Superimposed training for channel estimation in next-generation wireless multicarrier techniques

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dc.contributor.advisor Fernández-Getino García, María Julia Estrada Jiménez, Juan Carlos 2021-01-20T11:34:25Z 2021-01-20T11:34:25Z 2019-11 2019-11-08
dc.description Mención Internacional en el título de doctor
dc.description.abstract In this thesis, we propose novel superimposed training (ST) techniques for channel estimation for future wireless systems for 5G and beyond. ST is a promising technique that permits to obtain channel state information in a way that it can provide higher spectral e_ciency compared with dedicated pilot proposals at the cost of increasing the channel estimation error. In this context, a new proposal called partial-data superimposed training (PDST) is addressed for orthogonal frequency division multiplexing (OFDM) systems. The novelty of PDST is that incorporates an additional power control factor that, unlike previous proposals, allows to improve performance with an accurate control of data and pilot interference. Based on this proposal the channel estimation error is derived. The signal-to-interference and noise ratio (SINR) and average channel capacity are later introduced. The partial superimposition can overcome classical overlay schemes reducing the number of resources a_ected by the superimposition. Secondly, the channel estimation performance of a promising multicarrier technique known as _lterbank multicarrier o_set quadrature amplitude modulation (FBMCOQAM) is evaluated. In this contribution, we model the introduction of a superimposed training sequence in an FBMC-OQAM system. Due to the superimposition new parameters appear in the formulation known as intrinsic interference and data interference. An analytical expression for the channel estimation error, which _ts with the simulation results, is depicted. Then, the SINR and its average channel capacity expressions are presented. Furthermore, the power allocation factor that maximizes the spectral e_ciency is found. It is shown that this proposal overcomes the performance of FBMC-OQAM with pilot symbol assisted modulation (PSAM) and other multicarrier techniques as OFDM with PSAM and ST. Finally, the channel estimation in a promising technology known as visible light communication (VLC) is analyzed. In this proposal, we model a VLC scenario where ST is used for channel estimation. The multicarrier technique DC-o_set OFDM is taken into account to adapt the electrical signal to the optical one. Then, multiple input single output (MISO) is considered to be used as the most adequate spatial multiplexing technique to work with VLC. In this novel technique an extensive analysis is done for deduction of the channel estimation error, SINR and spectral e_ciency. Simulation results validate the performance of each proposal in a quasi stationary environment compared with PSAM-based channel estimation techniques. High spectral e_ciency and data rate can be expected of implementing these proposals which successfully could satisfy the new data-rate requirements. All of these proposals consider multicarrier techniques and novel technologies to be used in 5G and beyond systems thus o_ering new lines of investigation.
dc.language.iso eng
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.title Superimposed training for channel estimation in next-generation wireless multicarrier techniques
dc.type doctoralThesis
dc.subject.eciencia Telecomunicaciones
dc.rights.accessRights openAccess Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan Carlos
dc.description.responsability Presidente: Atilio Manuel Da Silva Gameiro.- Secretario: Matilde Pilar Sánchez Fernández.- Vocal: José Francisco París Ángel
dc.contributor.departamento Universidad Carlos III de Madrid.
dc.contributor.departamento Universidad Carlos III de Madrid. Departamento de Teoría de la Señal
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