Abstract
The concept and framework of a self-regulating symbiotic network planner is introduced as a way to improve the use of available resources and infrastructure and the overall performance of co-located wireless networks. A framework for physical-layer optimization is proposed, based on an advanced and reliable network planner. Besides an optimal network planning including the adjustment of transmit powers, also a symbiotic optimization over different networks and network layers is implemented, a new concept in network cooperation based on shared and variable incentives. In this article, specifically, it is assumed that the co-located networks share the incentive of a lower global power consumption and the newly created symbiotic network is optimized accordingly. Feedback about the signal quality parameters allows optimizing path loss models, finetuning device transmit powers, coping with a changing propagation environment, and improving network reliability. The concept is applied to and experimentally validated with a real-life wireless test environment and a power consumption reduction of 79.5% is obtained, by consecutively enabling energy-saving features of the network planner: intelligent cognitive network planning, symbiotic network cooperation, and transmit power adjustments.
Highlights
In the recent years, an increasing number of networks using different wireless technologies started to co-exist: GSM (Global System for Mobile Communications), UMTS (Universal Mobile Telecommunications System), Bluetooth, WiMAX (Worldwide Interoperability for Microwave Access), Zigbee, DECT (Digital Enhanced Cordless Telecommunications), Wi-Fi, LTE (Long-Term Evolution), etc
6 Conclusions The concept, creation, and framework of an advanced physical-layer-based self-regulating symbiotic network planner are presented as a way to improve the overall performance of co-located wireless networks
The planning tool creates an optimized incentive-based symbiotic network starting from different independent wireless networks
Summary
An increasing number of networks using different wireless technologies started to co-exist: GSM (Global System for Mobile Communications), UMTS (Universal Mobile Telecommunications System), Bluetooth, WiMAX (Worldwide Interoperability for Microwave Access), Zigbee, DECT (Digital Enhanced Cordless Telecommunications), Wi-Fi, LTE (Long-Term Evolution), etc. Network, real-time network and signal quality information can be fed back into the planning tool to increase the accuracy of the used propagation models, to finetune transmit powers, or to adapt to a varying propagation environment or varying network conditions, as is the case when node failures occur This allows an incentive-based optimization of the transmission settings. 4.3 Cognition implementation Tuning of the propagation models and optimization of the node parameters is done based on a feedback loop Once the optimal node parameters (sinks, transmit powers, modes, etc.) have been determined, the network (Figure 1) is reconfigured in a second step and packets are sent To this end, a java tool is developed that can send configuration messages (radio on, radio of, set tx power, etc.) to the sensor devices.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: EURASIP Journal on Wireless Communications and Networking
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
