Due to the highly-varying wireless channels over time, frequency, and space domains, statistical QoS provisioning, instead of deterministic QoS guarantees, has become a recognized feature in the next-generation wireless networks. In this dissertation, we study the adaptive wireless resource allocation problems for statistical QoS provisioning, such as guaranteeing the specified delay-bound violation probability, upper-bounding the average loss-rate, optimizing the average goodput/throughput, etc., in several typical types of mobile wireless networks. In the first part of this dissertation, we study the statistical QoS provisioning for mobile multicast through the adaptive resource allocations, where different multicast receivers attempt to receive the common messages from a single base-station sender over broadcast fading channels. Because of the heterogeneous fading across different multicast receivers, both instantaneously and statistically, how to design the efficient adaptive rate control and resource allocation for wireless multicast is a widely cited open problem. We first study the time-sharing based goodput-optimization problem for non-realtime multicast services. Then, to more comprehensively characterize the QoS provisioning problems for mobile multicast with diverse QoS requirements, we further integrate the statistical delay-QoS control techniques — effective capacity theory, statistical loss-rate control, and information theory to propose a QoS-driven optimization framework. Applying this framework and solving for the corresponding optimization problem, we identify the optimal tradeoff among statistical delay-QoS requirements, sustainable traffic load, and the average loss rate through the adaptive resource allocations and queue management. Furthermore, we study the adaptive resource allocation problems for multi-layer video multicast to satisfy diverse statistical delay and loss QoS requirements over different video layers. In addition, we derive the efficient adaptive erasure-correction coding scheme for the packet-level multicast, where the erasure-correction code is dynamically constructed based on multicast receivers’ packet-loss statuses, to achieve high error-control efficiency in mobile multicast networks. In the second part of this dissertation, we design the adaptive resource allocation schemes for QoS provisioning in unicast based wireless networks, with emphasis on statistical delay-QoS guarantees. First, we develop the QoS-driven time-slot and power allocation schemes for multi-user downlink transmissions (with independent messages) in cellular networks to maximize the delay-QoS-constrained sum system throughput. Second, we propose the delay-QoS-aware base-station selection schemes in distributed multiple-input-multiple-output systems. Third, we study the queueaware spectrum sensing in cognitive radio networks for statistical delay-QoS provisioning. Analyses and simulations are presented to show the advantages of our proposed schemes and the impact of delay-QoS requirements on adaptive resource allocations in various environments.

Communication over a wireless channel is a challenging task because of the inherent fading effects. Any wireless communication system employs some form of diversity improving techniques in order to improve the reliability of the channel. This thesis deals with efficient code design for two different spatial diversity techniques, viz, diversity by employing multiple antennas at the transmitter and/or the receiver, and diversity through cooperative commu- nication between users. In other words, this thesis deals with efficient code design for (1) multiple-input multiple-output (MIMO) channels, and (2) wireless relay channels. Codes for the MIMO channel are termed space-time (ST) codes and those for the relay channels are called distributed ST codes. The first part of the thesis focuses on ST code construction for MIMO fading channel with perfect channel state information (CSI) at the receiver, and no CSI at the transmitter. As a measure of performance we use the rate-diversity tradeoff and the Diversity-Multiplexing Gain (D-MG) Tradeoff, which are two different tradeoffs characterizing the tradeoff between the rate and the reliability achievable by any ST code. We provide two types of code constructions that are optimal with respect to the rate-diversity tradeoff; one is based on the rank-distance codes which are traditionally applied as codes for storage devices, and the second construction is based on a matrix representation of a cayley algebra. The second contribution in ST code constructions is related to codes with a certain nonvanishing determinant (NVD) property. Motivation for these constructions is a recent result on the necessary and sufficient conditions for an ST code to achieve the D-MG tradeoff. Explicit code constructions satisfying these conditions are provided for certain number of transmit antennas. The second part of the thesis focuses on distributed ST code construction for wireless relay channel. The transmission protocol follows a two-hop model wherein the source broadcasts a vector in the first hop and in the second hop the relays transmit a vector that is a transformation of the received vector by a relay-specific unitary transformation. While the source and relays do not have CSI, at the destination we assume two different scenarios (a) destina- tion with complete CSI (b) destination with only the relay-destination CSI. For both these scenarios, we derive a Chernoff bound on the pair-wise error probability and propose code design criteria. For the first case, we provide explicit construction of distributed ST codes with lower decoding complexity compared to codes based on some earlier system models. For the latter case, we propose a novel differential encoding and differential decoding technique and also provide explicit code constructions. At the heart of all these constructions is the cyclic division algebra (CDA) and its matrix representations. We translate the problem of code construction in each of the above scenarios to the problem of constructing CDAs satisfying certain properties. Explicit examples are provided to illustrate each of these constructions.

