Cognitive Antenna System for Sustainable Adaptive Radio Interfaces
Communication systems are usually implemented on a heterogeneous infrastructure and must operate in environments with accelerated dynamics. Adaptation is thus a key feature of such a system. Long-term, sustainable, adaptive solutions did not receive much attention in the design phase of wireless communication systems. With the advent of LTE, which was designed as a highly flexible radio interface—created to evolve—there is room for disruptive solutions to be put in place. A new approach for the receiver is proposed, where the antenna takes an active role in characterising and eventually learning the operation environment. The proposed solution—a Cognitive Antenna System (CAS), is based on two main mechanisms that we called antenna vision (AV) and signal fishing (SF). In the core cognitive cycle ‘observe-decide-act’ we aim to improve the ‘observe’ part, which critically influences the whole decision process. The SF and AV mechanisms bring a set of advantages: higher received SNR, no additional noise, higher AoA estimation accuracy.
KeywordsSustainable radio interface adaptation Antenna vision Signal fishing Cognitive antenna system
This paper was supported by CNCSIS–UEFISCDI, Romania, PD, project number 637/2010.
This work was also supported by the project “Develop and support multidisciplinary postdoctoral programs in primordial technical areas of national strategy of the research—development—innovation” 4D-POSTDOC, contract nr. POSDRU/89/1.5/S/52603, project co-funded from European Social Fund through Sectorial Operational Program Human Resources 2007-2013.
- 1.Mucchi L, Claudia Staderini J, Kyosti YP (2007) Modified spatial channel model for MIMO wireless systems. EURASIP J Wirel Comm Netw 2007:1–7Google Scholar
- 2.Crisan N, Cremene LC (2009) Antenna-based signal fishing, the fifth international conference on wireless and mobile communications—ICWMC’09, pp152–156, IEEE Computer Society Press, CannesGoogle Scholar
- 4.3GPP TS36.300 Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (E-UTRAN), Overall description, (Stage 2 Release 8)Google Scholar
- 5.Dahlman E et al (2008) 3G evolution: HSPA and LTE for mobile broadband, 2nd edn., Academic Press, Salt Lake CityGoogle Scholar
- 6.Stefania Sesia I, Baker TM (eds) (2009) LTE—the UMTS long term evolution. Wiley, New York, ChGoogle Scholar
- 7.Parkvall S, Astely D (2009) The evolution of LTE towards IMT-advanced. J Commun 4(3):146–154Google Scholar
- 9.Crişan N, Cremene LC, Cremene M (2011) Software components for signal fishing based on GA element position optimizer. Int J Comput Commun Control 6(1):63–71, CCC Publications, OradeaGoogle Scholar
- 10.Tuncer E, Friedlander B (2009) Classical and modern direction of arrival estimation, Elsevier, Academic Press, AmsterdamGoogle Scholar
- 11.Rübsamen M, Gershman AB (2008) Root-MUSIC based direction-of-arrival estimation methods for arbitrary non-uniform arrays. In: Proceedings ICASSP, pp 2317–2320Google Scholar
- 12.Rübsamen M, Gershman AB (2009) Direction-of-arrival estimation for non-uniform sensor arrays: from manifold separation to Fourier domain MUSIC methods. IEEE Trans Signal Process 57(2):588–599Google Scholar