Multi-Antenna System Performance and Impairments in Long Term Evolution Radio Access Networks Using the Extended Spatial Channel Model
Bibliographic record
Abstract
Consumer demand for rich content delivered to portable wireless devices is pushing the wireless industry and researchers to find ways to improve the efficiency of wireless networks.New technologies like LTE and LTE-Advanced are being refined and deployed to meet demands.This thesis studies three important areas of wireless communications using LTE; phase noise, Doppler and link adaptation and the performance of various multiple antenna systems.The thesis focuses on the performance of 4 base station antennas and results obtained with the advanced 3 rd Generation Partnership Project's (3GPP) extended spatial channel model (SCME).Simulations show the effect of each impairment and configuration on the LTE physical downlink shared channel.The best performing antenna configuration evaluated is the 4-transmitter, 4-port, correlated cross-polarized BS antenna when TM4's closed-loop spatial multiplexing is used.The results show that a 4 antenna BS setup provides gain over 2 BS antennas, despite the additional reference signal overhead, due to the greater set of precoding matrices available with 4 antenna ports.When only 2 ports are available, TM3's open-loop spatial multiplexing (OLSM) performs better than TM4 as the user equipment (UE) becomes mobile, since 2-port TM3 is less dependent on the channel state information.The practical implementation issues of link adaptation are shown to cause a significant drop in throughput at medium and high UE velocities.The results in the thesis suggest that improving the latency of the link adaptation loop with low complexity algorithms, or an increase in processing power, along with adaptive link adaptation reporting intervals can keep uplink overhead low and maintain a higher throughput as velocity increases.The UE velocity is also pushed to extremes in the high speed train on railway simulations and shows that LTE can operate with some throughput degradation at 350 km/hr.Finally, the LTE downlink is also subjected to phase noise; an important impairment present in communication systems employing up/down-conversion.The generated phase noise and the measured phase noise simulations show the effect of phase noise on the throughput.As expected, the relatively quiet measured phase noise does not significantly degrade the LTE downlink.iii I would like to thank my supervisor Prof. M. El-Tanany for his friendship and the genuine guidance he provided when I would ask for his help.He unselfishly lent me his time for any questions I had and occasional unrelated discussions about topics that interested us both.He provided encouragement along the way and allowed me to explore additional areas to satisfy my curiosity despite the extra time it would take to complete my thesis work.I'm very grateful for the opportunity he gave me to learn a new field, work on an interesting topic and meet a number of wonderful people along the way.I would also like thank my co-workers and mentors at Ericsson who often made themselves available (at any time) to discuss projects on which we were working.They inspired me since they had a tremendous amount of passion for the work they were performing.Thank you to
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".