SCIENCE CHINA Information Sciences, Volume 61, Issue 10: 102306(2018) https://doi.org/10.1007/s11432-017-9362-5

## Performance evaluation for underlay cognitive satellite-terrestrial cooperative networks

• AcceptedJan 8, 2018
• PublishedAug 9, 2018
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### Abstract

With the continuously increasing demand for broadband applications and services, underlay cognitive satellite-terrestrial networks, enabling to accommodate better wireless services within the scarce spectrum, have attracted tremendous attentions recently. In this network, satellite communications are allowed to operate in the frequency bands allocated to terrestrial networks under the interference constraints imposed by terrestrial network, which may lead to a performance degradation of the satellite network. To guarantee the performance of the primary terrestrial network as well as the secondary satellite network, we introduce the cooperation into cognitive satellite-terrestrial networks and investigate the performance of the new framework, i.e., cognitive satellite-terrestrial cooperative network (CSTCN). Specifically, by restricting the transmit power of satellite communications with interference power constraints imposed by terrestrial communications, we firstly obtain the received signal-to-interference-plus-noise ratio (SINR) of the considered network. Moreover, by employing themoment generating function (MGF) approach, closed-form expressions for symbol error rate (SER) and outage probability (OP) of the considered cognitive network are derived. The analytical results obtained in this paper can provide theoretical support for optimizing the performance of satellite-terrestrial networks.

### Acknowledgment

This work was supported by National Key RD Program of China (Grant No. 2016YF-B1200202), National Natural Science Foundation of China (Grant No. 61771365), Natural Science Foundation of Shaanxi Province (Grant No. 2017JZ022), Programme of Introducing Talents of Discipline to Universities (111 Project) (Grant No. B08038), EU H2020 RISE TESTBED Project (Grant No. 734325), and EPSRC TOUCAN Project (Grant No. EP/L020009/1).

### References

[1] Evans B, Werner M, Lutz E. Integration of satellite and terrestrial systems in future multimedia communications. IEEE Wirel Commun, 2005, 12: 72-80 CrossRef Google Scholar

[2] Sadek M, Aissa S. Personal satellite communication: technologies and challenges. IEEE Wirel Commun, 2012, 19: 28-35 CrossRef Google Scholar

[3] Ruan Y H, Li Y Z, Wang C X. Energy efficient adaptive transmissions in integrated satellite-terrestrial networks with SER constraints. IEEE Trans Wirel Commun, 2018, 17: 210-222 CrossRef Google Scholar

[4] Li H J, Yin H, Dong F H. Capacity upper bound analysis of the hybrid satellite terrestrial communication systems. IEEE Commun Lett, 2016, 20: 2402-2405 CrossRef Google Scholar

[5] Zhang J X, Evans B, Imran M A, et al. Green hybrid satellite terrestrial networks: fundamental trade-off analysis. In: Proceedings of IEEE Vehicular Technology Conference (VTC'16), Nanjing, 2016. Google Scholar

[6] Atri M K, Jindal S K. OSTBC transmission in shadowed-Rician land mobile satellite links. IEEE Trans Veh Technol, 2016, 65: 5771-5777 CrossRef Google Scholar

[7] Khan A H, Imran M A, Evans B G. Semi-adaptive beamforming for OFDM based hybrid terrestrial-satellite mobile system. IEEE Trans Wirel Commun, 2012, 11: 3424-3433 CrossRef Google Scholar

[8] Sithamparanathan K, de Nardis L, Di Benedetto M G, et al. Cognitive satellite terrestrial radios. In: Proceedings of IEEE Global Communications Conference (GLOBECOM'10), Miami, 2010. Google Scholar

[9] Ge X H, Tu S, Mao G Q. 5G ultra-dense cellular networks. IEEE Wirel Commun, 2016, 23: 72-79 CrossRef Google Scholar

[10] Wang C X, Wu S B, Bai L. Recent advances and future challenges for massive MIMO channel measurements and models. Sci China Inf Sci, 2016, 59: 021301 CrossRef Google Scholar

[11] Höyhtyä M, kyröläinen J, Hulkkonen A, et al. Application of cognitive radio techniques to satellite communication. In: Proceedings of IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN'12), Bellevue, 2012. 540--551. Google Scholar

[12] Sharma S K, Chatzinotas S, Ottersten B. Satellite cognitive communications: interference modeling and techniques selection. In: Proceedings of IEEE Advanced Satellite Multimedia Systems Conference (ASMS) and Signal Processing for Space Communications Workshop (SPSC), Baiona, 2012. 111--118. Google Scholar

[13] Haider F, Wang C X, Haas H. Spectral and energy efficiency analysis for cognitive radio networks. IEEE Trans Wirel Commun, 2015, 14: 2969-2980 CrossRef Google Scholar

[14] Icolari V, Guidotti A, Tarchi D, et al. An interference estimation technique for satellite cognitive radio systems. In: Proceedings of IEEE International Conference on Communications (ICC'15), London, 2015. 892--897. Google Scholar

[15] Kuang L L, Chen X, Jiang C X. Radio resource management in future terrestrial-satellite communication networks. IEEE Wirel Commun, 2017, 24: 81-87 CrossRef Google Scholar

