Low complexity approximate maximum throughput scheduling for LTE

In this paper we address the challenge of multiuser scheduling in the downlink of 3GPP UMTS/LTE. Long Term Evolution (LTE) imposes the constraint of using the same code rate, modulation order and transmit power for all resources a User Equipment (UE) is scheduled onto. This, in addition to the lack of channel knowledge, prohibits theoretical concepts such as capacity maximization to be applied for resource allocation. Based on the Channel Quality Indicator (CQI) feedback we derive a linearized model for multiuser scheduling. In contrast to other proposals we use Mutual Information Effective SNR Mapping (MIESM) to calculate an average CQI value for all UE resources. This enables a rate increase while still guaranteeing an imposed Block Error Ratio (BLER) constraint. The proposed framework can also be applied to implement other scheduling strategies. This is demonstrated by comparing different standard schedulers in terms of achieved throughput and fairness.

[1]  Markus Rupp,et al.  System Level Simulation of LTE Networks , 2010, 2010 IEEE 71st Vehicular Technology Conference.

[2]  Markus Rupp,et al.  Calculation of the spatial preprocessing and link adaption feedback for 3GPP UMTS/LTE , 2010, 2010 Wireless Advanced 2010.

[3]  Cyril Leung,et al.  Multiuser Scheduling on the Downlink of an LTE Cellular System , 2008, J. Electr. Comput. Eng..

[4]  Frank Kelly,et al.  Charging and rate control for elastic traffic , 1997, Eur. Trans. Telecommun..

[5]  Antonis G. Gotsis,et al.  Linear modeling and performance evaluation of resource allocation and user scheduling for LTE-like OFDMA networks , 2009, 2009 6th International Symposium on Wireless Communication Systems.

[6]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[7]  Raj Jain,et al.  A Quantitative Measure Of Fairness And Discrimination For Resource Allocation In Shared Computer Systems , 1998, ArXiv.

[8]  Giuseppe Caire,et al.  Capacity of bit-interleaved channels , 1996 .

[9]  Hoon Kim,et al.  A proportional fair scheduling for multicarrier transmission systems , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[10]  Jiaru Lin,et al.  Link Layer Abstraction in MIMO-OFDM System , 2007, 2007 International Workshop on Cross Layer Design.

[11]  Kenneth Steiglitz,et al.  Combinatorial Optimization: Algorithms and Complexity , 1981 .

[12]  Markus Rupp,et al.  Simulating the Long Term Evolution physical layer , 2009, 2009 17th European Signal Processing Conference.

[13]  Changchuan Yin,et al.  Reduced-Complexity Proportional Fair Scheduling for OFDMA Systems , 2006, 2006 International Conference on Communications, Circuits and Systems.

[14]  Markus Rupp,et al.  Mutual information based calculation of the Precoding Matrix Indicator for 3GPP UMTS/LTE , 2010, 2010 International ITG Workshop on Smart Antennas (WSA).

[15]  Magnus Almgren,et al.  A fading-insensitive performance metric for a unified link quality model , 2006, IEEE Wireless Communications and Networking Conference, 2006. WCNC 2006..