Advanced receivers for high data rate mobile communications

Improving the spectral efficiency is a key issue in the future wireless communication systems since the spectrum is a scarce resource. Both the number of users as well the demanded data rates are increasing all the time. Furthermore, in mobile communications the wireless link is required to be reliable even when the mobile is in a fast moving vehicle. Using Multiple-Input Multiple-Output (MIMO) antennas is a well known technique to provide higher spectral efficiency as well as better link reliability. Additionally, higher order modulation methods can be used to provide higher data rates. In order to benefit from these enhancements in practise, sophisticated signal processing methods as well as accurate estimates of time-varying wireless channel parameters are needed. This thesis addresses the problem of designing multi-antenna receivers in high data rate systems. The case of multiple transmit antennas is also considered. System specific features of High Speed Downlink Packet Access (HSDPA) which is part of 3rd generation (3G) Wideband Code Division Multiple Access (WCDMA) evolution are exploited in channel estimation methods and in MIMO receiver design. Additionally, complexity reduction methods for Minimum Mean Square Error (MMSE) equalization are addressed. Blind channel estimation methods are spectrally efficient, since no extra resources are needed for pilot signals. However, in mobile communications accurate estimates are needed also in fast fading channels. Consequently, semi-blind channel estimation methods where the receiver combines blind and pilot based channel estimation are an appealing alternative. In this thesis blind and semi-blind channel estimation methods based on knowledge of multiple spreading codes are derived. A novel semi-blind combining scheme for code multiplexed pilot signal and blind estimation is proposed. Another important factor in receiver design criteria is the structure of interference in the received signals. Interference mitigation techniques in MIMO systems have been shown to be potential methods for providing improved performance. A chip level inter-antenna interference cancellation method has been developed in this thesis for HSDPA. Furthermore, this multi-stage ordered interference canceler is combined with the semi-blind channel estimation scheme to enhance the system performance further.Langattomassa tiedonsiirrossa radiospektrin tehokas käyttö on tulevaisuuden suuria haasteita. Taajuuksia on käytössä vain rajoitetusti, kun taas käyttäjien määrä sekä vaaditut siirtonopeudet kasvavat jatkuvasti. Lisäksi langattomien yhteyksien on toimittava luotettavasti myös nopeasti liikkuvissa kulkuneuvoissa. Moniantennijärjestelmät, joissa on useita antenneita sekä tukiasemissa että päätelaitteissa mahdollistavat radiospektrin tehokkaamman käytön sekä parantavat yhteyksien laatua. Tiedonsiirtonopeutta voidaan myös kasvattaa erilaisilla modulaatiotekniikoilla. Hyötyjen saavutamiseksi käytännössä tarvitaan sekä kehittyneitä vastaanotinrakenteita että tarkkoja estimaatteja aikamuuttuvasta radiokanavasta. Tässä työssä on kehitetty vastaanotinrakenteita ja kanavan estimointimenetelmiä kolmannen sukupolven (3G) nopeiden datayhteyksien (HSPA) järjestelmissä. Työssä on johdettu menetelmiä, jotka hyödyntävät HSPA järjestelmien erikoispiirteitä tehokkaasti. Lisäksi on kehitetty laskennallisesti tehokkaita menetelmiä vastaanottimien signaalinkäsittelyyn. Ns. sokeat menetelmät mahdollistavat taajuuskaistan tehokkaan käytön, koska ne eivät vaadi tunnettuja harjoitussignaaleja. Mobiileissa tietolikennejärjestelmissä radiokanava saattaa kuitenkin muuttua hyvin nopeasti, jonka vuoksi kanavan estimoinnissa on tyypillisesti hyödynnetty tunnettua pilottisignaalia. Yhdistämällä pilottipohjainen ja sokea kanavaestimointimenetelmä, voidaan saavuttaa molempien menetelmien edut. Tässä työssä kehitettiin sokeita kanavaestimointimenetelmiä, jotka hyödyntävät useita tunnettuja hajoituskoodeja. Sokean ja koodijakoiseen pilottisignaaliin pohjautuvien kanavan estimaattien yhdistämiseksi kehitettiin uusi menetelmä. Signaalin laatua ja siten vastaanottimen suorituskykyä voidaan langattomissa järjestelmissä parantaa vaimentamalla interferenssiä eli häiriöitä. Vastaanottimen toimintaa voidaan tehostaa oleellisesti, jos häiriösignaalin rakenne tunnetaan. Käytettäessä useampaa lähetysantennia HSPA järjestelmissä vastaanotetussa signaalissa olevia häiriötä voidaan kumota usealla eri tasolla. Tässä työssä on kehitetty chippitasolla häiriöitä kumoava vastaanotinrakenne, joka hyödyntää HSPA järjestelmän ominaisuuksia. Vastaanottimen suorituskykyä on edelleen parannettu yhdistämällä se aiemmin esitettyyn puolisokeaan kanavan estimointimenetelmään.reviewe

