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An energy efficient DOA estimation algorithm for uncorrelated and coherent signals in virtual MIMO systems

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Abstract

The multiple input and multiple output (MIMO) and smart antenna (SA) technique have been widely accepted as promising schemes to improve the spectrum efficiency and coverage of mobile communication systems. The definition of direction-of-arrival (DOA) estimation is that multiple directions of incident signals can be estimated simultaneously by some algorithms using the received data. The conventional DOA estimation of user equipments (UEs) is one by one, which is named as sequential scheme. The Virtual MIMO (VMIMO) scheme is that the base station (BS) estimates the DOAs of UEs in a parallel way, which adopts the SA simultaneously. Obviously, when the power is fixed, the VMIMO scheme is much more energy efficient than the sequential scheme. In VMIMO scheme, a set of UEs are grouped together to simultaneously communicate with the BS on a given resource block. Then the BS using multiple antennas can estimate the 2D-DOA of the UEs in the group simultaneously. Based on VMIMO system, the 2D-DOA estimation algorithm for uncorrelated and coherent signals is proposed in this paper. The special structure of mutual coupling matrix (MCM) of uniform linear array (ULA) is applied to eliminate the effect of mutual coupling. The 2D-DOA of uncorrelated signals can be estimated by DOA-matrix method. The parameter pairing between azimuth and elevation is accomplished. Then these estimations are utilized to get the mutual coupling coefficients. Based on spatial smoothing and DOA matrix method, the 2D-DOA of coherent signals can be estimated. The Cramer–Rao lower bound is derived at last. Simulation results demonstrate the effectiveness and performance of the proposed algorithm.

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Acknowledgments

This work was supported in part by the Qing Lan Project, the National Science Foundation of China under Grant 61201410 and 61401147, the Natural Science Foundation of JiangSu Province of China,No.BK20140248, the Fundamental Research Funds for the Central Universities (Program No. HEUCF140803).This work has been partially supported by Instituto de Telecomunicações, Next Generation Networks and Applications Group (NetGNA), Covilhã Delegation, by Government of Russian Federation, Grant 074-U01, and by National Funding from the FCT - Fundação para a Ciência e a Tecnologia through the Pest-OE/EEI/LA0008/2013 Project.

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Correspondence to Guangjie Han or Weijian Si.

Appendix

Appendix

The Cramer–Rao lower bound (CRB) of 1D-DOA estimation in the presence of mutual coupling is given in [12, 37]. In this Appendix, the CRB of joint 2D-DOA and mutual coupling estimation is derived. Consider the array output vector \(\mathbf {x}\left( t \right) \) as a complex Gaussian vector with zero mean. Define \(\mathbf {A} \buildrel \varDelta \over = \left[ {{\mathbf {A}_c},{\mathbf {A}_u}} \right] \), \(\mathbf {E} \buildrel \varDelta \over = blkdiag\left[ {\varvec{\Gamma } ,{\mathbf {I}_{{K_u}}}} \right] \) , the covariance matrix of \(\mathbf {x}\left( t \right) \) is expressed as

$$\begin{aligned} {\mathbf {R}_x} = E\left\{ {\mathbf {x}\left( t \right) \mathbf {x}{{\left( t \right) }^H}} \right\} = \mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} \end{aligned}$$
(64)

For L statistically independent observations of \(\mathbf {x}\left( t \right) \), the logarithm of the likelihood function (the joint probability density function, PDF) can be written as [2, 38]

$$\begin{aligned} \varvec{\Theta }&= \ln \left\{ {f\left( {\mathbf {x}\left( 1 \right) ,\mathbf {x}\left( 2 \right) , \ldots ,\mathbf {x}\left( L \right) } \right) } \right\} \nonumber \\&= const - L \cdot \ln \left\{ {\det \left\{ {{\mathbf {R}_x}} \right\} } \right\} \nonumber \\&-\sum \limits _{t = 1}^L {\mathbf {x}{{\left( t \right) }^H}\mathbf {R}_x^{ - 1}\mathbf {x}\left( t \right) }\nonumber \\&= const - L \cdot \ln \left\{ {\det \left\{ {{\mathbf {R}_x}} \right\} } \right\} \nonumber \\&- L \cdot tr\left\{ {\mathbf {R}_x^{ - 1}{{\widehat{\mathbf {R}}}_x}} \right\} \end{aligned}$$
(65)

where the estimate of auto-correlation covariance \({\widehat{\mathbf {R}}_x}\) is given by

$$\begin{aligned} {\widehat{\mathbf {R}}_x} = \frac{1}{L}\sum \limits _{l = 1}^L {\mathbf {x}\left( l \right) \mathbf {x}{{\left( l \right) }^H}}. \end{aligned}$$
(66)

The unknown parameter vector of \({\mathbf {R}_x}\) is defined as

$$\begin{aligned} \varvec{\eta }&= {\left[ {{\varvec{\alpha } ^T},{\varvec{\beta } ^T},{\varvec{\mu } ^T},{\varvec{\nu } ^T},{\varvec{\kappa } ^T},{\varvec{\varsigma } ^T}} \right] ^T} \nonumber \\ \varvec{\alpha }&= \left[ {{\alpha _{11}}, \ldots ,{\alpha _{1{L_1}}}, \ldots ,{\alpha _{P_1}}, \ldots ,{\alpha _{P{L_P}}},} \right. \nonumber \\&\,{\left. {{\alpha _{{K_c} + 1}}, \ldots ,{\alpha _K}} \right] ^T} \nonumber \\ \varvec{\beta }&= \left[ {{\beta _{11}}, \ldots ,{\beta _{1{L_1}}}, \ldots ,{\beta _{P_1}}, \ldots ,{\beta _{P{L_P}}},} \right. \nonumber \\&\,{\left. {{\beta _{{K_c} + 1}}, \ldots ,{\beta _K}} \right] ^T} \end{aligned}$$
(67)

