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Transmit antenna selection for millimeter-wave communications using multi-RIS with imperfect transceiver hardware

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Abstract

This article presents a comprehensive exploration of the synergy between transmit antenna selection (TAS) and reconfigurable intelligent surfaces (RISs) in millimeter-wave (MW) communication systems, considering the impact of practical conditions. Notably, it accounts for imperfect transceiver hardware (ITH) at both the transmitter and receiver. Additionally, real-world channel models and receiver noise statistics are integrated into the analysis, providing a realistic representation of wireless systems in future networks. Mathematical formulas of outage probability (OP) and system throughput (ST) of the multi-RIS-assisted MW communications with ITH and TAS (shortened as the considered communications) are derived for analyzing the system behaviors. These formulas facilitate a comprehensive examination of system behavior. Through a series of comparative scenarios, including evaluations of OP and ST with and without TAS, with and without RISs, and with and without ITH (where the absence of ITH is denoted as perfect transceiver hardware, or PTH), the study substantiates the substantial advantages of TAS and RISs while shedding light on the significant influence of ITH. It is demonstrated that even in the presence of ITH, MW communication performance can be dramatically enhanced by optimizing the number of transmit antennas, selecting suitable carrier frequencies and RIS placements, and utilizing appropriate bandwidth. Ultimately, the derived formulas are rigorously validated through Monte-Carlo simulations, reinforcing the credibility of the findings.

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Notes

  1. It is noteworthy that while mathematical analysis provides valuable insights into the behavior of wireless communication systems, it is essential to recognize its limitations in capturing the full complexity of real-world scenarios. Integrating simulations, empirical studies, and practical experiments is often necessary to complement mathematical models and obtain a more comprehensive understanding of wireless communication systems.

  2. Based on the system characteristics used in 5G and B5G networks, S can use patch array antennas while U can use sector, log-periodic, and/or patch antenna [7,8,9,10,11, 58].

  3. Notice that RISs can be implemented using either passive or active elements. These surfaces are designed to enhance wireless communication systems by manipulating the propagation environment. The choice between passive and active RIS depends on various factors such as the specific application, energy constraints, system requirements, and cost considerations. Passive RIS may be suitable for static environments or applications where energy efficiency is critical, while active RIS provides greater flexibility and adaptability in dynamic scenarios. Based on these observations, we use passive RISs in our work [34, 35, 59].

  4. Due to the existence of term \(\Big ( \sum _{l=1}^{M} \sum _{k=1}^{G_l} \bar{a}_{ilk} \bar{b}_{lk} + \bar{c}_{isu} \Big ) ^2 \Big [(\alpha _\text {S}^\text {t})^2 + (\alpha _\text {U}^\text {r})^2 \Big ] P_\text {S}\) in denominator of (10), it is challenging to calculate OP and throughput of the considered communications. However, it is important to consider the case with ITH because of its practical characteristics in wireless communications.

  5. In the case of light-of-sight (LoS), \(\Omega\) is calculated as \(\Omega = - 21 \log (d) - 20 \log (f_c) + G_\text {tx} + G_\text {rx} -32.4\).

  6. It is essential to acknowledge that the computational complexity induced by multiple RISs and multiple antennas with ITH in multi-RIS-assisted MW communications is substantial. This complexity arises due to the considerably intricate formula derived in equation (24), surpassing the simplicity found in prior research [50, 54, 55]. Furthermore, this formula adeptly captures practical scenarios in multi-RIS-assisted MW communications with ITH and with TAS. The channel model, carrier frequency, and system parameters employed in this study are grounded in practical measurements, aligning with specific frequencies and path loss models recommended for 5G and B5G standards (as denoted in Eq. (14)). Notably, the carrier frequency normalization or exclusion of MW bands, as observed in previous works on RIS-aided wireless systems [50, 54, 55], renders their channel characteristics impractical and unsuitable for B5G networks.

  7. Besides considering antenna gains as constants, we can vary them to investigate the system behaviors. However, the antenna gains are often fixed because an increase in antenna gains will obviously improve the system performance [51, 61, 63].

  8. From the specific coordinates, the distance d between two communication nodes is formulated as \(d =\sqrt{(\hat{x}_i - \hat{x}_j)^2 + (\hat{y}_i - \hat{y}_j)^2}\) where \(i,j=\text {S}, \text {U}, \text {RIS}_1, \text {RIS}_2, \text {RIS}_3\) and \(i \ne j\).