Advanced receiver structures for mobile MIMO multicarrier communication systems

Beyond third generation (3G) and fourth generation (4G) wireless communication systems are targeting far higher data rates, spectral efficiency and mobility requirements than existing 3G networks. By using multiple antennas at the transmitter and the receiver, multiple-input multiple-output (MIMO) technology allows improving both the spectral efficiency (bits/s/Hz), the coverage, and link reliability of the system. Multicarrier modulation such as orthogonal frequency division multiplexing (OFDM) is a powerful technique to handle impairments specific to the wireless radio channel. The combination of multicarrier modulation together with MIMO signaling provides a feasible physical layer technology for future beyond 3G and fourth generation communication systems. The theoretical benefits of MIMO and multicarrier modulation may not be fully achieved because the wireless transmission channels are time and frequency selective. Also, high data rates call for a large bandwidth and high carrier frequencies. As a result, an important Doppler spread is likely to be experienced, leading to variations of the channel over very short period of time. At the same time, transceiver front-end imperfections, mobility and rich scattering environments cause frequency synchronization errors. Unlike their single-carrier counterparts, multi-carrier transmissions are extremely sensitive to carrier frequency offsets (CFO). Therefore, reliable channel estimation and frequency synchronization are necessary to obtain the benefits of MIMO OFDM in mobile systems. These two topics are the main research problems in this thesis. An algorithm for the joint estimation and tracking of channel and CFO parameters in MIMO OFDM is developed in this thesis. A specific state-space model is introduced for MIMO OFDM systems impaired by multiple carrier frequency offsets under time-frequency selective fading. In MIMO systems, multiple frequency offsets are justified by mobility, rich scattering environment and large angle spread, as well as potentially separate radio frequency - intermediate frequency chains. An extended Kalman filter stage tracks channel and CFO parameters. Tracking takes place in time domain, which ensures reduced computational complexity, robustness to estimation errors as well as low estimation variance in comparison to frequency domain processing. The thesis also addresses the problem of blind carrier frequency synchronization in OFDM. Blind techniques exploit statistical or structural properties of the OFDM modulation. Two novel approaches are proposed for blind fine CFO estimation. The first one aims at restoring the orthogonality of the OFDM transmission by exploiting the properties of the received signal covariance matrix. The second approach is a subspace algorithm exploiting the correlation of the channel frequency response among the subcarriers. Both methods achieve reliable estimation of the CFO regardless of multipath fading. The subspace algorithm needs extremely small sample support, which is a key feature in the face of time-selective channels. Finally, the Cramér-Rao (CRB) bound is established for the problem in order to assess the large sample performance of the proposed algorithms.reviewe