In order to obtain the unique CRB of \({\varvec{\rho } _k}\), the fading coefficient of the signal in the pth group is normalized to unity. For the sake of simplify, \({\alpha _{p1}}\) is assumed to be the smallest DOA in the pth group in the following derivation. \(\varvec{\mu } = {\left[ {{\mu _{12}}, \ldots ,{\mu _{1{L_1}}}, \ldots ,{\mu _{P_2}}, \ldots ,{\mu _{P{L_P}}}} \right] ^T}\) and \(\varvec{\nu } = {\left[ {{\nu _{12}}, \ldots ,{\nu _{1{L_1}}}, \ldots ,{\nu _{P_2}}, \ldots ,{\nu _{P{L_P}}}} \right] ^T}\) are defined as the real part and \(\varvec{\varpi } = {\left[ {{\varvec{\rho } _1}{{\left( {2:{P_1}} \right) }^T}, \ldots ,{\varvec{\rho } _D}{{\left( {2:{P_D}} \right) }^T}} \right] ^T}\) is defined as the imaginary part, respectively. \(\varvec{\kappa } \) and \(\varvec{\varsigma } \) are defined as the real part and imaginary part of \({\mathbf {c}_1}\), respectively. The kth element in a vector, for example, \(\varvec{\eta } \) is defined as \({\eta _k}\). Then the general expression of the \(\left( {m,n} \right) \)th element in Fisher information matrix (FIM) can be expressed as

$$\begin{aligned} {\mathbf {F}_{{\eta _m}{\eta _n}}} = - E\left\{ {\frac{{{\partial ^2}\varTheta }}{{\partial {\eta _m}\partial {\eta _n}}}} \right\} \end{aligned}$$
(68)

Based on the relationship

$$\begin{aligned}&\frac{{\partial \mathbf {R}_x^{ - 1}}}{{\partial {\eta _m}}} = - \mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}\mathbf {R}_x^{ - 1}\end{aligned}$$
(69)
$$\begin{aligned}&\frac{{\partial \ln \left\{ {\det \left\{ {{\mathbf {R}_x}} \right\} } \right\} }}{{\partial {\eta _m}}} = tr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}} \right\} \end{aligned}$$
(70)

the first derivative of \(\varTheta \) is obtained

$$\begin{aligned} \frac{{\partial \varTheta }}{{\partial {\eta _m}}}&= - Ltr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}} \right\} \nonumber \\&+\,Ltr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}\mathbf {R}_x^{ - 1}{{\widehat{\mathbf {R}}}_x}} \right\} \nonumber \\&= Ltr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}\left( {\mathbf {R}_x^{ - 1}{{\widehat{\mathbf {R}}}_x} - \mathbf {I}} \right) } \right\} . \end{aligned}$$
(71)

The second derivative of \(\varTheta \) is given by

$$\begin{aligned} \frac{{\partial \varTheta }}{{\partial {\eta _m}{\eta _n}}}&= Ltr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}\left( {\mathbf {R}_x^{ - 1}{{\widehat{\mathbf {R}}}_x} - \mathbf {I}} \right) } \right\} \nonumber \\&= Ltr\left\{ {\left( {{{\partial \left( {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}} \right) } \Big / {\partial {\eta _n}}}} \right) \left( {\mathbf {R}_x^{ - 1}{{\widehat{\mathbf {R}}}_x} - \mathbf {I}} \right) } \right\} \nonumber \\&+\,Ltr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}\frac{{\partial \left( {\mathbf {R}_x^{ - 1}{{\widehat{\mathbf {R}}}_x} - \mathbf {I}} \right) }}{{\partial {\eta _n}}}} \right\} \nonumber \\&= Ltr\left\{ {\left( {{{\partial \left( {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}} \right) } \Big / {\partial {\eta _n}}}} \right) \left( {\mathbf {R}_x^{ - 1}{{\widehat{\mathbf {R}}}_x} - \mathbf {I}} \right) } \right\} \nonumber \\&-\,Ltr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}\left( {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _n}}}\mathbf {R}_x^{ - 1}{{\widehat{\mathbf {R}}}_x}} \right) } \right\} . \end{aligned}$$
(72)

Due to \(E\left\{ {{{\widehat{\mathbf {R}}}_x}} \right\} = {\mathbf {R}_x}\), the expectation of both sides of (70) is taken, we have

$$\begin{aligned} {\mathbf {F}_{{\eta _m}{\eta _n}}} = Ltr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _m}}}\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\eta _n}}}} \right\} . \end{aligned}$$
(73)

In the subsequent derivation process, the FIM expression of mixed signals is derived. The notation \({\widetilde{\mathbf {R}}_{{\eta _m}}}\) defines \({{\partial \mathbf {R}} / {\partial {\eta _m}}}\).

