mathbf{H} = {{\varvec{\mu }}} + \mathbf{Z}\). We shall give the cumulants of \(\mathbf{X} = \mathbf{H} \mathbf{H}^+\) for \(\mathbf{H} = {{\varvec{\mu }}} + \mathbf{Z}\).
Theorem A. 4
Set
for
Then
for \(r \ge 2\), where
follows by (A.4) with \(r \ne s\). So,
given by (A.5), and
summed over all r permutations \(p_1 \cdots p_r\) of \(1 \cdots r\) giving distinct terms and so on for \(K_{r, r+2}, \ldots , K_{r, 2r-1}\). In particular,
for \(T_{123} = \kappa \left( \overline{Z}_{b_1}, Z_{a_2}, Z_{a_3} \overline{Z}_{b_3} \right) = v_{23} v_{31}\) and \(T_{1234} = \kappa \left( Z_{a_1}, Z_{a_2}, \overline{Z}_{b_3}, \overline{Z}_{b_4} \right) = 0\) by (A.5). Also,
This is enough to give \(\kappa \left( H_{a_1} \overline{H}_{b_1}, \ldots , H_{a_r} \overline{H}_{b_r} \right) \) for \(1 \le r \le 4\). Other values may be derived from (A.6) similarly.
Proof
Note that (A.7)–(A.9) follow from (A.4) and (A.5). To prove (A.10), note that
say, for \(k \left( i_1 \cdots i_r \right) = \kappa \left( x_{1 i_1}, \ldots , x_{ri_r} \right) \). So,
for
say,
by (A.5), and \(\mu _{12} = v_{21}\), \(\mu _{34} = v_{34}v_{43}\), \(\mu _{13} = \mu _{14} = 0\). So,
so that (A.10) holds. \(\square \)
Maiwald and Kraus [24] have obtained the first four non-central moments of \(\mathbf{W}_N / N\) for \(\mathbf{W}_N\) the complex Wishart of (A.2) by differentiating (A.3). We now give a simple method which gives the central and non-central moments of the Wishart up to 12th order.
Theorem A. 5
Suppose
where \(X_n\) are independently-distributed as X in \(\mathcal C\) with cumulants \(\left\{ \kappa _r \right\} \) defined by
say for t in \(\mathcal{C}\). Then the non-central moments of S are
for \(r \ge 1\), where
where \(B_{ri} = B_{ri} \left( {{\varvec{\kappa }}} \right) \) are the exponential Bell polynomials in \({{\varvec{\kappa }}} = \left( \kappa _1, \kappa _2, \ldots \right) \) tabled on page 30 of Comtet [25] up to \(r=12\). Putting \(\kappa _1 = 0\) gives the central moment
where \(B_{ri0} = B_{ri}|_{\kappa _1 = 0}\) since \(B_{ri0} = 0\) for \(i > r/2\). For example,
where \(B_{41} = \kappa _4\), \(B_{42} = 4 \kappa _1 \kappa _3 + 3 \kappa _2^2\), \(B_{43} = 6 \kappa _1^2 \kappa _2\), \(B_{44} = \kappa _1^4\), and \(B_{410} = \kappa _4, B_{420} = 3 \kappa _2^2\). For \(\mathbf{X}\) in \(\mathcal{C}^p\) these become
and
where \(B_i^{a_1 \cdots a_r}\) and \(B_{i0}^{a_1 \cdots a_r}\) can be written down immediately from \(B_{ri}\) and \(B_{ri0}\). For example,
and
where
where \(\displaystyle \sum ^M\) sums over all M permutations of indices \(1 \cdots 4\) giving distinct terms, and
for \(1 \le a_i \le p\), \(i=1, \ldots , r\). For \(\mathbf{X}\) in \(\mathcal{C}^{p \times q}\) these become
and
where \(B_i^{a_1 b_1 \cdots a_r b_r}\) is \(B_i^{a_1 \cdots a_r}\) with \(a_i\) replaced by \(\left( a_i b_i \right) \) and similarly for \(B_{i0}^{a_1 b_1 \cdots a_r b_r}\), these being given in terms of
for \(1 \le a_i \le p\), \(1 \le b_i \le q\) and \(i = 1, \ldots , r\). For example,
and
where
Now consider the weighted version:
where \(\left\{ P_n \right\} \) are constants in \(\mathcal C\) and \(\left\{ X_n \right\} \) are independent copies of X in \(\mathcal C\) with cumulants \(\left\{ \kappa _r \right\} \). Then
say, so
for \(r \ge 1\), where \(\alpha _r = P_{rN} \kappa _r\). Similarly, for \(\mathbf{X}\) in \(\mathcal{C}^{p \times q}\), (A.14)–(A.15) hold for
To apply (A.14), (A.15) to \(\mathbf{S}\) the central complex Wishart \(\mathbf{W}_N\) of (A.2), put \(p = q = M\) and substitute \(\kappa ^{a_1 b_1 \cdots a_r b_r}\) of (A.5). Finally, for the non-central Wishart defined by
where \(\mathbf{H}_1, \ldots , \mathbf{H}_N\) are independent \(\mathcal{CN}_M \left( {{\varvec{\mu }}}, \mathbf{V}\right) \), the moments of \(\mathbf{W}_N\) are given by (A.14), (A.15) with \(p=q=M\) and \(\kappa ^{a_1 b_1 \cdots a_r b_r}\) of (A.6).