  9. As can be seen in Table 4, the system parameters are from the practical measurements and experiments. Therefore, the behaviors of the considered communications achieved in this section will deeply reflect the behaviors of the wireless communications being deployed in B5G networks. Meanwhile, many previous works such as [2, 43, 48, 50, 53] normalized the system parameters by setting \(\Omega =1\), \(\sigma ^2 = 1\), and \(f_c =1\) Hz. Consequently, their results could not fully characterize the behaviors of practical wireless communications.

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Appendix

Appendix

In this appendix, all mathematical derivations are detailedly presented to derive the OP formula of the considered communications with TAS and ITH in (24).

Since \(\bar{c}_{su}\) is the single channel from S to U, its hth moment can be computed as [64]

$$\begin{aligned} \Delta _{\bar{c}_{su}}(h) \triangleq \mathbb {E}\{(\bar{c}_{su})^h\} = \int _{0}^{\infty } y^h f_{\bar{c}_{su}}(y) dy. \end{aligned}$$
(27)

After using (13), (27) becomes

$$\begin{aligned} \Delta _{\bar{c}_{su}}(h) = \frac{\Gamma (m_{su}+h/2)}{\Gamma (m_{su})} \Big ( \frac{m_{su}}{\Omega _{su}}\Big )^{-h/2}. \end{aligned}$$
(28)

From (28), the 1st and 2nd moments of \(\bar{c}_{su}\) are, respectively, given as

$$\begin{aligned} \Delta _{\bar{c}_{su}}(1)&=\frac{\Gamma (m_{su}+1/2)}{\Gamma (m_{su})} \sqrt{\frac{\Omega _{su}}{m_{su}}}, \end{aligned}$$
(29)
$$\begin{aligned} \Delta _{\bar{c}_{su}}(2)&= \Omega _{su}. \end{aligned}$$
(30)

Since \(\mathcal {X}_{lk} = \bar{a}_{lk} \bar{b}_{lk}\), its PDF is [65]

$$\begin{aligned} f_{\mathcal {X}_{lk}}(\rho ) = \int _{0}^{\infty } \frac{1}{y} f_{\bar{a}_{lk}} \Big (\frac{\rho }{y}\Big ) f_{\bar{b}_{lk}} (y) dy. \end{aligned}$$
(31)

Utilizing (13), (31) is now expressed as

$$\begin{aligned} \nonumber f_{\mathcal {X}_{lk}}(\rho ) =&\, \frac{4}{\Gamma (m_{b_l}) \Gamma (m_{a_l}) } \big (\frac{m_{b_l}}{ \Omega _{b_l}}\big )^{m_{b_l}} \big (\frac{m_{a_l}}{ \Omega _{a_l}}\big )^{m_{a_l}} \alpha ^{2 m_{a_l}-1} \\&\times \int _{0}^{\infty } y^{2 m_{b_l} - 2 m_{a_l} -1} \exp \big ( -\frac{\rho ^2 m_{a_l}}{\Omega _{a_l} y^2} - \frac{m_{b_l} y^2}{\Omega _{b_l}}\big ) dy. \end{aligned}$$
(32)

Applying [66, Eq. (3.478.4)], (32) becomes

$$\begin{aligned} \nonumber f_{\mathcal {X}_{lk}}(\rho ) =&\frac{4 }{\Gamma (m_{a_l}) \Gamma (m_{b_l}) } \Big (\frac{m_{a_l} m_{b_l} }{\Omega _{a_l} \Omega _{b_l} }\Big )^\frac{{m_{a_l} + m_{b_l}}}{2} \rho ^{ m_{a_l} + m_{b_l} -1} \\&\times \mathcal {K}_{m_{b_l} - m_{a_l}} \Bigg (2 \rho \sqrt{\frac{m_{a_l} m_{b_l} }{\Omega _{a_l} \Omega _{b_l} }} \Bigg ). \end{aligned}$$
(33)

Based on (33), the hth moment of \(\mathcal {X}_{lk}\) is calculated as

$$\begin{aligned} \Delta _{\mathcal {X}_{lk}}(h) \triangleq \mathbb {E}\{\mathcal {X}_{lk}^h\} = \int _{0}^{\infty } y^h f_{\mathcal {X}_{lk}}(y) dy. \end{aligned}$$
(34)

