Signal processing for future MIMO-OFDM wireless communication systems

The combination of multiple-input multiple-output (MIMO) technology and orthogonal frequency division multiplexing (OFDM) is likely to provide the air-interface solution for future broadband wireless systems. A major challenge for MIMO-OFDM systems is the problem of multi-access interference (MAI) induced by the presence of multiple users transmitting over the same bandwidth. Novel signal processing techniques are therefore required to mitigate MAI and thereby increase link performance. A background review of space-time block codes (STBCs) to lever age diversity gain in MIMO systems is provided together with an introduction to OFDM. The link performance of an OFDM system is also shown to be sensitive to time-variation of the channel. Iterative minimum mean square error (MMSE) receivers are therefore proposed to overcome such time-variation. In the context of synchronous uplink transmission, a new two-step hard-decision interference cancellation receiver for STBC MIMO-OFDM is shown to have robust performance and relatively low complexity. Further improvement is obtained through employing error control coding methods and iterative algorithms. A soft output multiuser detector based on MMSE interference suppression and error correction coding at the first stage is shown by frame error rate simulations to provide significant performance improvement over the classical linear scheme. Finally, building on the "turbo principle", a low-complexity iterative interference cancellation and detection scheme is designed to provide a good compromise between the exponential computational complexity of the soft interference cancellation linear MMSE algorithm and the near-capacity performance of a scheme which uses iterative turbo processing for soft interference suppression in combination with multiuser detection.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Signal processing for future MIMO-OFDM wireless communication systems

The combination of multiple-input multiple-output (MIMO) technology and orthogonal frequency division multiplexing (OFDM) is likely to provide the air-interface solution for future broadband wireless systems. A major challenge for MIMO-OFDM systems is the problem of multi-access interference (MAI) induced by the presence of multiple users transmitting over the same bandwidth. Novel signal processing techniques are therefore required to mitigate MAI and thereby increase link performance. A background review of space-time block codes (STBCs) to lever age diversity gain in MIMO systems is provided together with an introduction to OFDM. The link performance of an OFDM system is also shown to be sensitive to time-variation of the channel. Iterative minimum mean square error (MMSE) receivers are therefore proposed to overcome such time-variation. In the context of synchronous uplink transmission, a new two-step hard-decision interference cancellation receiver for STBC MIMO-OFDM is shown to have robust performance and relatively low complexity. Further improvement is obtained through employing error control coding methods and iterative algorithms. A soft output multiuser detector based on MMSE interference suppression and error correction coding at the first stage is shown by frame error rate simulations to provide significant performance improvement over the classical linear scheme. Finally, building on the "turbo principle", a low-complexity iterative interference cancellation and detection scheme is designed to provide a good compromise between the exponential computational complexity of the soft interference cancellation linear MMSE algorithm and the near-capacity performance of a scheme which uses iterative turbo processing for soft interference suppression in combination with multiuser detection

Joint signal detection and channel estimation in rank-deficient MIMO systems

L'évolution de la prospère famille des standards 802.11 a encouragé le développement des technologies appliquées aux réseaux locaux sans fil (WLANs). Pour faire face à la toujours croissante nécessité de rendre possible les communications à très haut débit, les systèmes à antennes multiples (MIMO) sont une solution viable. Ils ont l'avantage d'accroître le débit de transmission sans avoir recours à plus de puissance ou de largeur de bande. Cependant, l'industrie hésite encore à augmenter le nombre d'antennes des portables et des accésoires sans fil. De plus, à l'intérieur des bâtiments, la déficience de rang de la matrice de canal peut se produire dû à la nature de la dispersion des parcours de propagation, ce phénomène est aussi occasionné à l'extérieur par de longues distances de transmission. Ce projet est motivé par les raisons décrites antérieurement, il se veut un étude sur la viabilité des transcepteurs sans fil à large bande capables de régulariser la déficience de rang du canal sans fil. On vise le développement des techniques capables de séparer M signaux co-canal, même avec une seule antenne et à faire une estimation précise du canal. Les solutions décrites dans ce document cherchent à surmonter les difficultés posées par le medium aux transcepteurs sans fil à large bande. Le résultat de cette étude est un algorithme transcepteur approprié aux systèmes MIMO à rang déficient

Sparse nonlinear optimization for signal processing and communications

This dissertation proposes three classes of new sparse nonlinear optimization algorithms for network echo cancellation (NEC), 3-D synthetic aperture radar (SAR) image reconstruction, and adaptive turbo equalization in multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications, respectively. For NEC, the proposed two proportionate affine projection sign algorithms (APSAs) utilize the sparse nature of the network impulse response (NIR). Benefiting from the characteristics of l₁-norm optimization, affine projection, and proportionate matrix, the new algorithms are more robust to impulsive interferences and colored input than the conventional adaptive algorithms. For 3-D SAR image reconstruction, the proposed two compressed sensing (CS) approaches exploit the sparse nature of the SAR holographic image. Combining CS with the range migration algorithms (RMAs), these approaches can decrease the load of data acquisition while recovering satisfactory 3-D SAR image through l₁-norm optimization. For MIMO UWA communications, a robust iterative channel estimation based minimum mean-square-error (MMSE) turbo equalizer is proposed for large MIMO detection. The MIMO channel estimation is performed jointly with the MMSE equalizer and the maximum a posteriori probability (MAP) decoder. The proposed MIMO detection scheme has been tested by experimental data and proved to be robust against tough MIMO channels. --Abstract, page iv