In this thesis, we focus on interference cancelling (IC) detectors for advanced communication systems. The contents of this thesis is divided into the following four parts: 1. Multiuser interference (MUI) cancellation in uplink orthogonal frequency division multiple access (OFDMA). 2. Inter-carrier interference (ICI) and inter-symbol interference (ISI) cancellation in space-frequency block coded OFDM (SFBC-OFDM). 3. Single-symbol decodability (SSD) of distributed space-time block codes (DSTBC) in partially-coherent cooperative networks with amplify-and-forward protocol at the relays 4. Interference cancellation in cooperative SFBC-OFDM networks with amplify-and-forward (AF) and decode-and-forward (DF) protocols at the relays. In uplink OFDMA systems, MUI occurs due to different carrier frequency offsets of different users at the receiver. In the first part of the thesis, we present a weighted multistage linear parallel interference cancellation approach to mitigate the effect of this MUI in uplink OFDMA. We also present a minimum mean square error (MMSE) based approach to MUI cancellation in uplink OFDMA. We present a recursion to approach the MMSE solution and show structure-wise and performance-wise comparison with other detectors in the literature. Use of SFBC-OFDM signals is advantageous in high-mobility broadband wireless access, where the channel is highly time- as well as frequency-selective because of which the receiver experiences both ISI as well as ICI. In the second part of the thesis, we are concerned with the detection of SFBC-OFDM signals on time- and frequency-selective MIMO channels. Specifically, we propose and evaluate the performance of an interference cancelling receiver for SFBC-OFDM, which alleviates the effects of ISI and ICI in highly time- and frequency-selective channels The benefits of MIMO techniques can be made possible to user nodes having a single transmit antenna through cooperation among different nodes. In the third part of the thesis, we derive a new set of conditions for a distributed DSTBC to be SSD for a partially-coherent relay channel (PCRC), where the relays have only the phase information of the source-to-relay channels. We also establish several properties of SSD codes for PCRC. In the last part of the thesis, we consider cooperative SFBC-OFDM networks with AF and DF protocols at the relays. In cooperative SFBC-OFDM networks that employ DF protocol, i) ISI occurs at the destination due to violation of the `quasi-static' assumption because of the frequency selectivity of the relay-to-destination channels, and ii) ICI occurs due to imperfect carrier synchronization between the relay nodes and the destination, both of which result in error-floors in the bit error performance at the destination. We propose an interference cancellation algorithm for this system at the destination node, and show that the proposed algorithm effectively mitigates the ISI and ICI effects.

It is well known that communication using multiple antennas provides high data rate and reliability. Coding across space and time is necessary to fully exploit the gains offered by multiple input multiple output (MIMO) systems. One such popular method of coding for MIMO systems is space-time block coding. In applications where the terminals do not have enough physical space to mount multiple antennas, relaying or cooperation between multiple single antenna terminals can help achieve spatial diversity in such scenarios as well. Relaying techniques can also help improve the range and reliability of communication. Recently it has been shown that certain space-time block codes (STBCs) can be employed in a distributed fashion in single antenna relay networks to extract the same benefits as in point to point MIMO systems. Such STBCs are called distributed STBCs. However an important practical issue with STBCs and DSTBCs is its associated high maximum likelihood (ML) decoding complexity. The central theme of this thesis is to systematically construct STBCs and DSTBCs applicable for various scenarios such that are amenable for low decoding complexity. The first part of this thesis provides constructions of high rate STBCs from crossed product algebras that are minimum mean squared error (MMSE) optimal, i.e., achieves the least symbol error rate under MMSE reception. Moreover several previous constructions of MMSE optimal STBCs are found to be special cases of the constructions in this thesis. It is well known that STBCs from orthogonal designs offer single symbol ML decoding along with full diversity but the rate of orthogonal designs fall exponentially with the number of transmit antennas. Thus it is evident that there exists a tradeoff between rate and ML decoding complexity of full diversity STBCs. In the second part of the thesis, a definition of rate of a STBC is proposed and the problem of optimal tradeoff between rate and ML decoding complexity is posed. An algebraic framework based on extended Clifford algebras is introduced to study the optimal tradeoff for a class of multi-symbol ML decodable STBCs called ‘Clifford unitary weight (CUW) STBCs’ which include orthogonal designs as a special case. Code constructions optimally meeting this tradeoff are also obtained using extended Clifford algebras. All CUW-STBCs achieve full diversity as well. The third part of this thesis focusses on constructing DSTBCs with low ML decoding complexity for two hop, amplify and forward based relay networks under various scenarios. The symbol synchronous, coherent case is first considered and conditions for a DSTBC to be multi-group ML decodable are first obtained. Then three new classes of four-group ML decodable full diversity DSTBCs are systematically constructed for arbitrary number of relays. Next the symbol synchronous non-coherent case is considered and full diversity, four group decodable distributed differential STBCs (DDSTBCs) are constructed for power of two number of relays. These DDSTBCs have the best error performance compared to all previous works along with low ML decoding complexity. For the symbol asynchronous, coherent case, a transmission scheme based on orthogonal frequency division multiplexing (OFDM) is proposed to mitigate the effects of timing errors at the relay nodes and sufficient conditions for a DSTBC to be applicable in this new transmission scheme are given. Many of the existing DSTBCs including the ones in this thesis are found to satisfy these sufficient conditions. As a further extension, differential encoding is combined with the proposed transmission scheme to arrive at a new transmission scheme that can achieve full diversity in symbol asynchronous, non-coherent relay networks with no knowledge of the timing errors at the relay nodes. The DDSTBCs in this thesis are proposed for application in the proposed transmission scheme for symbol asynchronous, non-coherent relay networks. As a parallel to the non-coherent schemes based on differential encoding, we also propose non-coherent schemes for symbol synchronous and symbol asynchronous relay networks that are based on training. This training based transmission scheme leverages existing coherent DSTBCs for non-coherent communication in relay networks. Simulations show that this training scheme when used along with the coherent DSTBCs in this thesis outperform the best known DDSTBCs in the literature. Finally, in the last part of the thesis, connections between multi-group ML decodable unitary weight (UW) STBCs and groups with real elements are established for the first time. Using this connection, we translate the necessary and sufficient conditions for multi-group ML decoding of UW-STBCs entirely in group theoretic terms. We discuss various examples of multi-group decodable UW-STBCs together with their associated groups and list the real elements involved. These examples include orthogonal designs, quasi-orthogonal designs among many others.

