Performance Analysis and Investigation of Digital Symbol Detection Techniques for Single and Multi-carrier Modulations
| dc.contributor.advisor | Dereje, Hailemariam (PhD) | |
| dc.contributor.author | Gidey, Tesfay | |
| dc.date.accessioned | 2020-03-10T11:06:31Z | |
| dc.date.accessioned | 2023-11-28T14:09:11Z | |
| dc.date.available | 2020-03-10T11:06:31Z | |
| dc.date.available | 2023-11-28T14:09:11Z | |
| dc.date.issued | 2017-10 | |
| dc.description.abstract | During symbol transmission we may use single carrier or multi-carrier modulation. In case of single carrier transmission all users share the same transmission medium and this causes the problem of Inter Symbol Interference (ISI) which leads to error in reception. In case of multicarrier transmission there is Multiple Access Interference (MAI). In several digital communication problems, the received signal is given by a linear combination of the data symbols corrupted by channel effects. So the received symbol may be affected by transmission channel noise, interference, distortion, bit synchronization problems, attenuation, and wireless multipath-fading. Therefore efficient demodulation and symbol detection strategies are very necessary. This thesis work on symbol detection is done as per the request of Information Networks Security Agency (INSA) of Ethiopia. The industry wants to implement advanced digital receiver for local use. So the industry main aim is to review, investigate, and implement efficient symbol detection algorithms. In this paper we have considered a class of single carrier and multi-carrier symbol detection algorithms and compare their performance in terms of Bit Error Rate (BER) and Signal to Noise Ratio (SNR) of various modulation type and order. M-ary PSK and M-ary QAM have been simulated with optimum and sub-optimum detectors like Maximum-Likelihood (ML), Minimum Mean Square Error (MMSE) and Zero Forcing (ZF) detector. From our findings, for the single carrier single user case for additive White Gaussian Noise (AWGN) channel the BER at 15dB is 10 , which is acceptable. Again for the case of Rayleigh Fading channel at 35dB still we have a BER of 10 -3 . In the case of multicarrier multi user (MCCDMA) detection over Rayleigh fading channel, we have been shown how the three different detectors behave in performance and complexity analysis. Finally, it can be seen that the most complex and the best performing detector, is the Maximum Likelihood detector. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/21093 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Symbol detection | en_US |
| dc.subject | Single user | en_US |
| dc.subject | Single-carrier | en_US |
| dc.subject | Multi-carrier | en_US |
| dc.subject | Multi-user | en_US |
| dc.subject | Mary Modulation | en_US |
| dc.subject | maximum likelihood detection | en_US |
| dc.subject | optimal and sub-optimal detectors | en_US |
| dc.subject | BER | en_US |
| dc.subject | SNR | en_US |
| dc.subject | Complexity analysis | en_US |
| dc.subject | MATLAB | en_US |
| dc.title | Performance Analysis and Investigation of Digital Symbol Detection Techniques for Single and Multi-carrier Modulations | en_US |
| dc.type | Thesis | en_US |