Enhanced Air-Interfaces for Fifth Generation Mobile Broadband Communication

In broadband wireless multicarrier communication systems, intersymbol interference (ISI) and intercarrier interference (ICI) should be reduced. In orthogonal frequency division multiplexing (OFDM), the cyclic prefix (CP) guarantees to reduce the ISI interference. However, the CP reduces spectral and power efficiency. In this thesis, iterative interference cancellation (IIC) with iterative decoding is used to reduce ISI and ICI from the received signal in multicarrier modulation (MCM) systems. Alternative schemes as well as OFDM with insufficient CP are considered; filter bank multicarrier (FBMC/Offset QAM) and discrete wavelet transform based multicarrier modulation (DWT-MCM). IIC is applied in these different schemes. The required components are calculated from either the hard decision of the demapper output or the estimated decoded signal. These components are used to improve the received signal. Channel estimation and data detection are very important parts of the receiver design of the wireless communication systems. Iterative channel estimation using Wiener filter channel estimation with known pilots and IIC is used to estimate and improve data detection. Scattered and interference approximation method (IAM) preamble pilot are using to calculate the estimated values of the channel coefficients. The estimated soft decoded symbols with pilot are used to reduce the ICI and ISI and improve the channel estimation. The combination of Multi-Input Multi-Output MIMO and OFDM enhances the air-interface for the wireless communication system. In a MIMO-MCM scheme, IIC and MIMO-IIC-based successive interference cancellation (SIC) are proposed to reduce the ICI/ISI and cross interference to a given antenna from the signal transmitted from the target and the other antenna respectively. The number of iterations required can be calculated by analysing the convergence of the IIC with the help of EXtrinsic Information Transfer (EXIT) charts. A new EXIT approach is proposed to provide a means to define performance for a given outage probability on quasi-static channels

Channel Estimation in Coded Modulation Systems

With the outstanding performance of coded modulation techniques in fading channels, much research efforts have been carried out on the design of communication systems able to operate at low signal-to-noise ratios (SNRs). From this perspective, the so-called iterative decoding principle has been applied to many signal processing tasks at the receiver: demodulation, detection, decoding, synchronization and channel estimation. Nevertheless, at low SNRs, conventional channel estimators do not perform satisfactorily. This thesis is mainly concerned with channel estimation issues in coded modulation systems where different diversity techniques are exploited to combat fading in single or multiple antenna systems. First, for single antenna systems in fast time-varying fading channels, the thesis focuses on designing a training sequence by exploiting signal space diversity (SSD). Motivated by the power/bandwidth efficiency of the SSD technique, the proposed training sequence inserts pilot bits into the coded bits prior to constellation mapping and signal rotation. This scheme spreads the training sequence during a transmitted codeword and helps the estimator to track fast variation of the channel gains. A comprehensive comparison between the proposed training scheme and the conventional training scheme is then carried out, which reveals several interesting conclusions with respect to both error performance of the system and mean square error of the channel estimator. For multiple antenna systems, different schemes are examined in this thesis for the estimation of block-fading channels. For typical coded modulation systems with multiple antennas, the first scheme makes a distinction between the iteration in the channel estimation and the iteration in the decoding. Then, the estimator begins iteration when the soft output of the decoder at the decoding iteration meets some specified reliability conditions. This scheme guarantees the convergence of the iterative receiver with iterative channel estimator. To accelerate the convergence process and decrease the complexity of successive iterations, in the second scheme, the channel estimator estimates channel state information (CSI) at each iteration with a combination of the training sequence and soft information. For coded modulation systems with precoding technique, in which a precoder is used after the modulator, the training sequence and data symbols are combined using a linear precoder to decrease the required training overhead. The power allocation and the placement of the training sequence to be precoded are obtained based on a lower bound on the mean square error of the channel estimation. It is demonstrated that considerable performance improvement is possible when the training symbols are embedded within data symbols with an equi-spaced pattern. In the last scheme, a joint precoder and training sequence is developed to maximize the achievable coding gain and diversity order under imperfect CSI. In particular, both the asymptotic performance behavior of the system with the precoded training scheme under imperfect CSI and the mean square error of the channel estimation are derived to obtain achievable diversity order and coding gain. Simulation results demonstrate that the joint optimized scheme outperforms the existing training schemes for systems with given precoders in terms of error rate and the amount of training overhead