1.1 Derivatives with respect to DOA

Based on the expression of covariance matrix (64), the partial derivative of \({\mathbf {R}_x}\) with respect to the mth element \({\alpha _m}\) of \(\varvec{\alpha } \) can be written as

$$\begin{aligned} \frac{{\partial {\mathbf {R}_x}}}{{\partial {\alpha _m}}}&= \mathbf {C}{\widetilde{\mathbf {A}}_{{\alpha _m}}}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} \nonumber \\&+\,\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}\widetilde{\mathbf {A}}_{{\alpha _m}}^H{\mathbf {C}^H}. \end{aligned}$$
(74)

Based on \(tr\left\{ {\mathbf {R} + {\mathbf {R}^H}} \right\} = 2\mathrm{Re} \left\{ {tr\left\{ \mathbf {R} \right\} } \right\} \), we have

$$\begin{aligned} {\mathbf {F}_{{\alpha _m}{\alpha _n}}}&= Ltr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\alpha _m}}}\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\alpha _n}}}} \right\} \nonumber \\&= Ltr\left\{ {\mathbf {R}_x^{ - 1}\left( {\mathbf {C}{{\widetilde{\mathbf {A}}}_{{\alpha _m}}}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} } \right. } \right. \nonumber \\&\left. +\,{\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}\widetilde{\mathbf {A}}_{{\alpha _m}}^H{\mathbf {C}^H}} \right) \times \mathbf {R}_x^{ - 1} \nonumber \\&\left( {\mathbf {C}{{\widetilde{\mathbf {A}}}_{{\alpha _n}}}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} } \right. \nonumber \\&\left. {\left. +\, {\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}\widetilde{\mathbf {A}}_{{\alpha _n}}^H{\mathbf {C}^H}} \right) } \right\} \nonumber \\&= 2L\mathrm{Re} \left\{ {tr\left\{ {\mathbf {R}_x^{ - 1}C{{\widetilde{\mathbf {A}}}_{{\alpha _m}}}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H} } \right. } \right. \nonumber \\&\times \, {\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\widetilde{\mathbf {A}}_{{\alpha _n}}}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} \nonumber \\&+\,\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}\widetilde{\mathbf {A}}_{{\alpha _m}}^H \nonumber \\&\left. {\left. \times \,{ {\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\widetilde{\mathbf {A}}}_{{\alpha _n}}}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}} \right\} } \right\} \end{aligned}$$
(75)

Since only the mth column of \({\widetilde{\mathbf {A}}_{{\alpha _m}}}\) is nonzero, then \({\widetilde{\mathbf {A}}_{{\alpha _m}}}\) can be represented as \({\widetilde{\mathbf {A}}_{{\alpha _m}}} = {\mathbf {A}_\alpha }\varvec{\gamma } _K^m{\left( {\varvec{\gamma } _K^m} \right) ^T}\), where the mth column of the identity matrix is defined as \(\varvec{\gamma } _K^m\). \({\mathbf {A}_ {\varvec{\alpha }} }\) is the derivative matrix of the array manifold matrix, which is expressed as

$$\begin{aligned} {\mathbf {A}_ {\varvec{\alpha }} }&= \left[ {\frac{{d\mathbf {a}\left( {{\alpha _{11}}} \right) }}{{d{\alpha _{11}}}}, \ldots ,\frac{{d\mathbf {a}\left( {{\alpha _{1{P_1}}}} \right) }}{{d{\alpha _{1{P_1}}}}}, \ldots ,\frac{{d\mathbf {a}\left( {{\alpha _{D1}}} \right) }}{{d{\alpha _{D1}}}},} \right. \nonumber \\&{\left. { \ldots ,\frac{{d\mathbf {a}\left( {{\alpha _{D{P_D}}}} \right) }}{{d{\alpha _{D{P_D}}}}},\frac{{d\mathbf {a}\left( {{\alpha _{{K_c} + 1}}} \right) }}{{d{\alpha _{{K_c} + 1}}}}, \ldots ,\frac{{d\mathbf {a}\left( {{\alpha _K}} \right) }}{{d{\alpha _K}}}} \right] ^T} \end{aligned}$$
(76)

Then (73) can be written as

$$\begin{aligned} {\mathbf {F}_{{\alpha _m}{\alpha _n}}}&= 2L\mathrm{Re} \left\{ {tr} \right. \left\{ {\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_ {\varvec{\alpha }} }\varvec{\gamma } _K^m{{\left( {\varvec{\gamma } _K^m} \right) }^T}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}} \right. \nonumber \\&\times \,{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_ {\varvec{\alpha }} }\varvec{\gamma } _K^n{\left( {\varvec{\gamma } _K^n} \right) ^T}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} \nonumber \\&+\, \mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}\varvec{\gamma } _K^m{\left( {\varvec{\gamma } _K^m} \right) ^T}\mathbf {A}_ {\varvec{\alpha }} ^H \times \nonumber \\&\left. {\left. {{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_ {\varvec{\alpha }} }\varvec{\gamma } _K^n{{\left( {\varvec{\gamma } _K^n} \right) }^T}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}} \right\} } \right\} \nonumber \\&= 2L\mathrm{Re} \left\{ {\left( {{{\left( {\varvec{\gamma } _K^m} \right) }^T}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_ {\varvec{\alpha }} }\varvec{\gamma } _K^n} \right) } \right. \nonumber \\&\times \,\left( {{{\left( {\varvec{\gamma } _K^n} \right) }^T}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_ {\varvec{\alpha }} }\varvec{\gamma } _K^m} \right) \nonumber \\&+ \left( {{{\left( {\varvec{\gamma } _K^m} \right) }^T}\mathbf {A}_ {\varvec{\alpha }} ^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_ {\varvec{\alpha }} }\varvec{\gamma } _K^n} \right) \times \nonumber \\&\left. {\left( {{{\left( {\varvec{\gamma } _K^n} \right) }^T}\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}\varvec{\gamma } _K^m} \right) } \right\} \nonumber \\ \end{aligned}$$
(77)

