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![10: QPSK and 16-QAM signal constellations, gray coded [EUa]](profile/Tewelde-Assefa/publication/302959148/figure/fig10/AS:360847768604679@1463044220482/QPSK-and-16-QAM-signal-constellations-gray-coded-EUa.png)
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![Figure 2.11: HARQ processes behaviour in LTE [tel]](profile/Tewelde-Assefa/publication/302959148/figure/fig11/AS:360847768604680@1463044220526/HARQ-processes-behaviour-in-LTE-tel_Q320.jpg)
![Figure 2.7: Localized vs Distributed Mapping [kok]](profile/Tewelde-Assefa/publication/302959148/figure/fig7/AS:360847768604676@1463044220329/Localized-vs-Distributed-Mapping-kok_Q320.jpg)
![Figure 2.5: LTE Access Network Architecture [BAEG]](profile/Tewelde-Assefa/publication/302959148/figure/fig5/AS:360847768604674@1463044220064/LTE-Access-Network-Architecture-BAEG_Q320.jpg)
![Figure 2.2: Functional Split of EPS Entities [lteg]](profile/Tewelde-Assefa/publication/302959148/figure/fig2/AS:360847764410369@1463044219982/Functional-Split-of-EPS-Entities-lteg_Q320.jpg)
![Figure 2.6: OFDM transmitter and receiver structure [sin]](profile/Tewelde-Assefa/publication/302959148/figure/fig6/AS:360847768604675@1463044220272/OFDM-transmitter-and-receiver-structure-sin_Q320.jpg)
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Citations
... There are also various works on the experimental performance analysis of QoS in the literature. In [27], the authors study the QoS performance of LTE networks under different load scenarios. In [25], the focus is to analyze the correlation between UE position, network load and QoS performances for video specific services. ...
Differentiated quality-of-Service (QoS) techniques are widely used to distinguish between different service classes and prioritize service needs in mobile networks. Mobile Network Operators (MNOs) utilize QoS techniques to develop strategies that are supported by the mobile network infrastructure. However, QoS deployment strategy can ensure that the radio resources provided by the base station are easily consumed if it is not used correctly or when different techniques are used all together. In this paper, we propose a scheduling algorithm and compare two different QoS deployment strategies for prioritized User Equipment (UEs) (with higher scheduling rates and dedicated bandwidth) that MNOs can use in the current infrastructure, using a commercial real-time Long Term Evolution (LTE) network in different test scenarios. Moreover, we expose the real-time user experience in terms of uplink throughput and analyze results of the UE's real-time key performance indicators (KPIs) in detail. Experiment results are evaluated considering the implications of different QoS support types on network coverage and capacity planning optimizations. Our results demonstrate that even though pre-configured resource allocations can be given to prioritize UEs, the experience of all the UEs can be affected unexpectedly in the presence of many UEs who have received different QoS deployment support. Our experimental observations have revealed that location of the UEs with respect to Base Station (BS) and the availability of dedicated bandwidth UEs inside cell may have implications on the apriori defined resource allocation strategies of the other UEs.
... The LTE-A systems also aims at the effective utilization of the resources with the spectrum reuse and successful transmission even at the cell edges. LTE-A network is the enhancement to the LTE network with the technologies of multi-antenna system of Multiple Input and Multiple Output (MIMO), increasing the bandwidth with carrier aggregation (CA), heterogeneous network and relaying technology [10,11].The Network Coding techniques of transmitting the data to receivers in reduced time slots with the MIMO reduces the overall delay in the network [12,13]. The heart of LTE-A network is the MIMO technology to increase the overall capacity of the network. ...
The primary intention of the paper is to explore on various Multi-Layer MIMO approaches for the higher system performance. MIMO technique is said to be the key technology in LTE-A to achieve the spatial diversity in the system. Multi-Layer MIMO is the enhancement to the MIMO technology where multiple streams of data could be transferred to different layers for optimization with increased capacity in the network in high SNR condition. In a massive MIMO system, the cell interference hinders the system performance due to high channel dimensionality. The main design objective of the Multi-Layer MIMO techniques studied is to reduce the Cell Interference with lower complexity.
