Frame synchronization is an important problem in digital communication systems. In frame synchronization, the main task is to find the frame start given the flow of the communication symbols. In this thesis, frame synchronization problem is investigated for both additive white Gaussian noise (AWGN) channels and frequency selective channels. Most of the previous works on frame synchronization consider the simple case of AWGN channels. The algorithms developed for this purpose fail in frequency selective channels. There is limited number of algorithms proposed for the frequency selective channels. In this thesis, existing frame synchronization techniques are investigated for both AWGN and frequency selective channels. Code-aided frame synchronization techniques are combined with the methods for frequency selective channels. Mainly two types of code-aided frame synchronization schemes are considered and two new system structures are proposed for frame synchronization. One of the proposed structures performs better than the alternative methods for frequency selective channels. The overall system for this new synchronizer is composed of a list synchronizer which generates the possible frame starts, a channel estimator, a soft output MLSE equalizer, and a soft output Viterbi decoder. A mode separation algorithm is used to generate the statistics for the selection of the true frame start. Several experiments are done and the performance is outlined for a variety of scenarios.

Soft iterative detection and decoding techniques have been shown to be able to achieve near-capacity performance in multiple-antenna systems. To obtain the optimal soft information by marginalization over the entire observation space is intractable; and the current literature is unable to guide us towards the best way to obtain the suboptimal soft information. In this thesis, several existing soft-input soft-output (SISO) detectors, including minimum mean-square error-successive interference cancellation (MMSE-SIC), list sphere decoding (LSD), and Fincke-Pohst maximum-a-posteriori (FPMAP), are examined. Prior research has demonstrated that LSD and FPMAP outperform soft-equalization methods (i.e., MMSE-SIC); however, it is unclear which of the two scheme is superior in terms of performance-complexity trade-off. A comparison is conducted to resolve the matter. In addition, an improved scheme is proposed to modify LSD and FPMAP, providing error performance improvement and a reduction in computational complexity simultaneously. Although list-type detectors such as LSD and FPMAP provide outstanding error performance, issues such as the optimal initial sphere radius, optimal radius update strategy, and their highly variable computational complexity are still unresolved. A new detection scheme is proposed to address the above issues with fixed detection complexity, making the scheme suitable for practical implementation. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2008-07-08 19:29:17.66

Abstract The development of wireless telecommunication systems has been rapid during the last two decades and the data rates as well as the quality of service (QoS) requirements are continuously growing. Multiple-input multiple-output (MIMO) techniques in combination with orthogonal frequency-division multiplexing (MIMO–OFDM) have been identified as a promising approach for high spectral efficiency wideband systems. The optimal detection method for a coded MIMO–OFDM system with spatial multiplexing (SM) is the maximum a posteriori (MAP) detector, which is often too complex for systems with high order modulation. Suboptimal linear detectors, such as the linear minimum mean square error (LMMSE) criterion based detection, offer low complexity solutions, but have poor performance in correlated fading channels. A list sphere detector (LSD) is a tree search based soft output detector that can be used to approximate the MAP detector with a lower computational complexity. The benefits of the more advanced detectors can be realized especially in a low SNR environment by, e.g., increasing the cell coverage. In this thesis, we consider the linear minimum mean square error (LMMSE) criterion based detectors and more advanced LSDs for detection of SM transmission. The LSD algorithms are not as such feasible for hardware implementation. Therefore, we identify the design choices that relate to the performance and implementation complexity of the LSD algorithms. We give guidelines to the LSD algorithm design and propose the proper trade-off solutions for practical wireless systems. The more stringent requirements call for further research on architectures and implementation. In particular, it is important to address the parallelism and pipelining factors in the architecture design to enable an optimal trade-off between used resources and operating speed. We design pipelined systolic array architecture for LMMSE detector algorithms and efficient architectures with given algorithm properties for the LSD algorithms. We consider the VLSI implementation of the algorithms to study the true performance and complexity. The designed architectures are implemented on a field programmable gate array (FPGA) chip and CMOS application specific integrated circuit (ASIC) technology. Finally, we present some measurement results with a hardware testbed to verify the performance of the considered algorithms. / Tiivistelmä Langattoman tietoliikenteen kehitys on ollut nopeaa viimeisien vuosikymmenien aikana ja järjestelmiltä vaaditaan yhä suurempia datanopeuksia ja luotettavuutta. Multiple-input multiple-output (MIMO) tekniikka yhdistettynä monikantoaaltomodulointiin (MIMO-OFDM) on tunnistettu lupaavaksi järjestelmäksi, joka mahdollistaa tehokkaan taajuusalueen hyödyntämisen. Optimaalinen ilmaisumenetelmä tilakanavoituun (SM) ja koodattuun MIMO-OFDM järjestelmään on maximum a posteriori (MAP) ilmaisin, joka on tyypillisesti liian kompleksinen toteuttaa laajakaistajärjestelmissä, joissa käytetään korkean asteen modulointia. Alioptimaaliset lineaariset ilmaisimet, kuten pienimpään keskineliövirheeseen (LMMSE) perustuvat ilmaisimet, ovat suhteellisen yksinkertaisia toteuttaa nykyteknologialla, mutta niiden suorituskyky on varsin heikko korreloivassa radiokanavassa. Listapalloilmaisin (LSD) on puuhakualgoritmiin perustuva pehmeän ulostulon ilmaisin, joka pystyy jäljittelemään MAP ilmaisinta sitä pienemmällä kompleksisuudella. Kehittyneemmät ilmaisimet, kuten LSD, voivat parantaa langattoman verkon suorituskykyä erityisesti ympäristössä, jossa on matala signaalikohinasuhde, esimerkiksi mahdollistamalla suuremman toiminta-alueen. Tässä väitöskirjassa on tutkittu kahta LMMSE ilmaisinta ja kolmea LSD ilmaisinta SM lähetyksen ilmaisuun. Yleisesti LSD algoritmit eivät ole sellaisenaan toteutuskelpoisia kaupallisiin järjestelmiin. Väitöskirjassa on tämän vuoksi tutkittu LSD:n toteutukseen liittyviä haasteita ja toteutusmenetelmiä ja annetaan suosituksia LSD algorithmien suunnitteluun sekä ehdotetaan sopivia toteutuskompromisseja käytännön langattomiin järjestelmiin. Haastavammat suorituskyky- ja latenssivaatimukset edellyttävät lisätutkimuksia toteutusarkkitehtuureihin ja toteutuksiin. Erityisesti rinnakkaisten resurssien käyttö ja liukuhihnatekniikka toteutusarkkitehtuureissa mahdollistavat optimaalisen kompromissin löytämisen toteutuksessa käytettyjen resurssien ja laskentanopeuden väliltä. Väitöskirjassa suunnitellaan tehokkaat arkkitehtuurit tutkituille LMMSE ja LSD algoritmeille ottaen huomioon niiden ominaisuudet. Väitöskirjassa tutkitaan algoritmien toteutusta VLSI tekniikalla ja pyritään saamaan realistinen arvio algoritmien kompleksisuudesta ja suorituskyvystä. Algoritmeille suunnitellut arkkitehtuurit on toteutettu sekä FPGA piirille että erillisenä toteutuksena ASIC teknologialla. Väitöskirjassa esitetään myös testilaitteistolla tehtyjä mittaustuloksia ja varmistetaan toteutettujen algoritmien suorituskyky.

