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Outage Performance for Relaying Aided Non-orthogonal Multiple Access

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Recent Trends in Intelligent Computing, Communication and Devices

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1006))

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Abstract

Non-orthogonal multiple access is the key technique of the fifth-generation wireless communication. In this paper, we investigate the outage performance of NOMA-based downlink amplify-and-forward half-duplex relaying networks. The closed-form representations of exact outage performance are attained. Simulation results indicate that the concluded result is in excellent agreement with the Monte Carlo simulation.

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Acknowledgements

This work was supported by Scientific Research Common Program of Beijing Municipal Commission of Education under Grant No. KM201510009008 and Scientific Research Foundation of North China University of Technology.

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Correspondence to Jinhong Fan .

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Appendices

Appendix 1

Proof of Theorem 1

The outage probability of D1 is:

$$P_{\text{out}}^{1} = \left[ {1 - P\left( {\gamma_{s1 \to 2} \ge \gamma_{\text{th2}} ,\gamma_{s1} \ge \gamma_{\text{th1}} } \right)} \right] \times \left[ {1 - P\left( {\gamma_{R1 \to 2} \ge \gamma_{{{\text{th}}2}} ,\gamma_{R1} \ge \gamma_{\text{th1}} } \right)} \right]$$

and assumed that \(J_{1} = 1 - P\left( {\gamma_{s1 \to 2} \ge \gamma_{\text{th2}} ,\gamma_{s1} \ge \gamma_{\text{th1}} } \right)\) and \(J_{2} = \left[ {1 - P\left( {\gamma_{R1 \to 2} \ge \gamma_{\text{th2}} ,\gamma_{R1} \ge \gamma_{\text{th1}} } \right)} \right]\) where J1 can be solved as

$$\begin{aligned} J_{1} & = 1 - P\left( {\gamma_{s1 \to 2} \ge \gamma_{\text{th2}} } \right)P\left( {\gamma_{s1} \ge \gamma_{\text{th1}} } \right) \\ & = 1 - P\left( {\frac{{\left| {g_{1} } \right|^{2} a_{2} \gamma }}{{\left| {g_{1} } \right|^{2} a_{1} \gamma + 1}} \ge \gamma_{\text{th2}} } \right)P\left( {\left| {g_{1} } \right|^{2} a_{1} \gamma \ge \gamma_{\text{th1}} } \right) \\ & = 1 - P\left( {\left| {g_{1} } \right|^{2} \ge \frac{{\gamma_{\text{th2}} }}{{\gamma \left( {a_{2} - a_{1} \gamma_{\text{th2}} } \right)}} = \varepsilon } \right)P\left( {\left| {g_{1} } \right|^{2} \ge \frac{{\gamma_{\text{th1}} }}{{a_{1} \gamma }} = \beta } \right) \\ & = 1 - P\left[ {\left| {g_{1} } \right|^{2} \ge \hbox{max} \left( {\varepsilon ,\beta } \right)\underline{\underline{\Delta }} \theta } \right] \\ & = P\left( {\left| {g_{1} } \right|^{2} \le \theta } \right) = 1 - \exp \left( { - \frac{2\theta }{{\Omega_{1} }}} \right) \\ \end{aligned}$$
(15)

Now, J2 can be solved as

$$\begin{aligned} J_{2} & = 1 - P\left( {\gamma_{R1 \to 2} \ge \gamma_{\text{th2}} } \right)P\left( {\gamma_{R1} \ge \gamma_{\text{th1}} } \right) \\ & = 1 - P\left( {\frac{{a_{2} \gamma^{2} \left| {g_{r,1} } \right|^{2} \left| {g_{r} } \right|^{2} }}{{a_{1} \gamma^{2} \left| {g_{r,1} } \right|^{2} \left| {g_{r} } \right|^{2} + \gamma \left( {\left| {g_{r,1} } \right|^{2} + \left| {g_{r} } \right|^{2} } \right) + 1}} \ge \gamma_{\text{th2}} } \right)\\ & \quad \,\,P\left( {\frac{{a_{1} \gamma^{2} \left| {g_{r,1} } \right|^{2} \left| {g_{r} } \right|^{2} }}{{\gamma \left( {\left| {g_{r,1} } \right|^{2} + \left| {g_{r} } \right|^{2} } \right) + 1}} \ge \gamma_{\text{th1}} } \right) \\ & = 1 - P\left( {\left| {g_{r} } \right|^{2} \ge \frac{{\theta \left( {1 + \gamma \left| {g_{r,1} } \right|^{2} } \right)}}{{\left| {g_{r,1} } \right|^{2} - \theta }},\left| {g_{r,1} } \right|^{2} \ge \theta } \right) \\ & = 1 - \int\limits_{\theta }^{\infty } {\frac{1}{{\Omega_{r,1} }}} \exp \left( { - \frac{y}{{\Omega_{r,1} }}} \right)\int\limits_{{\frac{{\theta \left( {1 + \gamma y} \right)}}{y - \theta }}}^{\infty } {\frac{1}{{\Omega_{r} }}} \exp \left( { - \frac{x}{{\Omega_{r} }}} \right){\text{d}}x{\text{d}}y \\ & = 1 - \exp \left( { - \theta \left( {\frac{1}{{\Omega_{r,1} }} + \frac{1}{{\sigma_{r}^{2} }}} \right)} \right)\sqrt {\frac{{4\theta \left( {1 + \gamma \theta } \right)}}{{\gamma\Omega_{r,1}\Omega_{r} }}} K_{1} \left( {\sqrt {\frac{{4\theta \left( {1 + \gamma \theta } \right)}}{{\gamma\Omega_{r,1}\Omega_{r} }}} } \right) \\ \end{aligned}$$
(16)

Equation (16) is obtained with the aid [13] [(3.324.1)]. And substituting (15) and (16) into (11).

