Nearest Neighbour Decoding and Pilot-Aided Channel Estimation in Stationary Gaussian Flat-Fading Channels

We study the information rates of non-coherent, stationary, Gaussian, multiple-input multiple-output (MIMO) flat-fading channels that are achievable with nearest neighbour decoding and pilot-aided channel estimation. In particular, we analyse the behaviour of these achievable rates in the limit as the signal-to-noise ratio (SNR) tends to infinity. We demonstrate that nearest neighbour decoding and pilot-aided channel estimation achieves the capacity pre-log - which is defined as the limiting ratio of the capacity to the logarithm of SNR as the SNR tends to infinity - of non-coherent multiple-input single-output (MISO) flat-fading channels, and it achieves the best so far known lower bound on the capacity pre-log of non-coherent MIMO flat-fading channels.Comment: 5 pages, 1 figure. To be presented at the IEEE International Symposium on Information Theory (ISIT), St. Petersburg, Russia, 2011. Replaced with version that will appear in the proceeding

Cooperative diversity for the cellular uplink: Sharing strategies, performance analysis, and receiver design

In this thesis, we propose data sharing schemes for the cooperative diversity in a cellular uplink to exploit diversity and enhance throughput performance of the system. Particularly, we consider new two and three-or-more user decode and forward (DF) protocols using space time block codes. We discuss two-user and three-user amplify and forward (AF) protocols and evaluate the performance of the above mentioned data sharing protocols in terms of the bit error rate and the throughput in an asynchronous code division multiple access (CDMA) cellular uplink. We develop a linear receiver for joint space-time decoding and multiuser detection that provides full diversity and near maximum-likelihood performance.;We also focus on a practical situation where inter-user channel is noisy and cooperating users can not successfully estimate other user\u27s data. We further design our system model such that, users decide not to forward anything in case of symbol errors. Channel estimation plays an important role here, since cooperating users make random estimation errors and the base station can not have the knowledge of the errors or the inter-user channels. We consider a training-based approach for channel estimation. We provide an information outage probability analysis for the proposed multi-user sharing schemes. (Abstract shortened by UMI.)

Polynomial matrix decomposition techniques for frequency selective MIMO channels

For a narrowband, instantaneous mixing multi-input, multi-output (MIMO) communications system, the channel is represented as a scalar matrix. In this scenario, singular value decomposition (SVD) provides a number of independent spatial subchannels which can be used to enhance data rates or to increase diversity. Alternatively, a QR decomposition can be used to reduce the MIMO channel equalization problem to a set of single channel equalization problems. In the case of a frequency selective MIMO system, the multipath channel is represented as a polynomial matrix. Thus conventional matrix decomposition techniques can no longer be applied. The traditional solution to this broadband problem is to reduce it to narrowband form by using a discrete Fourier transform (DFT) to split the broadband channel into N narrow uniformly spaced frequency bands and applying scalar decomposition techniques within each band. This describes an orthogonal frequency division multiplexing (OFDM) based system. However, a novel algorithm has been developed for calculating the eigenvalue decomposition of a para-Hermitian polynomial matrix, known as the sequential best rotation (SBR2) algorithm. SBR2 and its QR based derivatives allow a true polynomial singular value and QR decomposition to be formulated. The application of these algorithms within frequency selective MIMO systems results in a fundamentally new approach to exploiting spatial diversity. Polynomial matrix decomposition and OFDM based solutions are compared for a wide variety of broadband MIMO communication systems. SVD is used to create a robust, high gain communications channel for ultra low signal-to-noise ratio (SNR) environments. Due to the frequency selective nature of the channels produced by polynomial matrix decomposition, additional processing is required at the receiver resulting in two distinct equalization techniques based around turbo and Viterbi equalization. The proposed approach is found to provide identical performance to that of an existing OFDM scheme while supporting a wider range of access schemes. This work is then extended to QR decomposition based communications systems, where the proposed polynomial approach is found to not only provide superior bit-error-rate (BER) performance but significantly reduce the complexity of transmitter design. Finally both techniques are combined to create a nulti-user MIMO system that provides superior BER performance over an OFDM based scheme. Throughout the work the robustness of the proposed scheme to channel state information (CSI) error is considered, resulting in a rigorous demonstration of the capabilities of the polynomial approach

Channel estimation, data detection and carrier frequency offset estimation in OFDM systems