[16] Ruan Y H, Li Y Z, Wang C X. Outage performance of integrated satellite-terrestrial networks with hybrid CCI. IEEE Commun Lett, 2017, 21: 1545-1548 CrossRef Google Scholar

[17] Lagunas E, Sharma S K, Maleki S. Resource allocation for cognitive satellite communications with incumbent terrestrial networks. IEEE Trans Cogn Commun Netw, 2015, 1: 305-317 CrossRef Google Scholar

[18] Guidolin F, Nekovee M, Badia L, et al. A cooperative scheduling algorithm for the coexistence of fixed satellite services and 5G cellular network. In: Proceedings of IEEE International Conference on Communications (ICC'15), London, 2015. 1322--1327. Google Scholar

[19] Zhang W S, Wang C X, Chen D. Energy-spectral efficiency tradeoff in cognitive radio networks. IEEE Trans Veh Technol, 2016, 65: 2208-2218 CrossRef Google Scholar

[20] An K, Ouyang J, Lin M. Outage analysis of multi-antenna cognitive hybrid satellite-terrestrial relay networks with beamforming. IEEE Commun Lett, 2015, 19: 1157-1160 CrossRef Google Scholar

[21] Bhatnagar M R, Arti M K. Performance analysis of AF based hybrid satellite-terrestrial cooperative network over generalized fading channels. IEEE Commun Lett, 2013, 17: 1912-1915 CrossRef Google Scholar

[22] Sreng S, Escrig B, Boucheret M L. Exact symbol error probability of hybrid/integrated satellite-terrestrial cooperative network. IEEE Trans Wirel Commun, 2013, 12: 1310-1319 CrossRef Google Scholar

[23] Ruan Y H, Li Y Z, Zhang R, et al. Performance analysis of hybrid satellite-terrestrial cooperative networks with distributed alamouti code. In: Proceedings of IEEE Vehicular Technology Conference (VTC'16), Nanjing, 2016. Google Scholar

[24] Chun L. A statistical model for a land mobile satellite link. IEEE Trans Veh Technol, 1985, 34: 122-127 CrossRef Google Scholar

[25] Peppas K P. Accurate closed-form approximations to generalised-K sum distributions and applications in the performance analysis of equal-gain combining receivers. IET Commun, 2011, 5: 982-989 CrossRef Google Scholar

[26] Ruan Y H, Li Y Z, Wang C X, et al. Effective capacity analysis for underlay cognitive satellite-terrestrial networks. In: Proceedings of IEEE International Conference on Communications (ICC'17), Paris, 2017. Google Scholar

[27] Gradshteyn I S, Ryzhik I M. Table of Integrals, Series, and Products. 6th ed. Orlando: Academic Press, 2000. Google Scholar

[28] Simon M K, Alouini M S. Digital Communication over Fading Channels. Hoboken: John Wiley & Sons, 2005. Google Scholar

[29] Simon M K, Alouini M S, Ko Y C. Outage probability of diversity systems over generalized fading channels. IEEE Trans Commun, 2000, 48: 1783-1787 CrossRef Google Scholar

[30] Adamchik V S, Marichev O I. The algorithm for calculating integrals of hypergeometric type functions and its realization in reduce systems. In: Proceedings of International Conference Symposium on Algebraic Computing, Tokyo, 1990. 212--224. Google Scholar

[31] Ikki S S, Aissa S. Performance analysis of two-way amplify-and-forward relaying in the presence of co-channel interferences. IEEE Trans Commun, 2012, 60: 933-939 CrossRef Google Scholar

[32] Mckay M R, Zanella A, Collings I B. Error probability and SINR analysis of optimum combining in rician fading. IEEE Trans Commun, 2009, 57: 676-687 CrossRef Google Scholar

• Figure 1

(Color online) System model of the underlaying CSTCN.

• Figure 2

(Color online) SER versus $\bar\gamma_{\rm~th}$ with QPSK for various shadowing cases ($\bar\gamma_{\rm~b}$ = 2 dB).

• Figure 3

(Color online) OP versus $\bar\gamma_{\rm~th}$ for various shadowing cases ($\bar\gamma_{\rm~b}$ = 2 dB).

• Figure 4

(Color online) SER versus $\bar\gamma_{\rm~th}$ for various $\bar\gamma_{\rm~b}$ with AS-FHS shadowing case ($m_{\rm~rd}$ = 3).

• Figure 5

(Color online) OP versus $\bar\gamma_{\rm~b}$ for various $\bar\gamma_{\rm~th}$ and shadowing cases ($m_{\rm~rd}$ = 3).

• Figure 6

(Color online) OP versus $\bar\gamma_{\rm~b}$ for various $\bar\gamma_{\rm~th}$ and $m_{\rm~rd}$ with ILS-AS shadowing.

• Table 1   Channel parameters for generalized-$K$ fading
 Shadowing $\sigma~$ ${\varphi_i}$ ${\varepsilon_i}$ Infrequent light shadowing (ILS) 0.115 75.1155 3 Average shadowing (AS) 0.345 7.9115 2 Frequent heavy shadowing (FHS) 0.806 1.0931 1

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