After utilizing [66, Eq. (6.561.16)], (34) becomes

$$\begin{aligned} \Delta _{\mathcal {X}_{lk}}(h) = \Big (\frac{m_{a_l} m_{b_l} }{\Omega _{a_l} \Omega _{b_l} }\Big )^\frac{-h}{2} \times \frac{\Gamma (m_{a_l}+h/2) \Gamma (m_{b_l}+h/2)}{\Gamma (m_{a_l}) \Gamma (m_{b_l})}. \end{aligned}$$
(35)

Based on (35), the specific moments of \(\Delta _{\mathcal {X}_{lk}}\) can be straightforwardly derived, i.e.,

$$\begin{aligned} \Delta _{\mathcal {X}_{lk}}(1)&= \sqrt{\frac{\Omega _{a_l} \Omega _{b_l} }{m_{a_l} m_{b_l} }} \times \frac{\Gamma (m_{a_l}+1/2) \Gamma (m_{b_l}+1/2)}{\Gamma (m_{a_l}) \Gamma (m_{b_l})}, \end{aligned}$$
(36)
$$\begin{aligned} \Delta _{\mathcal {X}_{lk}}(2)&= \frac{\Omega _{a_l} \Omega _{b_l} }{m_{a_l} m_{b_l} } \times \frac{\Gamma (m_{a_l}+1) \Gamma (m_{b_l}+1)}{\Gamma (m_{a_l}) \Gamma (m_{b_l})} = \Omega _{a_l} \Omega _{b_l}. \end{aligned}$$
(37)

From the above moments, the CDF of \(\mathcal {X}_{lk}\) is obtained as [51]

$$\begin{aligned} F_{\mathcal {X}_{lk}}(\rho ) \approx \frac{1}{\Gamma \Big ( \frac{[\Delta _{\mathcal {X}_{lk}}(1)]^2 }{\Delta _{\mathcal {X}_{lk}}(2) - [\Delta _{\mathcal {X}_{lk}}(1)]^2} \Big )} \gamma \Bigg ( \frac{[\Delta _{\mathcal {X}_{lk}}(1)]^2 }{\Delta _{\mathcal {X}_{lk}}(2) - [\Delta _{\mathcal {X}_{lk}}(1)]^2}, \frac{\Delta _{\mathcal {X}_{lk}}(1) \rho }{\Delta _{\mathcal {X}_{lk}}(2) - [\Delta _{\mathcal {X}_{lk}}(1)]^2} \Bigg ) \cdot \end{aligned}$$
(38)

It is because \(\mathcal {Y}_{l} = \sum _{k=1}^{G_l} \mathcal {X}_{lk}\), its CDF is formulated as [67]

$$\begin{aligned} F_{\mathcal {Y}_{l}}(\rho ) \approx \frac{1}{\Gamma \Big ( \frac{ [\Delta _{\mathcal {X}_{lk}}(1)]^2 G_l }{\Delta _{\mathcal {X}_{lk}}(2) - [\Delta _{\mathcal {X}_{lk}}(1)]^2} \Big )} \gamma \Bigg ( \frac{ [\Delta _{\mathcal {X}_{lk}}(1)]^2 G_l }{\Delta _{\mathcal {X}_{lk}}(2) - [\Delta _{\mathcal {X}_{lk}}(1)]^2}, \frac{\Delta _{\mathcal {X}_{lk}}(1) \rho }{\Delta _{\mathcal {X}_{lk}}(2) - [\Delta _{\mathcal {X}_{lk}}(1)]^2} \Bigg ) \cdot \end{aligned}$$
(39)

Now, the hth moment of \(\mathcal {Y}_{l}\) is formulated [68]

$$\begin{aligned} \nonumber \Delta _{\mathcal {Y}_{l}}(h) \triangleq \mathbb {E}\{\mathcal {Y}_{l}^h\} =&\sum _{h_1=0}^{h} \sum _{h_2=0}^{h_1} \cdots \sum _{h_{G_l -1}=0}^{h_{G_l -2}} {h\atopwithdelims ()h_1} {h_1 \atopwithdelims ()h_2} \cdots {h_{G_l -2} \atopwithdelims ()h_{G_l -1}} \\&\times \Delta _{\mathcal {X}_{l1}}(t -h_1) \Delta _{\mathcal {X}_{l2}}(h_1 -h_2) \cdots \Delta _{\mathcal {X}_{lG_l}}(h_{G_l -1}). \end{aligned}$$
(40)