Then the FIM that corresponds to \(\varvec{\alpha } \) can be expressed as

$$\begin{aligned} {\mathbf {F}_{\varvec{\alpha \alpha } }}&= 2L\mathrm{Re} \left\{ {\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_ {\varvec{\alpha }} }} \right) } \right. \nonumber \\&\odot \,{\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_ {\varvec{\alpha }} }} \right) ^T} \nonumber \\&+ \left( {\mathbf {A}_ {\varvec{\alpha }} ^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_ {\varvec{\alpha }} }} \right) \nonumber \\&\odot \,\left. {{{\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}} \right) }^T}} \right\} \end{aligned}$$
(78)

where \( \odot \) denotes the Hadamard product. Similarly, the FIM that corresponds to \(\varvec{\beta } \) can be expressed as

$$\begin{aligned} {\mathbf {F}_{\varvec{\beta \beta } }}&= 2L\mathrm{Re} \left\{ {\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) } \right. \nonumber \\&\odot \,{\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) ^T} \nonumber \\&+\,\left( {\mathbf {A}_{\varvec{\beta }} ^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) \nonumber \\&\odot \,\left. {{{\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}} \right) }^T}} \right\} \end{aligned}$$
(79)

where

$$\begin{aligned} {\mathbf {A}_{\varvec{\alpha }} }&= \left[ {\frac{{d\mathbf {a}\left( {{\beta _{11}}} \right) }}{{d{\beta _{11}}}}, \ldots ,\frac{{d\mathbf {a}\left( {{\beta _{1{P_1}}}} \right) }}{{d{\beta _{1{P_1}}}}}, \ldots ,\frac{{d\mathbf {a}\left( {{\beta _{D1}}} \right) }}{{d{\beta _{D1}}}},} \right. \nonumber \\&{\left. { \ldots ,\frac{{d\mathbf {a}\left( {{\beta _{D{P_D}}}} \right) }}{{d{\beta _{D{P_D}}}}},\frac{{d\mathbf {a}\left( {{\beta _{{K_c} + 1}}} \right) }}{{d{\beta _{{K_c} + 1}}}}, \ldots ,\frac{{d\mathbf {a}\left( {{\beta _K}} \right) }}{{d{\beta _K}}}} \right] ^T}\!.\nonumber \\ \end{aligned}$$
(80)

The FIM that corresponds to the cross terms between \(\varvec{\alpha } \) and \(\varvec{\beta } \) is

$$\begin{aligned} {\mathbf {F}_{\varvec{\alpha \beta } }}&= 2L\mathrm{Re} \left\{ {\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) } \right. \nonumber \\&\odot \,{\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\alpha }} }} \right) ^T} \nonumber \\&+ \left( {\mathbf {A}_{\varvec{\alpha }} ^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) \nonumber \\&\odot \,\left. {{{\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}} \right) }^T}} \right\} \end{aligned}$$
(81)

1.2 Derivatives with respect to fading coefficients

\({\overline{\mathbf {A}} _c} = \left[ {{\mathbf {A}_{c1}}\left( {1:N,2:{L_1}} \right) , \ldots ,\left. {{\mathbf {A}_{cD}}\left( {1:N,2:{L_P}} \right) } \right] } \right. \), and \(\overline{\varvec{\Gamma }} = blkdiag\left\{ {{\varvec{\rho } _1}\left( {2:{L_1}} \right) , \ldots ,{\varvec{\rho } _D}\left( {2:{L_P}} \right) } \right\} \). The matrix \({\varvec{\Psi } _\mathbf {r}} = blkdiag\left\{ {{\mathbf {1}_{\left( {{L_1} - 1} \right) \times 1}}, \ldots ,{\mathbf {1}_{\left( {{L_P} - 1} \right) \times 1}}} \right\} \) and \({\varvec{\Psi } _\mathbf {i}} = blkdiag\left\{ {{\mathbf {j}_{\left( {{L_1} - 1} \right) \times 1}}, \ldots ,{\mathbf {j}_{\left( {{L_P} - 1} \right) \times 1}}} \right\} \), where all the elements of the vector \(\mathbf {1}\) are equal to 1 and all the elements of the vector \(\mathbf {j}\) are equal to the imaginary unit \(j\). According to (73), the \(\left( {{r_m},{r_n}} \right) \)th element of the FIM with respect to fading coefficients can be expressed as