No description available.

The search for the closest lattice point arises in many communication problems, and is known to be NP-hard. The Maximum Likelihood (ML) Detector is the optimal detector which yields an optimal solution to this problem, but at the expense of high computational complexity. Existing near-optimal methods used to solve the problem are based on the Sphere Decoder (SD), which searches for lattice points confined in a hyper-sphere around the received point. The SD has emerged as a powerful means of finding the solution to the ML detection problem for MIMO systems. However the bottleneck lies in the determination of the initial radius. This thesis is concerned with the detection of transmitted wireless signals in Multiple-Input Multiple-Output (MIMO) digital communication systems as efficiently and effectively as possible. The main objective of this thesis is to design efficient ML detection algorithms for MIMO systems based on the depth-first search (DFS) algorithms whilst taking into account complexity and bit error rate performance requirements for advanced digital communication systems. The increased capacity and improved link reliability of MIMO systems without sacrificing bandwidth efficiency and transmit power will serve as the key motivation behind the study of MIMO detection schemes. The fundamental principles behind MIMO systems are explored in Chapter 2. A generic framework for linear and non-linear tree search based detection schemes is then presented Chapter 3. This paves way for different methods of improving the achievable performance-complexity trade-off for all SD-based detection algorithms. The suboptimal detection schemes, in particular the Minimum Mean Squared Error-Successive Interference Cancellation (MMSE-SIC), will also serve as pre-processing as well as comparison techniques whilst channel capacity approaching Low Density Parity Check (LDPC) codes will be employed to evaluate the performance of the proposed SD. Numerical and simulation results show that non-linear detection schemes yield better performance compared to linear detection schemes, however, at the expense of a slight increase in complexity. The first contribution in this thesis is the design of a near ML-achieving SD algorithm for MIMO digital communication systems that reduces the number of search operations within the sphere-constrained search space at reduced detection complexity in Chapter 4. In this design, the distance between the ML estimate and the received signal is used to control the lower and upper bound radii of the proposed SD to prevent NP-complete problems. The detection method is based on the DFS algorithm and the Successive Interference Cancellation (SIC). The SIC ensures that the effects of dominant signals are effectively removed. Simulation results presented in this thesis show that by employing pre-processing detection schemes, the complexity of the proposed SD can be significantly reduced, though at marginal performance penalty. The second contribution is the determination of the initial sphere radius in Chapter 5. The new initial radius proposed in this thesis is based on the variable parameter α which is commonly based on experience and is chosen to ensure that at least a lattice point exists inside the sphere with high probability. Using the variable parameter α, a new noise covariance matrix which incorporates the number of transmit antennas, the energy of the transmitted symbols and the channel matrix is defined. The new covariance matrix is then incorporated into the EMMSE model to generate an improved EMMSE estimate. The EMMSE radius is finally found by computing the distance between the sphere centre and the improved EMMSE estimate. This distance can be fine-tuned by varying the variable parameter α. The beauty of the proposed method is that it reduces the complexity of the preprocessing step of the EMMSE to that of the Zero-Forcing (ZF) detector without significant performance degradation of the SD, particularly at low Signal-to-Noise Ratios (SNR). More specifically, it will be shown through simulation results that using the EMMSE preprocessing step will substantially improve performance whenever the complexity of the tree search is fixed or upper bounded. The final contribution is the design of the LRAD-MMSE-SIC based SD detection scheme which introduces a trade-off between performance and increased computational complexity in Chapter 6. The Lenstra-Lenstra-Lovasz (LLL) algorithm will be utilised to orthogonalise the channel matrix H to a new near orthogonal channel matrix H ̅.The increased computational complexity introduced by the LLL algorithm will be significantly decreased by employing sorted QR decomposition of the transformed channel H ̅ into a unitary matrix and an upper triangular matrix which retains the property of the channel matrix. The SIC algorithm will ensure that the interference due to dominant signals will be minimised while the LDPC will effectively stop the propagation of errors within the entire system. Through simulations, it will be demonstrated that the proposed detector still approaches the ML performance while requiring much lower complexity compared to the conventional SD.