On the other hand, since \({\mathcal {Z}}= \sum _{l=1}^{M} \mathcal {Y}_{l}\), its hth moment is also formulated as

$$\begin{aligned} \nonumber \Delta _{{\mathcal {Z}}}(h) \triangleq \mathbb {E}\{{\mathcal {Z}}^h\} =&\sum _{h_1=0}^{h} \sum _{h_2=0}^{h_1} \cdots \sum _{h_{M -1}=0}^{h_{M -2}} {t \atopwithdelims ()h_1} {h_1 \atopwithdelims ()h_2} \cdots {h_{M -2} \atopwithdelims ()h_{M -1}} \\&\times \Delta _{\mathcal {Y}_{1}}(t -h_1) \Delta _{\mathcal {Y}_{2}}(h_1 -h_2) \cdots \Delta _{\mathcal {Y}_{M}}(h_{M -1}). \end{aligned}$$
(41)

Now, based on (35), (40), and (41), the specific moments of \({\mathcal {Z}}\) can be derived, i.e.,

$$\begin{aligned} \Delta _{\mathcal {Z}}(1)&= \sum _{l=1}^{M} \sum _{k=1}^{G_l} \Delta _{\mathcal {X}_{lk}}(1) , \end{aligned}$$
(42)
$$\begin{aligned} \nonumber \Delta _{\mathcal {Z}}(2) =&\sum _{l=1}^{M} \Big [ \sum _{k=1}^{G_l} \Delta _{\mathcal {X}_{lk}}(2) +2 \sum _{k=1}^{G_l} \Delta _{\mathcal {X}_{lk}}(1) \sum _{k'=k+1}^{G_l} \Delta _{\mathcal {X}_{lk'}}(1) \Big ] \\&+ 2 \sum _{l=1}^{M} \Big [ \sum _{k=1}^{G_l} \Delta _{\mathcal {X}_{lk}}(1) \Big ] \sum _{l'=l+1}^{M} \Big [ \sum _{k=1}^{L_{l'}} \Delta _{\mathcal {X}_{l'k}}(1) \Big ] , \end{aligned}$$
(43)

where \(\Delta _{\mathcal {X}_{lk}}(1)\) and \(\Delta _{\mathcal {X}_{lk}}(2)\) are, respectively, given in (36) and (37).

Then, the hth moment of \({\mathcal {T}} = {\mathcal {Z}} + \bar{c}_{su}\) can be formulated as

$$\begin{aligned} \nonumber \Delta _{{\mathcal {T}}}(h)&\triangleq \mathbb {E}\{( {\mathcal {Z}} +\bar{c}_{su})^h\} = \mathbb {E}\left\{ \sum _{i=0}^{h} {h \atopwithdelims ()i} \bar{c}_{su}^i {\mathcal {Z}}^{h-i} \right\} \\&= \sum _{i=0}^{h} {h \atopwithdelims ()i} \Delta _{\bar{c}_{su}}(i) \Delta _{\mathcal {Z}}(h-i). \end{aligned}$$
(44)

Based on (44), the specific moments of \(\mathcal {T}\) can be derived, i.e.,

$$\begin{aligned} \Delta _\mathcal {T}(1)&= \Delta _{\mathcal {Z}}(1) + \Delta _{\bar{c}_{su}}(1) , \end{aligned}$$
(45)
$$\begin{aligned} \Delta _\mathcal {T}(2)&= \Delta _{\mathcal {Z}}(2) + \Delta _{\bar{c}_{su}}(2) + 2 \Delta _{\mathcal {Z}}(1) \Delta _{\bar{c}_{su}}(1) . \end{aligned}$$
(46)

