Power estimation in LTE systems with the general framework of standard interference mappings

We devise novel techniques to obtain the downlink power inducing a given load in long-term evolution (LTE) systems, where we define load as the fraction of resource blocks in the time-frequency grid being requested by users from a given base station. These techniques are particularly important because previous studies have proved that the data rate requirement of users can be satisfied with lower transmit energy if we allow the load to increase. Those studies have also shown that obtaining the power assignment inducing a desired load profile can be posed as a fixed point problem involving standard interference mappings, but so far the mappings have not been obtained explicitly. One of our main contributions in this study is to close this gap. We derive an interference mapping having as its fixed point the power assignment inducing a desired load, assuming that such an assignment exists. Having this mapping in closed form, we simplify the proof of the aforementioned known results, and we also devise novel iterative algorithms for power computation that have many numerical advantages over previous methods.

[1]  E. R. Love,et al.  64.4 Some Logarithm Inequalities , 1980 .

[2]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[3]  Di Yuan,et al.  Power and Load Coupling in Cellular Networks for Energy Optimization , 2015, IEEE Transactions on Wireless Communications.

[4]  Kurt Majewski,et al.  Conservative Cell Load Approximation for Radio Networks with Shannon Channels and its Application to LTE Network Planning , 2010, 2010 Sixth Advanced International Conference on Telecommunications.

[5]  Heinz H. Bauschke,et al.  Convex Analysis and Monotone Operator Theory in Hilbert Spaces , 2011, CMS Books in Mathematics.

[6]  Roy D. Yates,et al.  A Framework for Uplink Power Control in Cellular Radio Systems , 1995, IEEE J. Sel. Areas Commun..

[7]  Di Yuan,et al.  Analysis of Cell Load Coupling for LTE Network Planning and Optimization , 2012, IEEE Transactions on Wireless Communications.

[8]  Gerhard Fettweis,et al.  Concurrent Load-Aware Adjustment of User Association and Antenna Tilts in Self-Organizing Radio Networks , 2013, IEEE Transactions on Vehicular Technology.

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

[10]  Slawomir Stanczak,et al.  Fundamentals of Resource Allocation in Wireless Networks - Theory and Algorithms (2. ed.) , 2009, Foundations in Signal Processing, Communications and Networking.

[11]  Slawomir Stanczak,et al.  Toward Energy-Efficient 5G Wireless Communications Technologies: Tools for decoupling the scaling of networks from the growth of operating power , 2014, IEEE Signal Processing Magazine.

[12]  Holger Boche,et al.  Interference Calculus - A General Framework for Interference Management and Network Utility Optimization , 2012, Foundations in Signal Processing, Communications and Networking.

[13]  Slawomir Stanczak,et al.  Toward Energy-Efficient 5G Wireless Communications Technologies , 2014, ArXiv.

[14]  Ulrich Türke,et al.  Analytical Cell Load Assessment in OFDM Radio Networks , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[15]  Slawomir Stanczak,et al.  Base station selection for energy efficient network operation with the majorization-minimization algorithm , 2012, 2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).