Papers by Goodwell Kapfunde
2021 20th International Conference on Ubiquitous Computing and Communications (IUCC/CIT/DSCI/SmartCNS), Dec 1, 2021
IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, 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.
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 accou...
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Papers by Goodwell Kapfunde