Στο πλαίσιο αυτής της διατριβής μελετάται η επίδοση συστημάτων διαφορισμού MIMO σε γενικευμένα κανάλια διαλείψεων. Αρχικά, εξετάζεται η επίδοση των OSTBC σε περιβάλλοντα διαλείψεων Hoyt. Αποδεικνύεται ότι, στην περίπτωση τέτοιων συστημάτων, ο σηματοθορυβικός λόγος (signal to noise ratio, SNR) εκφράζεται ως μία τετραγωνική μορφή κανονικών τυχαίων μεταβλητών και γίνεται χρήση της συνάρτησης πυκνότητας πιθανότητας και της αθροιστικής συνάρτησης κατανομής αυτής της μορφής για τον υπολογισμό των μετρικών επίδοσης. Επιπλέον, μελετάται η σύγκλιση των σειρών που χρησιμοποιούνται για τον υπολογισμό των δύο αυτών συναρτήσεων και κατασκευάζονται νέα άνω φράγματα για το σφάλμα αποκοπής των σειρών. Τα φράγματα αυτά είναι σαφώς πιο αυστηρά από τα ήδη γνωστά από τη βιβλιογραφία. Στη συνέχεια, εισάγεται ένα γενικευμένο μοντέλο διαλείψεων για την ανάλυση επίδοσης των OSTBC και των δεκτών MRC και υπολογίζονται όλες οι μετρικές επίδοσης των δύο συστημάτων για το συγκεκριμένο μοντέλο διαλείψεων. Το μοντέλο αυτό περιλαμβάνει ως ειδικές περιπτώσεις τα πλέον διαδεδομένα μοντέλα καναλιών διαλείψεων, ενώ επιπλέον, επιτρέπει την ανάλυση επίδοσης σε μικτά περιβάλλοντα διαλείψεων όπου τα πολλαπλά κανάλια μπορούν να ακολουθούν διαφορετικές κατανομές. Στη συνέχεια, μελετάται η επίδοση συστημάτων συνεργατικού διαφορισμού με χρήση αναμεταδοτών ανίχνευσης και προώθησης (Detect and Forward, DaF) σε περιβάλλοντα διαλείψεων Rayleigh. Εξετάζονται τρεις διαφορετικοί δέκτες και υπολογίζεται η πιθανότητα σφάλματος ανά bit γι' αυτούς. Τέλος προτείνεται ένας νέος δέκτης για συνεργατικά συστήματα DaF και αποδεικνύεται η ανωτερότητά του σε σύγκριση με τους υπόλοιπους μελετώμενους δέκτες. Όλα τα θεωρητικά αποτελέσματα που παρουσιάζονται στο πλαίσιο της διατριβής συγκρίνονται με αποτελέσματα προσομοιώσεων Monte Carlo που αποδεικνύουν την ορθότητα της ανάλυσης. / This thesis studies the performance of MIMO diversity systems in generalized fading channels. First, we examine the performance of OSTBC in Hoyt fading channels. It is proven that, for this fading model, and when an OSTBC is employed, the signal-to-noise ratio (SNR) of the OSTBC can be expressed as a quadratic form in normal random variables. Therefore, the performance analysis for OSTBC over Hoyt fading channels is performed using the PDF and the CDF of such quadratic forms. In the statistical literature, these functions are expressed in terms of infinite series. The convergence of the series is thoroughly studied and new expressions for the truncation error bound of these series are proposed. The proposed bounds are much tighter than the bounds that can be found in the literature. The expressions for the PDF and the CDF are then used for the performance analysis of OSTBC over Hoyt fading and several performance metrics are calculated. Then, a generalized fading model for the performance analysis of OSTBC and MRC is proposed and the theoretical performance analysis of both MRC and OSTBC is carried out. The main advantage of this model is the fact that it includes as special cases most of the widely used fading models. Furthermore, the performance of cooperative diversity systems employing Detect and Forward (DaF) relays is studied for Rayleigh fading channels. More specifically, three low complexity detection algorithms for these channels are examined and closed-form expressions of the bit error probability (BEP) for these receivers are derived. Finally, a new low complexity receiver for cooperative systems with DaF relays is proposed. Using Monte Carlo Simulations it is shown that this receiver outperforms the three receivers that have been studied. For the systems studied in the thesis, the performance analysis results that have been derived theoretically are compared with Monte Carlo simulations that prove the validity of the analysis.

