Slepian-based serial estimation of time-frequency variant channels for MIMO-OFDM systems

This paper proposes a low-complexity two dimensional channel estimator for MIMO-OFDM systems derived from a time-frequency variant channel estimator previously proposed. The estimator exploits both time and frequency correlations of the wireless channel via use of Slepian-basis expansions. The computational saving comes from replacing a two-dimensional Slepian-basis expansion with two serially concatenated one-dimensional Slepian-basis expansions. Performance in terms of Normalized Mean Square Error (NMSE) vs. Signal-to-Noise Ratio (SNR) have been analyzed via numerical simulations and compared with the original estimator. The analysis of the performance takes into account the impact of both system and channel parameters

Mobile and Wireless Communications

Mobile and Wireless Communications have been one of the major revolutions of the late twentieth century. We are witnessing a very fast growth in these technologies where mobile and wireless communications have become so ubiquitous in our society and indispensable for our daily lives. The relentless demand for higher data rates with better quality of services to comply with state-of-the art applications has revolutionized the wireless communication field and led to the emergence of new technologies such as Bluetooth, WiFi, Wimax, Ultra wideband, OFDMA. Moreover, the market tendency confirms that this revolution is not ready to stop in the foreseen future. Mobile and wireless communications applications cover diverse areas including entertainment, industrialist, biomedical, medicine, safety and security, and others, which definitely are improving our daily life. Wireless communication network is a multidisciplinary field addressing different aspects raging from theoretical analysis, system architecture design, and hardware and software implementations. While different new applications are requiring higher data rates and better quality of service and prolonging the mobile battery life, new development and advanced research studies and systems and circuits designs are necessary to keep pace with the market requirements. This book covers the most advanced research and development topics in mobile and wireless communication networks. It is divided into two parts with a total of thirty-four stand-alone chapters covering various areas of wireless communications of special topics including: physical layer and network layer, access methods and scheduling, techniques and technologies, antenna and amplifier design, integrated circuit design, applications and systems. These chapters present advanced novel and cutting-edge results and development related to wireless communication offering the readers the opportunity to enrich their knowledge in specific topics as well as to explore the whole field of rapidly emerging mobile and wireless networks. We hope that this book will be useful for students, researchers and practitioners in their research studies

Nonlinear amplifier distortion in cooperative OFDM systems

OFDM (Orthogonal frequency division multiplexing) on lupaava langattoman tietoliikenteen teknologia johtuen sen hyvästä suorituskyvystä monitieympäristössä. Yhteistoiminnallisen tiedonvälityksen tekniikka on nykyisin jatkuvan tutkimuksen kohteena. Se hyödyntää muiden päätteiden antenneja virtuaalisen moniantennijärjestelmän luomiseen mahdollistaen moniantennijärjestelmille ominaisia kapasiteettihyötyjä. Tässä diplomityössä tutkitaan epälineaarista vahvistussäröä, kun näitä molempia tekniikoita käytetään yhdessä. Ensimmäiset kappaleet käsittelevät OFDM-järjestelmien ja epälineaaristen OFDM-järjestelmien särön sekä yhteistoiminnallisen tiedonvälityksen taustoja. Yhteistoiminnallisten OFDM-järjestelmien suorituskykyä mitataan simulaatioiden avulla epälineaarisen särön vaikuttaessa. Suorituskykyä mitataan bittivirhesuhteena käyttäen epäyhteistoiminnallista ja lineaarista yhteistoiminnallista järjestelmää vertailukohteena. Lisäksi särötermi myös analysoidaan. Systeemimalli sisältää epälineaarisen vahvistuksen välittimessä, jota mallinnetaan elektronisella tehovahvistimella. Lopuksi esitellään ja testataan tekniikka järjestelmän suorituskyvyn parantamiseen optimoimalla maksimisuhdeyhdistintä. Se optimoidaan mallintamalla vahvistussäröä normaalijakaumalla. Lisäksi esitellään ja testataan yhteistoiminnallisille järjestelmille sopiva tehovahvistimen epälineaarisuuden poistotekniikan muunnelma, jolla saadaan lähellä lineaarista tapausta olevia tuloksia.Orthogonal frequency division multiplexing (OFDM) is a promising technique for wireless communications because of its good performance under multipath environments. The concept of cooperative communications is currently under constant research. It uses antennas of other terminals to create virtual multiple input multiple output (MIMO) systems, providing capacity gains similar to those of MIMO systems. This thesis studies the issue of nonlinear amplifier distortion when these two techniques are used together. The first chapters give a background on OFDM systems, nonlinear distortion in OFDM systems, and Cooperative Communications. The performance of OFDM cooperative systems under nonlinear distortion are measured by simulations. The performance is measured in terms of BER using a non-cooperative system and a linear cooperative system as references. In addition, the distortion term is also analysed. The system model includes a non-linear amplifier at the relay, modelled as a solid state power amplifier (SSPA). A technique for improving the performance of the system, by optimising the maximum ratio combiner (MRC), is introduced and tested. The MRC is optimised by modelling the distortion noise as Gaussian. Also, a modification to the power amplifier nonlinearity cancellation (PANC) technique, suitable to cooperative systems, is introduced and tested, showing results close to the linear case

Estimation and detection techniques for doubly-selective channels in wireless communications

A fundamental problem in communications is the estimation of the channel. The signal transmitted through a communications channel undergoes distortions so that it is often received in an unrecognizable form at the receiver. The receiver must expend significant signal processing effort in order to be able to decode the transmit signal from this received signal. This signal processing requires knowledge of how the channel distorts the transmit signal, i.e. channel knowledge. To maintain a reliable link, the channel must be estimated and tracked by the receiver. The estimation of the channel at the receiver often proceeds by transmission of a signal called the 'pilot' which is known a priori to the receiver. The receiver forms its estimate of the transmitted signal based on how this known signal is distorted by the channel, i.e. it estimates the channel from the received signal and the pilot. This design of the pilot is a function of the modulation, the type of training and the channel. [Continues.