The closed-form representation of the outage performance of D1 is

$$\begin{aligned} P_{\text{out}}^{1} & = \left( {1 - \exp \left( { - \frac{2\theta }{{\Omega_{1} }}} \right)} \right) \\ & \quad \,\,\left\{ {1 - \exp \left( { - \theta \left( {\frac{1}{{\Omega_{r,1} }} + \frac{1}{{\Omega_{r} }}} \right)} \right)\sqrt {\frac{{4\theta \left( {1 + \gamma \theta } \right)}}{{\gamma\Omega_{r,1}\Omega_{r} }}} K_{1} \left( {\sqrt {\frac{{4\theta \left( {1 + \gamma \theta } \right)}}{{\gamma\Omega_{r,1}\Omega_{r} }}} } \right)} \right\} \end{aligned}$$

Appendix 2

Proof of Theorem 2

The outage probability of D2 is:

$$P_{\text{out}}^{2} = P\left( {\gamma_{R2} < \gamma_{\text{th2}} } \right)$$

and

$$\begin{aligned} P_{\text{out}}^{2} & = P\left( {\gamma_{R2} < \gamma_{\text{th2}} } \right) \\ & = P\left( {\left| {g_{r,2} } \right|^{2} < \varepsilon } \right) + P\left\{ {\left| {g_{r} } \right|^{2} < (\varepsilon /r)\left( {\gamma \left| {g_{r,2} } \right|^{2} { + 1}} \right)/\left( {\left| {g_{r,2} } \right|^{2} - \varepsilon } \right),\left| {g_{r,2} } \right|^{2} > \varepsilon } \right\} \\ & = \int\limits_{0}^{\varepsilon } {f_{{\left| {g_{r,2} } \right|^{2} }} \left( x \right)} {\text{d}}x + \int\limits_{\varepsilon }^{\infty } {f_{{\left| {g_{r,2} } \right|^{2} }} } \left( x \right){\text{d}}x\int\limits_{0}^{{\frac{{\varepsilon \left( {1 + \gamma x} \right)}}{{\gamma \left( {x - \varepsilon } \right)}}}} {f_{{\left| {g_{r} } \right|^{2} }} } \left( y \right){\text{d}}y \\ & = 1 - \frac{1}{{\Omega_{r,2} }}\exp \left( { - \varepsilon \left( {\frac{1}{{\Omega_{r} }} + \frac{1}{{\Omega_{r,2} }}} \right)} \right)\int\limits_{\varepsilon }^{\infty } {\exp \left( { - \frac{x - \varepsilon }{{\Omega_{r,2} }}} \right)\exp \left( { - \frac{{\varepsilon \left( {1 + \varepsilon \gamma } \right)}}{{\Omega_{r} \gamma \left( {x - \varepsilon } \right)}}} \right){\text{d}}x} \\ & = 1 - \frac{1}{{\Omega_{r,2} }}\exp \left( { - \varepsilon \left( {\frac{1}{{\Omega_{r} }} + \frac{1}{{\Omega_{r,2} }}} \right)} \right)\int\limits_{0}^{\infty } {\exp \left( { - \frac{y}{{\Omega_{r,2} }}} \right)\exp \left( { - \frac{{\varepsilon \left( {1 + \varepsilon \gamma } \right)}}{{\Omega_{r} \gamma y}}} \right){\text{d}}y} \\ & = 1 - \frac{1}{{\Omega_{r,2} }}\exp \left( { - \varepsilon \left( {\frac{1}{{\Omega_{r} }} + \frac{1}{{\Omega_{r,2} }}} \right)} \right)\int\limits_{0}^{\infty } {\exp \left( { - \frac{{4\varepsilon \left( {1 + \varepsilon \gamma } \right)}}{{\frac{{\Omega_{r} \gamma }}{4y}}} - \frac{y}{{\Omega_{r,2} }}} \right){\text{d}}y} \\ & = 1 - \exp \left( { - \varepsilon \left( {\frac{1}{{\Omega_{r} }} + \frac{1}{{\Omega_{r,2} }}} \right)} \right)\frac{1}{{\Omega_{r,2} }}\sqrt {\frac{{4\varepsilon \left( {1 + \varepsilon \gamma } \right)\Omega_{r,2} }}{{\Omega_{r} \gamma }}} \,K_{1} \left( {\sqrt {\frac{{4\varepsilon \left( {1 + \varepsilon \gamma } \right)}}{{\Omega_{r,2}\Omega_{r} \gamma }}} } \right) \\ & = 1 - \exp \left( { - \varepsilon \left( {\frac{1}{{\Omega_{r} }} + \frac{1}{{\Omega_{r,2} }}} \right)} \right)\sqrt {\frac{{4\varepsilon \left( {1 + \varepsilon \gamma } \right)}}{{\Omega_{r,2}\Omega_{r} \gamma }}}\ K_{1} \left( {\sqrt {\frac{{4\varepsilon \left( {1 + \varepsilon \gamma } \right)}}{{\Omega_{r,2}\Omega_{r} \gamma }}} } \right) \\ \end{aligned}$$
(17)

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Fan, J., He, L. (2020). Outage Performance for Relaying Aided Non-orthogonal Multiple Access. In: Jain, V., Patnaik, S., Popențiu Vlădicescu, F., Sethi, I. (eds) Recent Trends in Intelligent Computing, Communication and Devices. Advances in Intelligent Systems and Computing, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-9406-5_88

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