In wireless networks, reliable communication is a challenging issue due to many attenuation factors such as receiver noise, channel fading, interference and asynchronous delays. Lattice coding and decoding provide efficient solutions to many problems in wireless communications and multiuser information theory. The capability in achieving the fundamental limits, together with simple and efficient transmitter and receiver structures, make the lattice strategy a promising approach. This work deals with problems of lattice detection over fading channels and time asynchronism over the lattice-based compute-and-forward protocol. In multiple-input multiple-output (MIMO) systems, the use of lattice reduction significantly improves the performance of approximate detection techniques. In the first part of this thesis, by taking advantage of the temporal correlation of a Rayleigh fading channel, low complexity lattice reduction methods are investigated. We show that updating the reduced lattice basis adaptively with a careful use of previous channel realizations yields a significant saving in complexity with a minimal degradation in performance. Considering high data rate MIMO systems, we then investigate soft-output detection methods. Using the list sphere decoder (LSD) algorithm, an adaptive method is proposed to reduce the complexity of generating the list for evaluating the log-likelihood ratio (LLR) values. In the second part, by applying the lattice coding and decoding schemes over asynchronous networks, we study the impact of asynchronism on the compute-and-forward strategy. While the key idea in compute-and-forward is to decode a linear synchronous combination of transmitted codewords, the distributed relays receive random asynchronous versions of the combinations. Assuming different asynchronous models, we design the receiver structure prior to the decoder of compute-and-forward so that the achievable rates are maximized at any signal-to-noise-ratio (SNR). Finally, we consider symbol-asynchronous X networks with single antenna nodes over time-invariant channels. We exploit the asynchronism among the received signals in order to design the interference alignment scheme. It is shown that the asynchronism provides correlated channel variations which are proved to be sufficient to implement the vector interference alignment over the constant X network.

In wireless networks, reliable communication is a challenging issue due to many attenuation factors such as receiver noise, channel fading, interference and asynchronous delays. Lattice coding and decoding provide efficient solutions to many problems in wireless communications and multiuser information theory. The capability in achieving the fundamental limits, together with simple and efficient transmitter and receiver structures, make the lattice strategy a promising approach. This work deals with problems of lattice detection over fading channels and time asynchronism over the lattice-based compute-and-forward protocol. In multiple-input multiple-output (MIMO) systems, the use of lattice reduction significantly improves the performance of approximate detection techniques. In the first part of this thesis, by taking advantage of the temporal correlation of a Rayleigh fading channel, low complexity lattice reduction methods are investigated. We show that updating the reduced lattice basis adaptively with a careful use of previous channel realizations yields a significant saving in complexity with a minimal degradation in performance. Considering high data rate MIMO systems, we then investigate soft-output detection methods. Using the list sphere decoder (LSD) algorithm, an adaptive method is proposed to reduce the complexity of generating the list for evaluating the log-likelihood ratio (LLR) values. In the second part, by applying the lattice coding and decoding schemes over asynchronous networks, we study the impact of asynchronism on the compute-and-forward strategy. While the key idea in compute-and-forward is to decode a linear synchronous combination of transmitted codewords, the distributed relays receive random asynchronous versions of the combinations. Assuming different asynchronous models, we design the receiver structure prior to the decoder of compute-and-forward so that the achievable rates are maximized at any signal-to-noise-ratio (SNR). Finally, we consider symbol-asynchronous X networks with single antenna nodes over time-invariant channels. We exploit the asynchronism among the received signals in order to design the interference alignment scheme. It is shown that the asynchronism provides correlated channel variations which are proved to be sufficient to implement the vector interference alignment over the constant X network.