Now, the CDF of \({\mathcal {T}}\) can be obtained from its moments [51], thus, we obtain

$$\begin{aligned} \nonumber F_{\mathcal {T}}(\rho )&= \frac{1}{\Gamma \Big ( \frac{[\Delta _\mathcal {T}(1)]^2 }{\Delta _\mathcal {T}(2) - [\Delta _\mathcal {T}(1)]^2} \Big )} \gamma \Bigg ( \frac{[\Delta _\mathcal {T}(1)]^2 }{\Delta _\mathcal {T}(2) - [\Delta _\mathcal {T}(1)]^2}, \frac{\Delta _\mathcal {T}(1) \rho }{\Delta _\mathcal {T}(2) - [\Delta _\mathcal {T}(1)]^2} \Bigg ) \\&= 1 - \frac{1}{\Gamma \Big ( \frac{[\Delta _\mathcal {T}(1)]^2 }{\Delta _\mathcal {T}(2) - [\Delta _\mathcal {T}(1)]^2} \Big )} \Gamma \Bigg ( \frac{[\Delta _\mathcal {T}(1)]^2 }{\Delta _\mathcal {T}(2) - [\Delta _\mathcal {T}(1)]^2}, \frac{\Delta _\mathcal {T}(1) \rho }{\Delta _\mathcal {T}(2) - [\Delta _\mathcal {T}(1)]^2} \Bigg ). \end{aligned}$$
(47)

Then, the OP from (23) is expressed as

$$\begin{aligned} \nonumber \mathcal {P}_\text {out}&= \Bigg [ \text {Pr} \Bigg \{\mathcal {T}^2< \frac{\sigma ^2_\text {U} \rho _\text {th}}{\Big ( 1 - \big [(\alpha _\text {S}^\text {t})^2 + (\alpha _\text {U}^\text {r})^2 \big ] \rho _\text {th} \Big ) P_\text {S}} \Bigg \} \Bigg ]^N \\ \nonumber&= \Bigg [ \text {Pr} \Bigg \{\mathcal {T} <\sqrt{\frac{\sigma ^2_\text {U} \rho _\text {th}}{\Big ( 1 - \big [(\alpha _\text {S}^\text {t})^2 + (\alpha _\text {U}^\text {r})^2 \big ] \rho _\text {th} \Big ) P_\text {S}}} \Bigg \} \Bigg ]^N \\&= \Bigg [F_{\mathcal {T}} \Bigg (\sqrt{\frac{\sigma ^2_\text {U} \rho _\text {th}}{\Big ( 1 - \big [(\alpha _\text {S}^\text {t})^2 + (\alpha _\text {U}^\text {r})^2 \big ] \rho _\text {th} \Big ) P_\text {S}}} \Bigg ) \Bigg ]^N. \end{aligned}$$
(48)

Applying (47), (48) is solved as

$$\begin{aligned} \mathcal {P}_\text {out} =&\Bigg [F_{\mathcal {T}} \Bigg (\sqrt{\frac{\sigma ^2_\text {U} \rho _\text {th}}{\Big ( 1 - \big [(\alpha _\text {S}^\text {t})^2 + (\alpha _\text {U}^\text {r})^2 \big ] \rho _\text {th} \Big ) P_\text {S}}} \Bigg ) \Bigg ]^N \nonumber \\ =&\Bigg [1 - \frac{1}{\Gamma \Big ( \frac{[\Delta _\mathcal {T}(1)]^2 }{\Delta _\mathcal {T}(2) - [\Delta _\mathcal {T}(1)]^2} \Big )} \end{aligned}$$
(49)
$$\begin{aligned}&\times \Gamma \Bigg ( \frac{[\Delta _\mathcal {T}(1)]^2 }{\Delta _\mathcal {T}(2) - [\Delta _\mathcal {T}(1)]^2}, \frac{\Delta _\mathcal {T}(1)}{\Delta _\mathcal {T}(2) - [\Delta _\mathcal {T}(1)]^2} \sqrt{\frac{\sigma ^2_\text {U} \rho _\text {th}}{\Big ( 1 - \big [(\alpha _\text {S}^\text {t})^2 + (\alpha _\text {U}^\text {r})^2 \big ] \rho _\text {th} \Big ) P_\text {S}}} \Bigg ) \Bigg ]^N. \end{aligned}$$
(50)

Utilizing the binomial theorem, the OP formula of the considered communications with TAS is derived as (24) in Theorem. The proof is now complete. \(\square\)

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Van Vinh, N. Transmit antenna selection for millimeter-wave communications using multi-RIS with imperfect transceiver hardware. Wireless Netw (2024). https://doi.org/10.1007/s11276-024-03754-w

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