Goodwell Kapfunde Kapfunde - Academia.edu (original) (raw)
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Papers by Goodwell Kapfunde Kapfunde
2021 20th International Conference on Ubiquitous Computing and Communications (IUCC/CIT/DSCI/SmartCNS)
The LRAD-MMSE-SIC-SE-SD (Lattice Reduction Aided Detection - Minimum Mean Squared Error-Successiv... more The LRAD-MMSE-SIC-SE-SD (Lattice Reduction Aided Detection - Minimum Mean Squared Error-Successive Interference Cancellation - Schnorr Euchner - Sphere Decoder) detection scheme that introduces a trade-off between performance and computational complexity is proposed for Multiple-Input Multiple-Output (MIMO) in this paper. The Lenstra-Lenstra-Lovász (LLL) algorithm is employed to orthogonalise the channel matrix by transforming the signal space of the received signal into an equivalent reduced signal space. A novel Lattice Reduction aided SE-SD probing for the Closest Lattice Point in the transformed reduced signal space is hereby proposed. Correspondingly, the computational complexity of the proposed LRAD-MMSE-SIC-SE-SD detection scheme is independent of the constellation size while it is polynomial with reference to the number of antennas, and signal-to-noise-ratio (SNR). Performance results of the detection scheme indicate that SD complexity is significantly reduced at only marginal performance penalty.
The search for the closest lattice point arises in many communication problems, and is known to b... more 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 performancecomplexity 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
2016 ESA Workshop on Aerospace EMC (Aerospace EMC), 2016
In situ magnetic field measurements are of critical importance to unanswered questions on the inn... more In situ magnetic field measurements are of critical importance to unanswered questions on the inner heliosphere, such as: how the corona and solar wind are accelerated and heated; how the solar magnetic field evolves over a solar cycle; and how this field links into space. However, accurate spacecraft magnetometer measurements require reliable in-flight calibration. The magnetic interference caused by reaction wheels on magnetometer measurements in space is well known, and a common mitigation method is to use magnetic shielding. However, the presence of high-permeability material in-flight has the side-effect of distorting the true ambient field. We present a theoretical analysis of this distortion, and suggest a transfer function that can be used to recover the ambient field from the distorted dataset. Experimental measurements on a shield prototype for the Solar Orbiter mission agree with predictions to within an order of magnitude, demonstrating a distortion of approximately 1 part in 104.
2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2012
The Maximum Likelihood (ML) detector is a detection criteria which yields an optimal solution to ... more The Maximum Likelihood (ML) detector is a detection criteria which yields an optimal solution to Multiple-Input Multiple-Output (MIMO) systems but however, at the expense of its NP-hard complexity. Instead, the Sphere Decoder (SD) was proposed as an efficient algorithm for finding the solution to the ML detection problem in MIMO digital communication systems. Unlike the ML detector whose complexity rises exponentially with the number of transmit and receive antennas, the complexity of the SD is polynomial for both finite and infinite lattices which makes real-time implementation of the ML detector practical. The choice of the initial radius for the SD has a significant impact on the complexity and the performance of the SD. However, the problem of selecting the initial radius is NP-hard itself. In this paper, we propose a simple Schnorr-Euchner SD (SE-SD) with a novel radius based on the received signal, noise statistics, number of transmit antennas, the energy of the transmitted symbols and on the channel matrix. The proposed method does not only reduce the complexity of the SD, but it also improves the bit error rate performance of the SD, particularly at low signal-to-noise ratios (SNR). To demonstrate the feasibility of our proposed method, we compare our method with the conventional SD radius and with other methods proposed in the literature.
2021 20th International Conference on Ubiquitous Computing and Communications (IUCC/CIT/DSCI/SmartCNS)
The LRAD-MMSE-SIC-SE-SD (Lattice Reduction Aided Detection - Minimum Mean Squared Error-Successiv... more The LRAD-MMSE-SIC-SE-SD (Lattice Reduction Aided Detection - Minimum Mean Squared Error-Successive Interference Cancellation - Schnorr Euchner - Sphere Decoder) detection scheme that introduces a trade-off between performance and computational complexity is proposed for Multiple-Input Multiple-Output (MIMO) in this paper. The Lenstra-Lenstra-Lovász (LLL) algorithm is employed to orthogonalise the channel matrix by transforming the signal space of the received signal into an equivalent reduced signal space. A novel Lattice Reduction aided SE-SD probing for the Closest Lattice Point in the transformed reduced signal space is hereby proposed. Correspondingly, the computational complexity of the proposed LRAD-MMSE-SIC-SE-SD detection scheme is independent of the constellation size while it is polynomial with reference to the number of antennas, and signal-to-noise-ratio (SNR). Performance results of the detection scheme indicate that SD complexity is significantly reduced at only marginal performance penalty.
The search for the closest lattice point arises in many communication problems, and is known to b... more 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 performancecomplexity 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
2016 ESA Workshop on Aerospace EMC (Aerospace EMC), 2016
In situ magnetic field measurements are of critical importance to unanswered questions on the inn... more In situ magnetic field measurements are of critical importance to unanswered questions on the inner heliosphere, such as: how the corona and solar wind are accelerated and heated; how the solar magnetic field evolves over a solar cycle; and how this field links into space. However, accurate spacecraft magnetometer measurements require reliable in-flight calibration. The magnetic interference caused by reaction wheels on magnetometer measurements in space is well known, and a common mitigation method is to use magnetic shielding. However, the presence of high-permeability material in-flight has the side-effect of distorting the true ambient field. We present a theoretical analysis of this distortion, and suggest a transfer function that can be used to recover the ambient field from the distorted dataset. Experimental measurements on a shield prototype for the Solar Orbiter mission agree with predictions to within an order of magnitude, demonstrating a distortion of approximately 1 part in 104.
2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2012
The Maximum Likelihood (ML) detector is a detection criteria which yields an optimal solution to ... more The Maximum Likelihood (ML) detector is a detection criteria which yields an optimal solution to Multiple-Input Multiple-Output (MIMO) systems but however, at the expense of its NP-hard complexity. Instead, the Sphere Decoder (SD) was proposed as an efficient algorithm for finding the solution to the ML detection problem in MIMO digital communication systems. Unlike the ML detector whose complexity rises exponentially with the number of transmit and receive antennas, the complexity of the SD is polynomial for both finite and infinite lattices which makes real-time implementation of the ML detector practical. The choice of the initial radius for the SD has a significant impact on the complexity and the performance of the SD. However, the problem of selecting the initial radius is NP-hard itself. In this paper, we propose a simple Schnorr-Euchner SD (SE-SD) with a novel radius based on the received signal, noise statistics, number of transmit antennas, the energy of the transmitted symbols and on the channel matrix. The proposed method does not only reduce the complexity of the SD, but it also improves the bit error rate performance of the SD, particularly at low signal-to-noise ratios (SNR). To demonstrate the feasibility of our proposed method, we compare our method with the conventional SD radius and with other methods proposed in the literature.