Review of Recent Trends

This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe

Signal Processing and Learning for Next Generation Multiple Access in 6G

Wireless communication systems to date primarily rely on the orthogonality of resources to facilitate the design and implementation, from user access to data transmission. Emerging applications and scenarios in the sixth generation (6G) wireless systems will require massive connectivity and transmission of a deluge of data, which calls for more flexibility in the design concept that goes beyond orthogonality. Furthermore, recent advances in signal processing and learning have attracted considerable attention, as they provide promising approaches to various complex and previously intractable problems of signal processing in many fields. This article provides an overview of research efforts to date in the field of signal processing and learning for next-generation multiple access, with an emphasis on massive random access and non-orthogonal multiple access. The promising interplay with new technologies and the challenges in learning-based NGMA are discussed

Enhanced Spectrum Sensing Techniques for Cognitive Radio Systems

Due to the rapid growth of new wireless communication services and applications, much attention has been directed to frequency spectrum resources. Considering the limited radio spectrum, supporting the demand for higher capacity and higher data rates is a challenging task that requires innovative technologies capable of providing new ways of exploiting the available radio spectrum. Cognitive radio (CR), which is among the core prominent technologies for the next generation of wireless communication systems, has received increasing attention and is considered a promising solution to the spectral crowding problem by introducing the notion of opportunistic spectrum usage. Spectrum sensing, which enables CRs to identify spectral holes, is a critical component in CR technology. Furthermore, improving the efficiency of the radio spectrum use through spectrum sensing and dynamic spectrum access (DSA) is one of the emerging trends. In this thesis, we focus on enhanced spectrum sensing techniques that provide performance gains with reduced computational complexity for realistic waveforms considering radio frequency (RF) impairments, such as noise uncertainty and power amplifier (PA) non-linearities. The first area of study is efficient energy detection (ED) methods for spectrum sensing under non-flat spectral characteristics, which deals with relatively simple methods for improving the detection performance. In realistic communication scenarios, the spectrum of the primary user (PU) is non-flat due to non-ideal frequency responses of the devices and frequency selective channel conditions. Weighting process with fast Fourier transform (FFT) and analysis filter bank (AFB) based multi-band sensing techniques are proposed for overcoming the challenge of non-flat characteristics. Furthermore, a sliding window based spectrum sensing approach is addressed to detect a re-appearing PU that is absent in one time and present in other time. Finally, the area under the receiver operating characteristics curve (AUC) is considered as a single-parameter performance metric and is derived for all the considered scenarios. The second area of study is reduced complexity energy and eigenvalue based spectrum sensing techniques utilizing frequency selectivity. More specifically, novel spectrum sensing techniques, which have relatively low computational complexity and are capable of providing accurate and robust performance in low signal-to-noise ratio (SNR) with noise uncertainty, as well as in the presence of frequency selectivity, are proposed. Closed-form expressions are derived for the corresponding probability of false alarm and probability of detection under frequency selectivity due the primary signal spectrum and/or the transmission channel. The offered results indicate that the proposed methods provide quite significant saving in complexity, e.g., 78% reduction in the studied example case, whereas their detection performance is improved both in the low SNR and under noise uncertainty. Finally, a new combined spectrum sensing and resource allocation approach for multicarrier radio systems is proposed. The main contribution of this study is the evaluation of the CR performance when using wideband spectrum sensing methods in combination with water-filling and power interference (PI) based resource allocation algorithms in realistic CR scenarios. Different waveforms, such as cyclic prefix based orthogonal frequency division multiplexing (CP-OFDM), enhanced orthogonal frequency division multiplexing (E-OFDM) and filter bank based multicarrier (FBMC), are considered with PA nonlinearity type RF impairments to see the effects of spectral leakage on the spectrum sensing and resource allocation performance. It is shown that AFB based spectrum sensing techniques and FBMC waveforms with excellent spectral containment properties have clearly better performance compared to the traditional FFT based spectrum sensing techniques with the CP-OFDM. Overall, the investigations in this thesis provide novel spectrum sensing techniques for overcoming the challenge of noise uncertainty with reduced computational complexity. The proposed methods are evaluated under realistic signal models