Proof
It follows from (A.11) that
So, (A.12) follows from (A.13) since \(B_{r0} = 0\) for \(r \ne 0\). \(\square \)
Appendix B
Theorem B. 1
Suppose that \(\mathbf{A}\) in \(\mathcal{C}^{M \times M}\) is a non-singular matrix, \({{\varvec{\tau }}}\) lies in \(\mathcal{C}^M\) and \(\rho \) lies in \(\mathcal C\). Set
Then
and, for \(r = 1,2,\ldots \),
is given in terms of
by
So,
Also \(e_r = {{\varvec{\tau }}}^+ \mathbf{B}^{-r} {{\varvec{\tau }}}\) is given by
For \(r \ge 2\) the general formula is
where for \(\mathbf{f} = \left( f_1, f_2, \ldots \right) \), \(\widehat{B}_{ri} (\mathbf{f})\) is the ordinary Bell polynomial tabled on page 309 of Comtet [25], and defined by
for z in \(\mathcal{C}\).
Proof
Note that (B.1) holds by equation (3) of Henderson and Searle [19], and (B.2) follows. Set \(\mathbf{a} = \mathbf{A}^{-1}\) and \(\mathbf{b} = \mathbf{A}^{-1} {{\varvec{\tau }}} {{\varvec{\tau }}}^+ \mathbf{A}^{-1}\), so
where \(\displaystyle \sum ^m \mathbf{a}^i \mathbf{b}^j\) sums over all m permutations of the \(i+j\) elements of \(\mathbf{a}^i \mathbf{b}^j\) giving distinct terms. So,
Set \({{\varvec{\tau }}}_r = \mathbf{A}^{-r} {{\varvec{\tau }}}\) so that
for \(i \ge 1\), and (B.3), (B.4) follow.
Set
summed over \(\left\{ i + j = r, i> 0, j > 0 \right\} \), where m is the number of terms: \(\mathbf{S}_2^1 = {{\varvec{\tau }}}_1 {{\varvec{\tau }}}_1^+\), \(\mathbf{S}_3^2 = {{\varvec{\tau }}}_1 {{\varvec{\tau }}}_2^+ + {{\varvec{\tau }}}_2 {{\varvec{\tau }}}_1^+\), \(\mathbf{S}_4^3 = {{\varvec{\tau }}}_1 {{\varvec{\tau }}}_3^+ + {{\varvec{\tau }}}_2 {{\varvec{\tau }}}_2^+ + {{\varvec{\tau }}}_3 {{\varvec{\tau }}}_1^+\), and so on. By (B.6),
and so on. Note (B.5) and the expressions for \(e_1, \ldots , e_6\) above follow. \(\square \)
As a special case we have
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Withers, C.S., Nadarajah, S. The distribution and percentiles of channel capacity for multiple arrays. Sādhanā 45, 155 (2020). https://doi.org/10.1007/s12046-020-01388-0
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DOI: https://doi.org/10.1007/s12046-020-01388-0