Volker Kühn

MMSE extension of V-BLAST based on sorted QR decomposition

In rich-scattering environments, layered space-time architectures like the BLAST system may exploit the capacity advantage of multiple antenna systems. We present a novel, computationally efficient algorithm for detecting V-BLAST architectures with respect to the MMSE criterion. It utilizes a sorted QR decomposition of the channel matrix and leads to a simple successive detection structure. The new algorithm needs only a fraction of computational effort compared to the standard V-BLAST algorithm and achieves the same error performance.

Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction

In recent publications the use of lattice-reduction for signal detection in multiple antenna systems has been proposed. In this paper, we adopt these lattice-reduction-aided schemes to the MMSE criterion. We show that an obvious way to do this is infeasible and propose an alternative method based on an extended system model, which in conjunction with simple successive interference cancellation nearly reaches the performance of maximum-likelihood detection. Furthermore, we demonstrate that, a sorted QR decomposition can significantly reduce the computational effort associated with lattice-reduction. Thus, the new algorithm clearly outperforms existing methods with comparable complexity.

Reduced complexity MMSE detection for BLAST architectures

Theoretical and experimental studies have shown that layered space-time architectures like the BLAST system can exploit the capacity advantage of multiple antenna systems in rich-scattering environments. We present a new efficient algorithm for detecting such architectures with respect to the MMSE criterion. This algorithm utilizes a sorted QR decomposition of the channel matrix and leads to a simple successive detection structure. The algorithm needs only a fraction of the computational effort compared to the standard V-BLAST algorithm and achieves the same bit error performance.

Wireless Communications over Mimo Channels: Applications to Cdma And Multiple Antenna Systems

Preface. Acknowledgements. List of Abbreviations. List of Symbols. 1. Introduction to Digital Communications. 1.1 Basic System Model. 1.2 Characteristics of Mobile Radio Channels. 1.3 Signal Detection. 1.3.1 Optimal Decision Criteria. 1.4 Digital Linear Modulation. 1.5 Diversity. 1.6 Summary. 2. Information Theory. 2.1 Basic Definitions. 2.2 Channel Coding Theorem for SISO Channels. 2.3 Channel Capacity of MIMO Systems. 2.4 Channel Capacity for Multi-User Communications. 2.5 Summary. 3. Forward Error Correction Coding. 3.1 Introduction. 3.2 Linear Block Codes. 3.3 Convolutional Codes. 3.4 Soft-Output Decoding of Binary Codes. 3.5 Performance Evaluation of Linear Codes. 3.6 Concatenated Codes. 3.7 Low Density Parity Check (LDPC) Codes. 3.8 Summary. 4. Code Division Multiple Access. 4.1 Fundamentals. 4.2 OFDM-CDMA. 4.3 Low Rate Channel Coding in CDMA Systems. 4.4 Uplink Capacity of CDMA Systems. 4.5 Summary. 5. Multi-User Detection in CDMA Systems. 5.1 Optimum Detection. 5.2 Linear Multi-User Detection. 5.3 Nonlinear Iterative Multi-User Detection. 5.4 Combining Linear MUD and Nonlinear SIC. 5.5 Summary. 6. Multiple Antenna Systems. 6.1 Introduction . 6.2 Spatial Diversity Concepts. 6.3 Multi-Layer Transmission. 6.4 Linear Dispersion Codes. 6.5 Information Theoretic Analysis. 6.6 Summary. Appendix A: Channel Models. A.1 Equivalent Baseband Representation. A.2 Typical Propagation Profiles for Outdoor Mobile Radio Channels. A.3 Moment Generating Function for Ricean Fading. Appendix B: Derivations for Information Theory. B.1 Chain Rule for Entropies. B.2 Chain Rule for Information. B.3 Data Processing Theorem. Appendix C: Linear Algebra. C.1 Selected Basics. C.2 Householder Reflections and Givens Rotation. C.3 LLL Lattice-Reduction. Bibliography. Index.

MMSE-based lattice-reduction for near-ML detection of MIMO systems

Recently the use of lattice-reduction for signal detection in multiple antenna systems has been proposed. In this paper, we adopt these lattice-reduction aided schemes to the MMSE criterion. We show that an obvious way to do this is suboptimum and propose an alternative method based on an extended system model. In conjunction with simple successive interference cancellation this scheme almost reaches the performance of maximum-likelihood detection. Furthermore, we demonstrate that the application of sorted QR decomposition (SQRD) as a initialization step can significantly reduce the computational effort associated with lattice-reduction. Thus, the new algorithm clearly outperforms existing methods with comparable complexity.