Equalization of doubly selective channels using iterative and recursive methods

Novel iterative and recursive schemes for the equalization of time-varying frequency selective channels are proposed. Such doubly selective channels are shown to be common place in mobile communication systems, for example in second generation systems based on time division multiple access (TDMA) and so-called beyond third generation systems most probably utilizing orthogonal frequency division multiplexing (OFDM). A new maximum likelihood approach for the estimation of the complex multipath gains (MGs) and the real Doppler spreads (DSs) of a parametrically modelled doubly selective single input single output (SISO) channel is derived. Considerable complexity reduction is achieved by exploiting the statistical properties of the training sequence in a TDMA system. The Cramer-Rao lower bound for the resulting estimator is derived and simulation studies are employed to confirm the statistical efficiency of the scheme. A similar estimation scheme is derived for the MGs and DSs in the context of a multiple input multiple output (MIMO) TDMA system. A computationally efficient recursive equalization scheme for both a SISO and MIMO TDMA system which exploits the estimated MGs and DSs is derived on the basis of repeated application of the matrix inversion lemma. Bit error rate (BER) simulations confirm the advantage of this scheme over equalizers which have limited knowledge of such parameters. For OFDM transmission over a general random doubly selective SISO channel, the time selectivity is mitigated with an innovative relatively low complexity iterative method. Equalization is in effect split into two stages: one which exploits the sparsity in the associated channel convolution matrix and a second which performs a posteriori detection of the frequency domain symbols. These two procedures interact in an iterative manner, exchanging information between the time and frequency domains. Simulation studies show that the performance of the scheme approaches the matched filter bound when interleaving is also introduced to aid in decorrelation. Finally, to overcome the peak to average power problem in conventional OFDM transmission, the iterative approach is extended for single carrier with cyclic prefix (SCCP) systems. The resulting scheme has particularly low complexity and is shown by simulation to have robust performance.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Iterative Receiver Techniques for Data-Driven Channel Estimation and Interference Mitigation in Wireless Communications

Wireless mobile communications were initially a way for people to communicate through low data rate voice call connections. As data enabled devices allow users the ability to do much more with their mobile devices, so to will the demand for more reliable and pervasive wireless data. This is being addressed by so-called 4th generation wireless systems based on orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) antenna systems. Mobile wireless customers are becoming more demanding and expecting to have a great user experience over high speed broadband access at any time and anywhere, both indoor and outdoor. However, these promising improvements cannot be realized without an e±cient design of the receiver. Recently, receivers utilizing iterative detection and decoding have changed the fundamental receiver design paradigm from traditional separated parameter estimation and data detection blocks to an integrated iterative parameter estimator and data detection unit. Motivated by this iterative data driven approach, we develop low complexity iterative receivers with improved sensitivity compared to the conventional receivers, this brings potential benefits for the wireless communication system, such as improving the overall system throughput, increasing the macro cell coverage, and reducing the cost of the equipments in both the base station and mobile terminal. It is a challenge to design receivers that have good performance in a highly dynamic mobile wireless environment. One of the challenges is to minimize overhead reference signal energy (preamble, pilot symbols) without compromising the performance. We investigate this problem, and develop an iterative receiver with enhanced data-driven channel estimation. We discuss practical realizations of the iterative receiver for SISO-OFDM system. We utilize the channel estimation from soft decoded data (the a priori information) through frequency-domain combining and time-domain combining strategies in parallel with limited pilot signals. We analyze the performance and complexity of the iterative receiver, and show that the receiver's sensitivity can be improved even with this low complexity solution. Hence, seamless communications can be achieved with better macro cell coverage and mobility without compromising the overall system performance. Another challenge is that a massive amount of interference caused by MIMO transmission (spatial multiplexing MIMO) reduces the performance of the channel estimation, and further degrades data detection performance. We extend the iterative channel estimation from SISO systems to MIMO systems, and work with linear detection methods to perform joint interference mitigation and channel estimation. We further show the robustness of the iterative receivers in both indoor and outdoor environment compared to the conventional receiver approach. Finally, we develop low complexity iterative spatial multiplexed MIMO receivers for nonlinear methods based on two known techniques, that is, the Sphere Decoder (SD) method and the Markov Chain Monte Carlo (MCMC) method. These methods have superior performance, however, they typically demand a substantial increase in computational complexity, which is not favorable in practical realizations. We investigate and show for the first time how to utilize the a priori information in these methods to achieve performance enhancement while simultaneously substantially reducing the computational complexity. In our modified sphere decoder method, we introduce a new accumulated a priori metric in the tree node enumeration process. We show how we can improve the performance by obtaining the reliable tree node candidate from the joint Maximum Likelihood (ML) metric and an approximated a priori metric. We also show how we can improve the convergence speed of the sphere decoder (i.e., reduce the com- plexity) by selecting the node with the highest a priori probability as the starting node in the enumeration process. In our modified MCMC method, the a priori information is utilized for the firrst time to qualify the reliably decoded bits from the entire signal space. Two new robust MCMC methods are developed to deal with the unreliable bits by using the reliably decoded bit information to cancel the interference that they generate. We show through complexity analysis and performance comparison that these new techniques have improved performance compared to the conventional approaches, and further complexity reduction can be obtained with the assistance of the a priori information. Therefore, the complexity and performance tradeoff of these nonlinear methods can be optimized for practical realizations