Orthogonal Frequency Division Multiplexing (OFDM) plays an important role in the implementation of high data rate communication. In this thesis, the problems of data detection and channel and carrier frequency offset estimation in OFDM systems are studied. Multi-symbol non-coherent data detection is studied which performs data detection by processing multiple symbols without the knowledge of the channel impulse response (CIR). For coherent data detection, the CIR needs to be estimated. Our objective in this thesis is to work on blind channel estimators which can extract the CIR using just one block of received OFDM data. A blind channel estimator for (Single Input Multi Output) SIMO OFDM systems is derived. The conditions under which the estimator is identifiable is studied and solutions to resolve the phase ambiguity of the proposed estimator are given.A channel estimator for superimposed OFDM systems is proposed and its CRB is derived. The idea of simultaneous transmission of pilot and data symbols on each subcarrier, the so called superimposed technique, introduces the efficient use of bandwidth in OFDM context. Pilot symbols can be added to data symbols to enable CIR estimation without sacrificing the data rate. Despite the many advantages of OFDM, it suffers from sensitivity to carrier frequency offset (CFO). CFO destroys the orthogonality between the subcarriers. Thus, it is necessary for the receiver to estimate and compensate for the frequency offset. Several high accuracy estimators are derived. These include CFO estimators, as well as a joint iterative channel/CFO estimator/data detector for superimposed OFDM. The objective is to achieve CFO estimation with using just one OFDM block of received data and without the knowledge of CIR

Physical and Link Layer Implications in Vehicle Ad Hoc Networks

Vehicle Ad hoc Networks (V ANET) have been proposed to provide safety on the road and deliver road traffic information and route guidance to drivers along with commercial applications. However the challenges facing V ANET are numerous. Nodes move at high speeds, road side units and basestations are scarce, the topology is constrained by the road geometry and changes rapidly, and the number of nodes peaks suddenly in traffic jams. In this thesis we investigate the physical and link layers of V ANET and propose methods to achieve high data rates and high throughput. For the physical layer, we examine the use of Vertical BLAST (VB LAST) systems as they provide higher capacities than single antenna systems in rich fading environments. To study the applicability of VB LAST to VANET, a channel model was developed and verified using measurement data available in the literature. For no to medium line of sight, VBLAST systems provide high data rates. However the performance drops as the line of sight strength increases due to the correlation between the antennas. Moreover, the performance of VBLAST with training based channel estimation drops as the speed increases since the channel response changes rapidly. To update the channel state information matrix at the receiver, a channel tracking algorithm for flat fading channels was developed. The algorithm updates the channel matrix thus reducing the mean square error of the estimation and improving the bit error rate (BER). The analysis of VBLAST-OFDM systems showed they experience an error floor due to inter-carrier interference (lCI) which increases with speed, number of antennas transmitting and number of subcarriers used. The update algorithm was extended to VBLAST -OFDM systems and it showed improvements in BER performance but still experienced an error floor. An algorithm to equalise the ICI contribution of adjacent subcarriers was then developed and evaluated. The ICI equalisation algorithm reduces the error floor in BER as more subcarriers are equalised at the expense of more hardware complexity. The connectivity of V ANET was investigated and it was found that for single lane roads, car densities of 7 cars per communication range are sufficient to achieve high connectivity within the city whereas 12 cars per communication range are required for highways. Multilane roads require higher densities since cars tend to cluster in groups. Junctions and turns have lower connectivity than straight roads due to disconnections at the turns. Although higher densities improve the connectivity and, hence, the performance of the network layer, it leads to poor performance at the link layer. The IEEE 802.11 p MAC layer standard under development for V ANET uses a variant of Carrier Sense Multiple Access (CSMA). 802.11 protocols were analysed mathematically and via simulations and the results prove the saturation throughput of the basic access method drops as the number of nodes increases thus yielding very low throughput in congested areas. RTS/CTS access provides higher throughput but it applies only to unicast transmissions. To overcome the limitations of 802.11 protocols, we designed a protocol known as SOFT MAC which combines Space, Orthogonal Frequency and Time multiple access techniques. In SOFT MAC the road is divided into cells and each cell is allocated a unique group of subcarriers. Within a cell, nodes share the available subcarriers using a combination of TDMA and CSMA. The throughput analysis of SOFT MAC showed it has superior throughput compared to the basic access and similar to the RTS/CTS access of 802.11

Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems

Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER

Frequency synchronization for multiuser MIMO-OFDM system using Bayesian approach

This paper addresses the problem of frequency synchronization in multiuser multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. Different from existing work, a Bayesian approach is used in the parameter estimation problem. In this paper, the Bayes estimator for carrier frequency offset (CFO) estimation is proposed and the Bayesian Cramér-Rao bound (BCRB) is also derived in closed form. Direct implementation of the resultant estimation scheme with conventional methods is challenging since a high degree of mathematical sophistication is always required. To solve this problem, the Gibbs sampler is exploited with an efficient sample generation method. Simulation results illustrate the effectiveness of the proposed estimation scheme. ©2010 IEEE.published_or_final_versionThe 2010 IEEE Global Telecommunications Conference (GLOBECOM 2010), Miami, FL., 6-10 December 2010. In Globecom. IEEE Conference and Exhibition, 2010, p. 1-