$$\begin{aligned} {\mathbf {F}_{{\mu _m}{\mu _n}}}&= Ltr\left\{ {\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\mu _m}}}\mathbf {R}_x^{ - 1}\frac{{\partial {\mathbf {R}_x}}}{{\partial {\mu _n}}}} \right\} \nonumber \\&= Ltr\left\{ {\mathbf {R}_x^{ - 1}\left( {\mathbf {CA}{{\widetilde{\mathbf {E}}}_{{\mu _m}}}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} } \right. } \right. \nonumber \\&+\,\left. {\mathbf {CAE}{\mathbf {R}_s}\mathbf {E}_{{\mu _m}}^H{\mathbf {A}^H}{\mathbf {C}^H}} \right) \nonumber \\&\times \, \mathbf {R}_x^{ - 1}\left( {\mathbf {CA}{{\widetilde{\mathbf {E}}}_{{\mu _n}}}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} } \right. \nonumber \\&+\left. {\left. {\mathbf {CAE}{\mathbf {R}_s}\mathbf {E}_{{\mu _n}}^H{\mathbf {A}^H}{\mathbf {C}^H}} \right) } \right\} \nonumber \\&= Ltr\left\{ {\mathbf {R}_x^{ - 1}\left( {\mathbf {C}{{\overline{\mathbf {A}}_c}{{\widetilde{\overline{\varvec{\Gamma }}} }}_{{\mu _m}}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}} \right. } \right. \nonumber \\&+ \left. {\mathbf {C}{\mathbf {A}_c}\varvec{\Gamma } {\mathbf {R}_{cs}}{\widetilde{\overline{\varvec{\Gamma }}}}_{ {\mu _m}}^H\overline{\mathbf {A}} _c^H{\mathbf {C}^H}} \right) \nonumber \\&\times \, \mathbf {R}_x^{- 1}\left( {\mathbf {C}{{\overline{\mathbf {A}}}}_c} {{\widetilde{\overline{\varvec{\Gamma }}} }}_{{\mu _n}} {\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H} \right. \nonumber \\&+ \,\left. {\left. {\mathbf {C}{\mathbf {A}_c}\varvec{\Gamma } {\mathbf {R}_{cs}}\widetilde{\overline{\varvec{\Gamma }}}_{{\mu _n}}^H\overline{\mathbf {A}} _c^H{\mathbf {C}^H}} \right) } \right\} \nonumber \\&= 2L\mathrm{Re} \left\{ {tr\left\{ {\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}{{\widetilde{\overline{\varvec{\Gamma }}}}_{{\mu _m}}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H } \right. } \right. \nonumber \\&\times \,{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\overline{\mathbf {A}} _c}{\widetilde{\overline{\varvec{\Gamma }}}_{{\mu _n}}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H} \nonumber \\&+\,\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_c}\varvec{\Gamma } {\mathbf {R}_{cs}}\widetilde{\overline{\varvec{\Gamma }}}_{{\mu _m}}^H\overline{\mathbf {A}} _c^H \nonumber \\&\left. {\left. {{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}{{\widetilde{\overline{\varvec{\Gamma }}}}_{{\mu _n}}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}} \right\} } \right\} \end{aligned}$$
(82)

Based on \({\overline{\varvec{\Gamma }}}_{{\mu _m}} = {\varvec{\upgamma }} _{{K_c} - P}^m{\left( {\varvec{\upgamma } _{{K_c} - P}^m} \right) ^T}{\varvec{\Psi } _\mathbf {r}}\), the real part of fading coefficients of the FIM can be represented as

$$\begin{aligned} {F_{\mu \mu }}&= 2L\mathrm{Re} \left\{ {\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}{\widetilde{\overline{\varvec{\Gamma }}}}_{\mu _m}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H \right. \nonumber \\&\times \,{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\overline{\mathbf {A}} _c}{\widetilde{\overline{\varvec{\Gamma }}}_{{\mu _n}}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H} \nonumber \\&+\,\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_c}\varvec{\Gamma } {\mathbf {R}_{cs}}\widetilde{\overline{\varvec{\Gamma }}}_{{\mu _m}}^H\overline{\mathbf {A}} _c^H \nonumber \\&\times \, \left. {{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}{{\widetilde{\overline{\varvec{\Gamma }}}}_{{\mu _n}}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}} \right\} \nonumber \\&= 2L\mathrm{Re} \left\{ {\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right. \nonumber \\&\odot \,{\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) ^T} \nonumber \\&+\,\left( {\overline{\mathbf {A}} _c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&\odot \left. {{{\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_c}\varvec{\Gamma } {\mathbf {R}_{cs}}\varvec{\Psi } _\mathbf {r}^H} \right) }^T}} \right\} \end{aligned}$$
(83)

Based on \({\overline{\varvec{\Gamma }} _{{\nu _m}}} = \varvec{\gamma } _{{K_c} - P}^m{\left( {\varvec{\gamma } _{{K_c} - P}^m} \right) ^T}{\varvec{\Psi } _\mathbf {i}}\), the imaginary part of fading coefficients of the FIM can be represented as

$$\begin{aligned} {\mathbf {F}_{\varvec{\nu \nu } }}&= 2L\mathrm{Re} \left\{ {\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right. \nonumber \\&\odot \,{\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) ^T} \nonumber \\&+\left( {\overline{\mathbf {A}} _c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&\odot \,\left. {{{\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_c}\varvec{\Gamma } {\mathbf {R}_{cs}}\varvec{\Psi } _\mathbf {i}^H} \right) }^T}} \right\} \end{aligned}$$
(84)

The FIM that corresponds to the cross terms between \(\varvec{\mu } \) and \(\varvec{\nu }\) is

$$\begin{aligned} {\mathbf {F}_{\varvec{\mu \nu } }}&= 2L\mathrm{Re} \left\{ {\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right. \nonumber \\&\odot \,{\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) ^T} \nonumber \\&+\left( {\overline{\mathbf {A}} _c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&\odot \,\left. {{{\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_c}\varvec{\Gamma } {\mathbf {R}_{cs}}\varvec{\Psi } _\mathbf {r}^H} \right) }^T}} \right\} \end{aligned}$$
(85)

1.3 Derivatives with respect to mutual coupling coefficients

Based on (73), the mth and nth element of \({\mathbf {F}_{\varvec{\kappa \kappa } }} \), \({\mathbf {F}_{\varvec{\varsigma } \varvec{\varsigma } }} \) and \({\mathbf {F}_{\varvec{\kappa \varsigma } }} \) can be given respectively as follows

$$\begin{aligned} {\mathbf {F}_{{\varvec{\kappa } _m}{\varvec{\kappa } _n}}}&= 2L\mathrm{Re} \left\{ {tr\left\{ {\mathbf {R}_x^{ - 1}{{\widetilde{\mathbf {C}}}_{{\varvec{\kappa } _m}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}} \right. } \right. \nonumber \\&\times \, {\mathbf {C}^H}\mathbf {R}_x^{ - 1}{\widetilde{\mathbf {C}}_{{\varvec{\kappa } _n}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} \nonumber \\&+\,\mathbf {R}_x^{ - 1}{\widetilde{\mathbf {C}}_{{\varvec{\kappa } _m}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H} \nonumber \\&\times \, \left. {\left. {{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\mathbf {C}_{{\varvec{\kappa } _n}}^H} \right\} } \right\} \end{aligned}$$
(86)
$$\begin{aligned} {\mathbf {F}_{{\varvec{\varsigma } _m}{\varvec{\varsigma } _n}}}&= 2L\mathrm{Re} \left\{ {tr\left\{ {\mathbf {R}_x^{ - 1}{{\widetilde{\mathbf {C}}}_{{\varvec{\varsigma } _m}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}} \right. } \right. \nonumber \\&\times \, {\mathbf {C}^H}\mathbf {R}_x^{ - 1}{\widetilde{\mathbf {C}}_{{\varvec{\varsigma } _n}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} \nonumber \\&+\,\mathbf {R}_x^{ - 1}{\widetilde{\mathbf {C}}_{{\varvec{\varsigma } _m}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H} \nonumber \\&\times \, \left. {\left. {{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\mathbf {C}_{{\varvec{\varsigma } _n}}^H} \right\} } \right\} \end{aligned}$$
(87)
$$\begin{aligned} {\mathbf {F}_{{\varvec{\kappa } _m}{\varvec{\varsigma } _n}}}&= 2L\mathrm{Re} \left\{ {tr\left\{ {\mathbf {R}_x^{ - 1}{{\widetilde{\mathbf {C}}}_{{\varvec{\kappa } _m}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}} \right. } \right. \nonumber \\&\times \,{\mathbf {C}^H}\mathbf {R}_x^{ - 1}{\widetilde{\mathbf {C}}_{{\varvec{\varsigma } _n}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H} \nonumber \\&+\,\mathbf {R}_x^{ - 1}{\widetilde{\mathbf {C}}_{{\varvec{\kappa } _m}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H} \nonumber \\&\times \,\left. {\left. {{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\mathbf {C}_{{\varvec{\varsigma } _n}}^H} \right\} } \right\} \end{aligned}$$
(88)

where

$$\begin{aligned} {\widetilde{\mathbf {C}}_{{\varvec{\kappa } _m}}}&= toeplitz\left\{ {\left[ {0,{{\left( {\varvec{\gamma } _{{M_0}}^m} \right) }^T},{\mathbf {0}_{1,\left( {M - {M_0} - 1} \right) }}} \right] } \right\} , \nonumber \\ m&= 1, \ldots ,{M_0}. \end{aligned}$$
(89)

\(toeplitz\left\{ \mathbf {z} \right\} \) stands for the symmetric Toeplitz matrix constructed by the vector \(\mathbf {z}\).

1.4 DOA-fading coefficients cross terms

$$\begin{aligned} {\mathbf {F}_{\varvec{\alpha \mu } }}&= 2L\mathrm{Re} \left\{ {\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right. \nonumber \\&\odot \,{\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\alpha }} }} \right) ^T} \nonumber \\&+\,\left( {\mathbf {A}_{\varvec{\alpha }} ^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&\odot \left. {{{\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}} \right) }^T}} \right\} \end{aligned}$$
(90)
$$\begin{aligned} {\mathbf {F}_{\varvec{\alpha \nu } }}&= 2L\mathrm{Re} \left\{ {\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right. \nonumber \\&\odot {\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\alpha }} }} \right) ^T} \nonumber \\&+\,\left( {\mathbf {A}_{\varvec{\alpha }} ^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&\odot \left. {{{\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}} \right) }^T}} \right\} \end{aligned}$$
(91)
$$\begin{aligned} {\mathbf {F}_{\varvec{\beta \mu } }}&= 2L\mathrm{Re} \left\{ {\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right. \nonumber \\&\odot \,{\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta } }}} \right) ^T} \nonumber \\&+\,\left( {\mathbf {A}_{\varvec{\beta }} ^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&\odot \,\left. {{{\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}} \right) }^T}} \right\} \end{aligned}$$
(92)
$$\begin{aligned} {\mathbf {F}_{\varvec{\beta \nu }}}&= 2L\mathrm{Re} \left\{ {\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right. \nonumber \\&\odot \,{\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) ^T} \nonumber \\&+\left( {\mathbf {A}_{\varvec{\beta }} ^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&\odot \,\left. {{{\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}} \right) }^T}} \right\} \end{aligned}$$
(93)