Τα μελλοντικά ασύρματα δίκτυα και συστήματα επικοινωνιών αναμένεται να παρέχουν αξιόπιστα υπηρεσίες δεδομένων με απαιτήσεις ρυθμού μετάδοσης δεδομένων οι οποίες κυμαίνονται από λίγα kbps μέχρι μερικά Mbps και εξαιτίας του υψηλού κόστους του φάσματος συχνοτήτων, αυτά τα συστήματα χρειάζεται να είναι εξαιρετικά αποτελεσματικά όσον αφορά στη χρησιμοποίηση του φάσματος. Συγκεκριμένα, η εφαρμογή τεχνικών μετάδοσης δεδομένων οι οποίες βασίζονται σε MIMO και OFDMA θεωρείται ως μια πολλά υποσχόμενη λύση για να ικανοποιήσει αυτές τις απαιτήσεις. Από την άλλη μεριά, τα συστήματα MIMO-OFDMA είναι εύκαμπτα και φασματικά αποτελεσματικά αλλά ο αξιοσημείωτα μεγάλος αριθμός υποφορέων και ο συνυπολογισμός της διάστασης χώρου καθιστούν την κατανομή ραδιοπόρων πολύ πολύπλοκη. Στην πραγματικότητα, η βέλτιστη κατανομή ραδιοπόρων η οποία μεγιστοποιεί το συνολικό ρυθμό μετάδοσης δεδομένων των χρηστών είναι συχνά πάρα πολύ πολύπλοκη για πρακτικές εφαρμογές. Συνεπώς, απαιτούνται υποβέλτιστες σχετικά αποτελεσματικές και χαμηλής πολυπλοκότητας στρατηγικές κατανομής ραδιοπόρων ώστε να κατανείμουν τους ραδιοπόρους συχνότητας, ισχύος και χώρου του συστήματος στους χρήστες του συστήματος. Η παρούσα ΔΔ διαπραγματεύεται στρατηγικές κατανομής ραδιοπόρων στην κατερχόμενη και στην ανερχόμενη ζεύξη συστημάτων OFDMA, στην κατερχόμενη ζεύξη συστημάτων MISO-OFDMA και στην κατερχόμενη ζεύξη συστημάτων MIMO-OFDMA στοχεύοντας στη μεγιστοποίηση του συνολικού ρυθμού μετάδοσης δεδομένων των χρηστών εγγυώντας οι ρυθμοί μετάδοσης δεδομένων των χρηστών να τηρούν μια προκαθορισμένη αναλογία μεταξύ τους ή να ξεπερνούν προκαθορισμένους ελάχιστους ρυθμούς μετάδοσης δεδομένων. Στο πλαίσιο της επίλυσης του προβλήματος της μεγιστοποίησης του συνολικού ρυθμού μετάδοσης δεδομένων των χρηστών με ανεκτή πολυπλοκότητα για κάθε μία από τις προαναφερθείσες περιπτώσεις, προτείνονται νέοι υποβέλτιστοι αλγόριθμοι. Στην κατερχόμενη ζεύξη των συστημάτων SISO, στόχος είναι η μεγιστοποίση του συνολικού ρυθμού μετάδοσης δεδομένων των χρηστών με περιορισμό στη συνολική διαθέσιμη ισχύ και με αναλογικούς ρυθμούς μετάδοσης δεδομένων μεταξύ των χρηστών. Η προτεινόμενη μέθοδος, η οποία είναι αποτελεσματική όσον αφορά στην πολυπλοκότητα, αποτελείται από τρεις αλγόριθμους: έναν αλγόριθμο ο οποίος προσδιορίζει τον αριθμό των υποφορέων για κάθε χρήστη, έναν αλγόριθμο κατανομής υποφορέων διαιρώντας τους χρήστες σε δύο ομάδες και τον αλγόριθμο water-filling. Οι πρώτοι δύο αλγόριθμοι αναθέτουν τους διαθέσιμους υποφορείς στους χρήστες του συστήματος και ο τρίτος αλγόριθμος κατανέμει τη διαθέσιμη ισχύ με βέλτιστο τρόπο για μεγιστοποίηση του συνολικού ρυθμού μετάδοσης δεδομένων. Στην ανερχόμενη ζεύξη των συστημάτων SISO, στόχος είναι η μεγιστοποίηση του συνολικού ρυθμού μετάδοσης δεδομένων των χρηστών με περιορισμό στην ισχύ κάθε χρήστη και σε ελάχιστους ρυθμούς μετάδοσης δεδομένων μεταξύ των χρηστών. Η προτεινόμενη τεχνική, η οποία είναι αποτελεσματική όσον αφορά στην πολυπλοκότητα, αποτελείται από τρεις αλγόριθμους: έναν αλγόριθμο ο οποίος προσδιορίζει τον αριθμό των υποφορέων για κάθε χρήστη, έναν αλγόριθμο κατανομής υποφορέων διαιρώντας τους χρήστες σε δύο ομάδες και τον αλγόριθμο water-filling. Οι πρώτοι δύο αλγόριθμοι αναθέτουν τους διαθέσιμους υποφορείς στους χρήστες του συστήματος και ο τρίτος αλγόριθμος κατανέμει τη διαθέσιμη ισχύ. Στην κατερχόμενη ζεύξη των συστημάτων MISO αναπτύσσονται τρεις αλγόριθμοι επιλογής χρηστών και κατανομής πόρων για πολυχρηστικά συστήματα κατερχόμενης ζεύξης οι οποίοι είναι λιγότερο πολύπλοκοι από άλλες προσεγγίσεις και ενσωματώνουν τη δικαιοσύνη. Στους πρώτους δύο αλγόριθμους επιβάλλονται αναλογικοί περιορισμοί μεταξύ των ρυθμών μετάδοσης δεδομένων των χρηστών και στον τρίτο αλγόριθμο περιορισμοί στους ελάχιστους ρυθμούς μετάδοσης δεδομένων λαμβάνονται υπόψη. Επίσης, πραγματοποιείται επέκταση του αλγόριθμου μεγιστοποίησης του συνολικού ρυθμού μετάδοσης δεδομένων με αναλογικούς περιορισμούς δικαιοσύνης σε ΣΚΚ και για μείωση της πολυπλοκότητας οι υποφορείς ομαδοποιούνται σε τεμάχια. Τα αποτελέσματα της προσομοίωσης επιβεβαιώνουν την αποτελεσματικότητα τους στη διανομή του συνολικού ρυθμού μετάδοσης δεδομένων δίκαια μεταξύ των χρηστών αλλά και ότι σε ΣΚΚ επιτυγχάνονται μεγαλύτεροι συνολικοί ρυθμοί μετάδοσης δεδομένων. Τέλος, στην κατερχόμενη ζεύξη των συστημάτων MIMO, το πρόβλημα διατυπώνεται με στόχο τη μεγιστοποίηση του συνολικού ρυθμού μετάδοσης δεδομένων των χρηστών με περιορισμό στη συνολική διαθέσιμη ισχύ και ελέγξιμο εύρος ζώνης στο σύστημα εισάγοντας την παράμετρο α. Αφού αυτό το πρόβλημα βελτιστοποίησης πρέπει να εκτελεστεί σε πραγματικό χρόνο, προτείνεται ένας αλγόριθμος αποδοτικός, υποβέλτιστος και αποτελεματικός όσον αφορά στην πολυπλοκότητα ο οποίος παρουσιάζει λογική απώλεια όσον αφορά στην περίπτωση χωρίς περιορισμούς όπου ο μόνος στόχος είναι η μεγιστοποίηση του συνολικού ρυθμού μετάδοσης δεδομένων και εντυπωσιακό όφελος συγκρινόμενος με τη στατική τεχνική TDMA. Πέραν της θεωρητικής ανάλυσης των παραπάνω αλγόριθμων, ο προσομοιωτικός κώδικας που δημιουργήθηκε βασισμένος σε ρεαλιστικές υποθέσεις και απλουστεύσεις, μάς έδωσε τα αποτελέσματα εκείνα τα οποία μετρούν το συνολικό ρυθμό μετάδοσης δεδομένων των χρηστών ο οποίος παρέχεται από κάθε έναν από τους προαναφερθέντες αλγόριθμους και εξετάζουν την πιθανή καταλληλότητα για χρήση τους σε συγκεκριμένα περιβάλλοντα. Τα τελικά συμπεράσματα είναι ότι τα συστήματα MIMO-OFDMA είναι ικανά να προσφέρουν πραγματικές ευρυζωνικές υπηρεσίες πάνω από το ασύρματο κανάλι επικοινωνίας. / Future wireless communication networks and systems are expected to reliably provide data services with data rate requirements ranging from a few kbps up to some Mbps and, due to the high costs of frequency spectrum, these systems also need to be extremely efficient in terms of the spectrum usage. In particular, the application of transmission schemes based on OFDMA and on MIMO is considered as a promising solution to meet these requirements. On the one hand, MIMO-OFDMA systems are flexible and spectrally efficient but the considerably large number of subcarriers and the inclusion of the space dimension make the RRA in such systems very complex. In fact, the optimum RRA that maximizes the sum of the users' data rates is often too complex for practical application. Consequently, suboptimal rather efficient and low-complexity RRA strategies are required in order to allocate the frequency, power, and space radio resources of the system to the users of the system. This doctoral thesis deals with RRA strategies in the downlink and uplink of OFDMA systems, the downlink of MISO-OFDMA systems, and the downlink of MIMO-OFDMA systems aiming at the maximization of the sum of the users' data rates guaranteeing proportional data rates or minimum data rates among users. In order to solve the problem of maximizing the sum of the users' data rates with affordable complexity in each one of the aforementioned cases, new suboptimal algorithms are proposed. In the SISO downlink the objective is to maximize the sum of the users' data rates subject to constraints on the total available power and proportional data rates among users. The proposed method, which is also complexity effective, consists of three algorithms; an algorithm that determines the number of subcarriers for each user, a subcarrier allocation algorithm by dividing the users in two groups and the water-filling algorithm. The first two algorithms assign the available subcarriers to the users of the system and the third one allocates the available power optimally in order to maximize the sum of the users' data rates. In the SISO uplink the objective is to maximize the sum of the users' data rates subject to constraints on per user power and minimum data rates among users. The proposed scheme, which is also complexity effective, consists of three algorithms; an algorithm that determines the number of subcarriers for each user, a subcarrier allocation algorithm by dividing the users in two groups and the water-filling algorithm. The first two algorithms assign the available subcarriers to the users of the system and the third one allocates the available power. In the MISO downlink three user selection and resource allocation algorithms for multiuser downlink systems are developed that are less complex than other approaches