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Power Control and Resource Allocation for Device-to-Device Communications in Cellular Networks
KTH, School of Information and Communication Technology (ICT).
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Device-to-device (D2D) communications in cellular networks will improve traditional cellular systems in many ways. By allowing user equipment (UE) in proximity to communicate through direct links, the transmitter would be able to transmit with lower power while the receiver could still receive better-quality signals. Both spectrum and energy eciency can be signicantly increased. Moreover, D2D communications in cellular networks will make an eective way for emerging proximity-based services.

The introduction of D2D links into a cellular network complicates the interference situation. Traditional macro-cellular links will experience high interference from D2D links, especially if D2D links are reusing the cellular radio resources. This amplies the importance of power control and resource allocation techniques to mitigate interference. This thesis evaluates the performance of three power control algorithms, namely LTE power control, utility maximization, and hybrid power control. LTE power control plays the role of the most practical power control scheme as it has been standardized. Utility maximization power control is an optimal distributed power control designed to improve spectrum and energy eciency in a balanced manner. Hybrid power control is a scheme proposed in this thesis, which combines LTE power control for the cellular UEs and utility maximization power control for the D2D UEs. It is designed to have compatibility with existing LTE system as well as to protect cellular links.

Four resource allocation algorithms are considered in this thesis, namely random resource allocation, balanced random allocation (BRA), cellular protection allocation (CPA), and minimum interference (MinInterf) allocation. They are all heuristic algorithms with dierent degrees of complexity. Numerical results are obtained with Monte Carlo simulations, modelling a cellular system with randomly dropped UEs in each iteration. System performance metrics resulted from dierent power control and resource allocation algorithms are evaluated and compared. The performance metrics of interest include both spectrum and energy eciency, SINR, and transmit power. The results show that LTE power control performs well in terms of D2D UEs' SINR if the path loss compensation factor is set to a suciently high value, e.g. 0.8.

Meanwhile, the performance of utility maximization power control depends heavily on its tuning parameter. If the parameter is low, high spectrum efciency is achieved in the exchange of high transmit power, or vice versa. Hybrid power control is proven to yield better cellular UEs' SINR compared to other power control algorithms. This depends on an interference threshold parameter. If the threshold parameter is lower, the cellular links are better protected. Simulation results also show that the MinInterf allocation algorithm is superior than other resource allocation algorithms in terms of UEs' SINR.

However, MinInterf is a complex algorithm which requires the knowledge of all cellular and D2D link qualities. Therefore, it might be preferable to use either of three other algorithms. Simulation results show that BRA performs better than random resource allocation, although in many cases their performance metrics are almost identical. CPA algorithm performs slightly better than random resource allocation and BRA in the low-SINR region, but it performs badly in the high-SINR region.

Place, publisher, year, edition, pages
2013. , 61 p.
Trita-ICT-EX, 2013:114
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-128351OAI: diva2:647340
Educational program
Master of Science - School of Electrical Engineering (EES) - Master of Science - Research on Information and Communication Technologies
Available from: 2013-09-11 Created: 2013-09-11 Last updated: 2013-09-11Bibliographically approved

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