1.5 DOA-mutual coupling coefficients cross terms

$$\begin{aligned} {\mathbf {F}_{{\varvec{\alpha }} {\kappa _n}}}&= 2L\mathrm{Re} \left\{ {diag\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}{{\widetilde{\mathbf {C}}}_{{\varvec{\kappa } _n}}}} \right. } \right. \nonumber \\&\times \,\left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\alpha }} }} \right) \nonumber \\&+\,diag\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}} \right. \nonumber \\&\times \, \left. {\left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\widetilde{\mathbf {C}}_{{\varvec{\kappa } _n}}^H\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\alpha }} }} \right) } \right\} \end{aligned}$$
(94)
$$\begin{aligned} {\mathbf {F}_{\varvec{\alpha } {\varvec{\varsigma } _n}}}&= 2L\mathrm{Re} \left\{ {diag\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}{{\widetilde{\mathbf {C}}}_{{\varvec{\varsigma } _n}}}} \right. } \right. \nonumber \\&\times \, \left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\alpha }} }} \right) \nonumber \\&+\,\,diag\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}} \right. \nonumber \\&\times \, \left. {\left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\widetilde{\mathbf {C}}_{{\varvec{\varsigma } _n}}^H\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\alpha }} }} \right) } \right\} \end{aligned}$$
(95)
$$\begin{aligned} {\mathbf {F}_{\varvec{\beta } {\varvec{\kappa } _n}}}&= 2L\mathrm{Re}\left\{ {diag} \right. \left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}{{\widetilde{\mathbf {C}}}_{{\varvec{\kappa } _n}}}} \right. \nonumber \\&\times \, \left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) \nonumber \\&+\,\,diag \left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C} \times } \right. \nonumber \\&\left. {\left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\widetilde{\mathbf {C}}_{{\varvec{\kappa } _n}}^H\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) } \right\} \end{aligned}$$
(96)
$$\begin{aligned} {\mathbf {F}_{\varvec{\beta } {\varvec{\varsigma } _n}}}&= 2L\mathrm{Re} \left\{ {diag} \right. \left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}{{\widetilde{\mathbf {C}}}_{{\varvec{\varsigma } _n}}}} \right. \nonumber \\&\times \, \left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) \nonumber \\&+\,\,diag\left( {\mathbf {E}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}} \right. \nonumber \\&\times \, \left. {\left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\widetilde{\mathbf {C}}_{{\varvec{\varsigma } _n}}^H\mathbf {R}_x^{ - 1}\mathbf {C}{\mathbf {A}_{\varvec{\beta }} }} \right) } \right\} \end{aligned}$$
(97)

where \(diag\left( \mathbf {A} \right) \) is a column vector constructed by the main diagonal elements of matrix \(\mathbf {A}\).

1.6 Fading coefficients-mutual coupling coefficients cross terms

$$\begin{aligned} {\mathbf {F}_{\varvec{\mu } {\varvec{\kappa } _n}}}&= 2L\mathrm{Re} \left\{ {diag} \right. \left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}} \right. \nonumber \\&\times \left. {{\widetilde{\mathbf {C}}}_{{\varvec{\kappa } _n}}}{\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&+diag\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}} \right. \nonumber \\&\times \left. {\left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\widetilde{\mathbf {C}}_{{\varvec{\kappa } _n}}^H\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right\} \end{aligned}$$
(98)
$$\begin{aligned} {\mathbf {F}_{\varvec{\mu } {\varvec{\varsigma } _n}}}&= 2L\mathrm{Re} \left\{ {diag} \right. \left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1} } \right. \nonumber \\&\times \left. {{{\widetilde{\mathbf {C}}}_{{\varvec{\varsigma } _n}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&+\,diag\left( {{\varvec{\Psi } _\mathbf {r}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}} \right. \nonumber \\&\times \left. {\left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\widetilde{\mathbf {C}}_{{\varvec{\varsigma } _n}}^H\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right\} \end{aligned}$$
(99)
$$\begin{aligned} {F_{\nu {\kappa _n}}}&= 2L\mathrm{Re} \left\{ {diag} \right. \left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}} \right. \nonumber \\&\times \left. {{{\widetilde{\mathbf {C}}}_{{\varvec{\kappa } _n}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) \nonumber \\&+\,diag\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1} } \right. \nonumber \\&\times \left. {\left. {\mathbf {CAE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\widetilde{\mathbf {C}}_{{\varvec{\kappa } _n}}^H\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right\} \end{aligned}$$
(100)
$$\begin{aligned} {\mathbf {F}_{\varvec{\nu } {\varvec{\varsigma } _n}}}&= 2L\mathrm{Re}\left\{ {diag} \right. \left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}} \right. \nonumber \\&\times {\widetilde{\mathbf {C}}_{{\varvec{\varsigma } _n}}}\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}{\overline{\mathbf {A}} _c} \nonumber \\&+\,diag\left( {{\varvec{\Psi } _\mathbf {i}}{\mathbf {R}_{cs}}{\varvec{\Gamma } ^H}\mathbf {A}_c^H{\mathbf {C}^H}\mathbf {R}_x^{ - 1}\mathbf {C}} \right. \nonumber \\&\times \left. {\left. {\mathbf {AE}{\mathbf {R}_s}{\mathbf {E}^H}{\mathbf {A}^H}\widetilde{\mathbf {C}}_{{\varvec{\varsigma } _n}}^H\mathbf {R}_x^{ - 1}\mathbf {C}{{\overline{\mathbf {A}} }_c}} \right) } \right\} \end{aligned}$$
(101)