and incorporate fairness. In the first two algorithms proportional constraints among the users' data rates are imposed and in the third algorithm minimum data rate constraints are taken into account. The proposed algorithm that maximizes the sum of the users' data rates with proportional data rate constraints is also applied to DAS and subcarriers are grouped to chunks. Simulation results sustain their effectiveness in distributing the sum data rate fairly and flexibly among users and that in DAS higher sum of the users' data rates are obtained. Finally, in the MIMO downlink the problem is formulated in order to maximize the sum of the users' data rates subject to total available power constraint with controllable bandwidth introducing system parameter α. Since this optimization should be performed in real time, an efficient, suboptimal and complexity effective algorithm is proposed which shows reasonable loss with respect to the unconstrained case where the only target is the maximization of the sum data rate and impressive profit compared to static TDMA scheme. Apart from the theoretical analysis of the above algorithms, simulation code, which was created based on realistic assumptions and simplifications, gave us results which measure the sum of the users' data rates that provide each one of the aforementioned algorithms and examine the possible appropriateness for use in specific environments. The final concluding results are that MIMO-OFDMA systems are able to offer real broadband services over the wireless communication channel.

Parameter estimation and signal detection are the two key components of a wireless communication system. They directly impact the bit-error-ratio (BER) performance of the system. Several criteria have been successfully applied for parameter estimation and signal detection. They include maximum likelihood (ML), maximum a-posteriori probability (MAP), least square (LS) and minimum mean square error (MMSE) etc. In the linear detection framework, linear MMSE (LMMSE) and LS are the most popular ones. Nevertheless, these criteria do not necessarily minimize the BER, which is one of the key aspect of any communication receiver design. Thus, minimization of BER is tantamount to an important design criterion for a wireless receiver, the minimum bit/symbol error ratio (MBER/MSER). We term this design criterion as the minimum-error-probability (MEP). In this thesis, parameter estimation and signal detection have been extensively studied based on the MEP framework for various unexplored scenar-ios of a wireless communication system. Thus, this thesis has two broad categories of explorations, first parameter estimation and then signal detection. Traditionally, the MEP criterion has been well studied in the context of the discrete signal detection in the last one decade, albeit we explore this framework for the continuous parameter es-timation. We first use this framework for channel estimation in a frequency flat fading single-input single-output (SISO) system and then extend this framework to the carrier frequency offset (CFO) estimation of multi-user MIMO OFDM system. We observe a reasonably good SNR improvement to the tune of 1 to 2.5 dB at a fixed BER (tentatively at 10−3). In this context, it is extended to the scenario of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) or MIMO-OFDM with pa-rameter estimation error statistics obtained from LMMSE only and checked its effect at the equalizer design using MEP and LMMSE criteria. In the second exploration of the MEP criterion, it is explored for signal detection in the context of MIMO-relay and MIMO systems. Various low complexity solutions are proposed to alleviate the effect of high computational complexity for the MIMO-relay. We also consider various configurations of relay like cognitive, parallel and multi-hop relaying. We also propose a data trans-mission scheme with a rate of 1/Ns (Ns is the number of antennas at the transmitter) with the help of the MEP criterion to design various components. In all these cases, we obtain considerable BER improvement compared to the existing solutions.