Combined MMSE-PIC in coded OFDM-CDMA systems

The performance of linear multiuser detection (MUD) and nonlinear parallel interference cancellation (PIC) is analyzed for a quasi synchronous OFDM-CDMA uplink transmission. Specifically, we investigate two different approaches concerning the combination of linear MUD techniques such as the decorrelator and the MMSE approach with nonlinear parallel interference cancellation (PIC). It is pointed out that OFDM-CDMA systems offer great advantages over single carrier systems due to flat fading conditions on each subcarrier leading to much lower implementation costs of MUD techniques. Assuming perfectly known channel impulse responses for each user and a rough synchronization, it turns out that the application of the MMSE-MUD filter leads to an insufficient equalization of the channel. Therefore, we propose an approach where the PIC loop works directly on the channel output and the MMSE filter is only active in the initial iteration loop. With this approach, the combination of linear MMSE-MUD and PIC shows excellent performance even for very high system loads.The performance of linear multiuser detection (MUD) and nonlinear parallel interference cancellation (PIC) is analyzed for a quasi synchronous OFDM-CDMA uplink transmission. Specifically, we investigate two different approaches concerning the combination of linear MUD techniques such as the decorrelator and the MMSE approach with nonlinear parallel interference cancellation (PIC). It is pointed out that OFDM-CDMA systems offer great advantages over single carrier systems due to flat fading conditions on each subcarrier leading to much lower implementation costs of MUD techniques. Assuming perfectly known channel impulse responses for each user and a rough synchronization, it turns out that the application of the MMSE-MUD filter leads to an insufficient equalization of the channel. Therefore, we propose an approach where the PIC loop works directly on the channel output and the MMSE filter is only active in the initial iteration loop. With this approach, the combination of linear MMSE-MUD and PIC shows excellent performance even for very high system loads.

Blind and nonblind turbo estimation for fast fading GSM channels

Wireless communication systems such as global system for mobile (GSM) communications are playing a growing role for data transmission. In order to ensure reliable transmission, the channel impulse response has to be estimated accurately. This is a difficult task particularly for fast fading channels caused by high-speed mobile units. We deal with the application of nonblind and blind channel estimation approaches to identify the full rate data Traffic CHannel (TCHF9.6) of GSM. We present a new iterative channel estimation scheme leading to a significant performance improvement especially for high-speed propagation with Doppler frequencies up to 500 Hz. Furthermore, it is shown that blind channel estimation schemes could be as efficient as nonblind methods when regarding bit error rates (BERs) after channel decoding in terms of the E~/sub b//N/sub 0/ ratio. Moreover, a solution for the scalar ambiguity inherent in all blind estimation approaches is suggested.

On the robustness of lattice-reduction aided detectors in correlated MIMO systems

Recently the use of lattice-reduction for signal detection in multiple antenna systems has been proposed. In combination with simple successive interference cancellation this scheme achieves near maximum-likelihood performance. To this end, the given MIMO channel is transformed into an almost orthogonal matrix leading to less noise enhancement within the detection. In this paper, we investigate the performance of common and lattice-reduction-aided detection schemes for correlated fading channels. We show, that the new scheme achieves significant gain in comparison to common algorithms. Thus, the new algorithm clearly outperforms existing methods with comparable complexity and is also more robust with respect to spatial correlation.

Evaluating the performance of turbo codes and turbo-coded modulation in a DS-CDMA environment

Turbo codes have received great attention due to their outstanding performance. Unfortunately, a high performance is associated with large transmission delays, prohibiting an application for speech transmission. Hence, the aim of this paper is the comparison of turbo codes employing short interleavers with convolutional codes in terms of bit error rate performance and computational effort. Additionally, a pragmatic approach of bandwidth-efficient turbo-coded modulation is considered. Analyzing the structure of the transmitter and receiver, interesting results are presented concerning the design of the mapper. Furthermore, a new very simple soft-output demodulation algorithm is derived. In order to compare turbo codes with convolutional codes under realistic conditions, both are embedded in a direct sequence (DS) code division multiple access system. Besides this comparison, a compromise between a high coding gain (low code rate) and high direct-sequence spreading is worked out, including the consideration of the turbo-coded modulation scheme. Simulation results indicate that turbo codes with small block interleavers do not outperform conventional convolutional codes. Furthermore, it is shown that for coherent demodulation, low code rates and low DS spreading is superior to high code rates and high DS spreading.

On phase correct blind deconvolution exploiting channel coding

In this paper we derive an algorithm, which estimates the channel blindly exploiting the statistical dependencies of the transmitted signal caused by channel coding. An additional feature of this algorithm is that in contrast to most blind deconvolution algorithms phase correct estimates can be obtained. The error performance of the proposed algorithm depends on the characteristics of the channel code. If the code has appropriate properties, which is true for some convolutional codes as well as for several block codes, e.g. especially low-density parity check codes (LDPC), the proposed algorithm performs similarly or slightly better in comparison to higher order statics based algorithms.