Based on the above formulations, the whole FIM can be expressed as

$$\begin{aligned} {\mathbf {F}_{\varvec{\eta \eta }}}&= \left[ {\begin{array}{l@{\quad }l@{\quad }l@{\quad }l@{\quad }l@{\quad }l} {{\mathbf {F}_{\varvec{\alpha \alpha } }}} &{} {{\mathbf {F}_{\varvec{\alpha \beta } }}} &{} {{\mathbf {F}_{\varvec{\alpha \mu } }}} &{} {{\mathbf {F}_{\varvec{\alpha \nu } }}} &{} {{\mathbf {F}_{\varvec{\alpha \kappa } }}} &{} {{\mathbf {F}_{\varvec{\alpha \varsigma } }}} \\ {\mathbf {F}_{\varvec{\alpha \beta } }^T} &{} {{\mathbf {F}_{\varvec{\beta \beta } }}} &{} {{\mathbf {F}_{\varvec{\beta \mu } }}} &{} {{\mathbf {F}_{\varvec{\beta \nu } }}} &{} {{\mathbf {F}_{\varvec{\beta \kappa } }}} &{} {{\mathbf {F}_{\varvec{\beta \varsigma } }}} \\ {\mathbf {F}_{\varvec{\alpha \mu } }^T} &{} {\mathbf {F}_{\varvec{\beta \mu } }^T} &{} {{\mathbf {F}_{\varvec{\mu \mu } }}} &{} {{\mathbf {F}_{\varvec{\mu \nu } }}} &{} {{\mathbf {F}_{\varvec{\mu \kappa } }}} &{} {{\mathbf {F}_{\varvec{\mu \varsigma } }}} \\ {\mathbf {F}_{\varvec{\alpha \nu } }^T} &{} {\mathbf {F}_{\varvec{\beta \nu } }^T} &{} {\mathbf {F}_{\varvec{\mu \nu } }^T} &{} {{\mathbf {F}_{\varvec{\nu \nu } }}} &{} {{\mathbf {F}_{\varvec{\nu \kappa } }}} &{} {{\mathbf {F}_{\varvec{\nu \varsigma } }}} \\ {\mathbf {F}_{\varvec{\alpha \kappa } }^T} &{} {\mathbf {F}_{\varvec{\beta \kappa } }^T} &{} {\mathbf {F}_{\varvec{\mu \kappa } }^T} &{} {\mathbf {F}_{\varvec{\nu \kappa } }^T} &{} {{\mathbf {F}_{\varvec{\kappa \kappa } }}} &{} {{\mathbf {F}_{\varvec{\kappa \varsigma } }}} \\ {\mathbf {F}_{\varvec{\alpha \varsigma } }^T} &{} {\mathbf {F}_{\varvec{\beta \varsigma } }^T} &{} {\mathbf {F}_{\varvec{\mu \varsigma } }^T} &{} {\mathbf {F}_{\varvec{\nu \varsigma } }^T} &{} {\mathbf {F}_{\varvec{\kappa \varsigma } }^T} &{} {{\mathbf {F}_{\varvec{\varsigma \varsigma } }}} \\ \end{array}} \right] \end{aligned}$$
(102)

Define \(\mathbf {H} = \mathbf {F}_{\varvec{\eta \eta } }^{ - 1}\), the CRBs of coherent signals, uncorrelated signals and mutual coupling coefficients can be given, respectively, as

$$\begin{aligned} CR{B_{{\Omega _c}}}&= \sqrt{\frac{1}{{2{K_c}}}\left( {\sum \limits _{k = 1}^{{K_c}} {{\mathbf {H}_{kk}}} + \sum \limits _{k = K + 1}^{K + {K_c}} {{\mathbf {H}_{kk}}} } \right) }\end{aligned}$$
(103)
$$\begin{aligned} CR{B_{{\Omega _u}}}&= \nonumber \\&\sqrt{\frac{1}{{2{K_c}}}\left( {\sum \limits _{k = {K_c} + 1}^K {{\mathbf {H}_{kk}}} + \sum \limits _{k = K + {K_c} + 1}^{2K} {{\mathbf {H}_{kk}}} } \right) }\end{aligned}$$
(104)
$$\begin{aligned} CR{B_c}&= \sqrt{\frac{1}{{\left\| {{\mathbf {c}_1}} \right\| }}\left( {\sum \limits _{k = 2\left( {K + {K_c} - P} \right) }^{2\left( {K + {K_c} - P + {M_0}} \right) } {{\mathbf {H}_{kk}}} } \right) } \end{aligned}$$
(105)

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Wan, L., Han, G., Rodrigues, J.J.P.C. et al. An energy efficient DOA estimation algorithm for uncorrelated and coherent signals in virtual MIMO systems. Telecommun Syst 59, 93–110 (2015). https://doi.org/10.1007/s11235-014-9886-3

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