Multi-antenna wireless communication systems that employ a large number of antennas have recently stirred a lot of research interest. This is mainly due to the possibility of achieving very high spectral efficiency, power efficiency, and link reliability in such large-scale multiple-input multiple-output (MIMO) systems. An emerging architecture for large-scale multiuser MIMO communications is one where each base station (BS) is equipped with a large number of antennas (tens to hundreds of antennas) and the user terminals are equipped with fewer antennas (one to four antennas) each. The backhaul communication between base stations is also carried out using large number of antennas. Because of the high dimensionality of large-scale MIMO signals, the computational complexity of various transceiver operations can be prohibitively large. Therefore, low complexity techniques that scale well for transceiver signal processing in such large-scale MIMO systems are crucial. The transceiver operations of interest include signal encoding at the transmitter, and channel estimation, detection and decoding at the receiver. This thesis focuses on the design and analysis of novel low-complexity transceiver signal processing schemes for large-scale MIMO systems. In this thesis, we consider two types of large-scale MIMO systems, namely, massive MIMO systems and generalized spatial modulation MIMO (GSM-MIMO) systems. In massive MIMO, the mapping of information bits to modulation symbols is done using conventional modulation alphabets (e.g., QAM, PSK). In GSM-MIMO, few of the avail-able transmit antennas are activated in a given channel use, and information bits are conveyed through the indices of these active antennas, in addition to the bits conveyed through conventional modulation symbols. We also propose a novel modulation scheme named as precoder index modulation, where information bits are conveyed through the index of the chosen precoder matrix as well as the modulation symbols transmitted. Massive MIMO: In this part of the thesis, we propose a novel MIMO receiver which exploits channel hardening that occurs in large-scale MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of HH H become much weaker compared to the diagonal terms as the size of the channel gain matrix H increases. We exploit this phenomenon to devise a low-complexity channel estimation scheme and a message passing algorithm for signal detection at the BS receiver in massive MIMO systems. We refer to the proposed receiver as the channel hardening-exploiting message passing (CHEMP) receiver. The key novelties in the proposed CHEMP receiver are: (i) operation on the matched filtered system model, (ii) Gaussian approximation on the off-diagonal terms of the HH H matrix, and (iii) direct estimation of HH H instead of H and use of this estimate of HH H for detection The performance and complexity results show that the proposed CHEMP receiver achieves near-optimal performance in large-scale MIMO systems at complexities less than those of linear receivers like minimum mean squared error (MMSE) receiver. We also present a log-likelihood ratio (LLR) analysis that provides an analytical reasoning for this better performance of the CHEMP receiver. Further, the proposed message passing based detection algorithm enables us to combine it with low density parity check (LDPC) decoder to formulate a joint message passing based detector-decoder. For this joint detector-decoder, we design optimized irregular binary LDPC codes specific to the massive MIMO channel and the proposed receiver through EXIT chart matching. The LDPC codes thus obtained are shown to achieve improved coded bit error rate (BER) performance compared to off-the-shelf irregular LDPC codes. The performance of the CHEMP receiver degrades when the system loading factor (ratio of the number of users to the number of BS antennas) and the modulation alpha-bet size are large. It is of interest to devise receiver algorithms that work well for high system loading factors and modulation alphabet sizes. For this purpose, we propose a low-complexity factor-graph based vector message passing algorithm for signal detection. This algorithm uses a scalar Gaussian approximation of interference on the basic sys-tem model. The performance results show that this algorithm performs well for large modulation alphabets and high loading factors. We combine this detection algorithm with a non-binary LDPC decoder to obtain a joint detector-decoder, where the field size of the non-binary LDPC code is same as the size of the modulation alphabet. For this joint message passing based detector-decoder, we design optimized non-binary irregular LDPC codes tailored to the massive MIMO channel and the proposed detector. GSM-MIMO: In this part of the thesis, we consider GSM-MIMO systems in point-to-point as well as multiuser communication settings. GSM-MIMO has the advantage of requiring only fewer transmit radio frequency (RF) chains than the number of transmit antennas. We analyze the capacity of point-to-point GSM-MIMO, and obtain lower and upper bounds on the GSM-MIMO system capacity. We also derive an upper bound on the BER performance of maximum likelihood detection in GSM-MIMO systems. This bound is shown to be tight at moderate to high signal-to-noise ratios. When the number of transmit and receive antennas are large, the complexity of en-coding and decoding of GSM-MIMO signals can be prohibitively high. To alleviate this problem, we propose a low complexity GSM-MIMO encoding technique that utilizes com-binatorial number system for bits-to-symbol mapping. We also propose a novel layered message passing (LaMP) algorithm for decoding GSM-MIMO signals. Low computational complexity is achieved in the LaMP algorithm by detecting the modulation bits and the antenna index bits in two deferent layers. We then consider large-scale multiuser GSM-MIMO systems, where multiple users employ GSM at their transmitters to communicate with a BS having a large number of receive antennas. For this system, we develop computationally efficient message passing algorithms for signal detection using vector Gaussian approximation of interference. The performance results of these algorithms show that the GSM-MIMO system outperforms the massive MIMO system by several dBs for the same spectral efficiency. Precoder index modulation: It is known that the performance of a communication link can be enhanced by exploiting time diversity without reducing the rate of transmission using pseudo random phase preceding (PRPP). In order to further improve the performance of GSM-MIMO, we apply PRPP technique to GSM-MIMO systems. PRPP provides additional diversity advantage at the receiver and further improves the performance of GSM-MIMO systems. For PRPP-GSM systems, we propose methods to simultaneously precode both the antenna index bits and the modulation symbols using rectangular precoder matrices. Finally, we extend the idea of index modulation to pre-coding and propose a new modulation scheme referred to as precoder index modulation (PIM). In PIM, information bits are conveyed through the index of a prehared PRPP matrix, in addition to the information bits conveyed through the modulation symbols. PIM is shown to increase the achieved spectral efficiency, in addition to providing diver-sity advantages.