SoCoR (Strategies for cooperative spectrum sensing in Cognitive Radio networks)

Duration: 01.04.2012 - 31.03.2015
Projectleader: Prof. Dr. Horst Hellbrück
Staff: Tahir Akram


There has always been an increasing demand for data rate for the wireless applications and this will also continue in future. But the available spectrum is fixed and furthermore the latest research shows that we are reaching quite close to the channel capacity of the wireless link. Therefore, researchers are working on alternative ways in order to meet with the increasing demand of data rate. Cognitive Radio is one of the research area which has been under focus in the last decade. An interesting frequency range in this regard is the ISM 2.4 GHz band which is quite crowded. This frequency band is also used for the wireless medical applications that demand high reliability requirements. Therefore new schemes, algorithms and approaches for spectrum awareness and cognition are required to guarantee a more efficient and interference reduced spectrum usage.


In this research project cooperative spectrum sensing approaches and strategies will be developed to use the spectrum within a distributed topology targeted for medical applications. The goal is to implement a prototype system based on Software Defined Radio to minimize interference and disturbance while improving the spectrum utilization.


The basic principle of CR Technology is to add intelligence to the radio. The CR can adapt its transmission parameters according to the environment autonomously and use the expensive radio bandwidth more efficiently while avoiding interfering others. The detection of unused frequency band at a particular time is done with the help of spectrum sensing techniques. The major difficulty in accuracy of performance of spectrum sensing techniques is due to the presence of multipath effects, shadowing, receiver noise, and energy consumption. Cooperative Sensing is one of the diversity technique to improve sensing performance of CR. The CRs share their local spectrum occupancy information in order to have a better understanding of the spectrum usage situation. The major challenges in cooperative sensing are;

  • how to establish a common control channel among cooperating nodes.
  • how to reach at consensus about the spectrum occupancy situation among cooperating nodes.

 The cooperative sensing schemes also involve overheads due to control channel. Therefore developing efficient cooperative sensing schemes keeping in view different QoS requirements is still an open research question.


Cognitive Engine (CE) is the brain of the CRs which optimizes the target function having various goals, namely; power consumption, interference, throughput and latency etc. CE tries to achieve this goal with the help of learning from the environment and selects various parameters using a cross layer approach. In this regard, Software Defined Radio  is one of the enabling technology to implement the CR on the hardware. Therefore, a prototype system will be developed which implements the CE and the developed cooperative strategies and algorithms.


Refereed Articles and Book Chapters
[2016] Cooperative Sensing Protocols and Evaluation via IEEE 802.15.4 Devices (Tahir Akram, Tim Esemann, Hellbrück Horst), In the Special Issue of Self Optimized Radio Technologies (Journal of Physical Communication), 2016. [bib]
Refereed Conference Papers
[2015] Performance Evaluation of Cooperative Sensing via IEEE 802.15.4 Radio (Tahir Akram, Horst Hellbrück), In Wireless Communications and Networking Conference, IEEE (WCNC 2015), 2015. [bib] [abstract]
Spectrum Sensing is one of the important tasks for the wireless devices but due to fading, shadowing and noise the performance of individual spectrum sensing devices is not ideal. Cooperative Sensing is seen as a way to improve the performance of individual spectrum sensing devices resultantly improving the efficient utilization of radio bandwidth and minimizing the interference among wireless devices. State of the art are extensive simulations and analysis on cooperative sensing although there are also number of performance evaluations of various fusion rules of cooperative sensing using software defined radios and FPGAs. The limitation of previous work is that they do not address the question how we can improve the overall performance of real systems with cooperative sensing. To the best of our knowledge, this is the first experimental work which presents cooperative sensing protocols with standard radios and evaluates the system performance using cooperative sensing. With IEEE 802.15.4 equipped radio devices we model primary, secondary and cooperating users. We implement cooperative sensing protocols, setup a scenario, perform measurements and compare system performance with and without cooperative sensing. All the experiments are automated with the wisebed testbed software. The evaluation results of cooperative sensing protocols indicate new challenges for optimization and provide awareness to the problem of improving the overall system performance
[2013] Performance Evaluation Metric for Cooperative Sensing in Heterogeneous Radio Environments (Tahir Akram, Tim Esemann, Horst Hellbrück), In European Wireless Conference, IEEE, 2013. [bib] [abstract]
Spectrum sensing is a major task for wireless devices in order to improve coexistence among them in heterogeneous radio environments. Wireless communication includes at least two partners: transmitter and receiver. Therefore, cooperation between partners can improve the performance of spectrum sensing by reducing effort, improving sensing result or a combination of both. An optimal cooperative sensing scheme is a first step to achieve complete awareness of the radio environment for wireless devices. To the best of our knowledge, this is the first theoretical work performed in order to understand the problem of developing optimal cooperative sensing schemes for heterogeneous radio environments for multiple users and single channel. We analyze the problem and perform analytical work which results in a cooperative sensing model. The model comprises sensing schedule, data fusion rules, PU's traffic pattern, and detection performance of the sensing device. A new performance evaluation metric is introduced for optimum spectrum sensing in heterogeneous radio environments. An evaluation of available exemplary cooperative sensing schemes shows that none provides optimality in all scenarios.
Refereed Workshop Papers
[2013] A Reusable and Extendable Testbed for Implementation and Evaluation of Cooperative Sensing (Tahir Akram, Tim Esemann, Torsten Teubler, Horst Hellbrück), In The 8th ACM International Workshop on Performance Monitoring, Measurement and Evaluation of Heterogeneous Wireless and Wired Networks PM2HW2N'13, 2013. [bib] [abstract]
Cooperative sensing has been identi?ed as a potential improvement for cognitive radios to perceive their radio environment. In the past, algorithms have been developed by analysis and simulations exclusively. With cheaper hardware experimental platforms have been used for evaluation purpose recently. Simulations lack realistic propagation models for radio transmission but are reproducible compared to experimental evaluation done by hand. The effects of reduced detection probability and false alarms are not realistic in these simulations. In this paper, we suggest a reusable and extendable automated testbed software and instructions for deployment of own testbeds. Primary users as well as secondary users with cooperating cognitive radios can be flexibly deployed in the testbed within seconds. The advantage is that a series of even long lasting measurements including automatic logging of results can be easily repeated. Results can be assessed on the fly during the ongoing evaluation by accessing debug output remotely. The testbed supports stationary, portable, and in the future mobile radio devices for flexible scenarios as well as monitoring devices for debugging. The testbed and the radio devices are validated by deploying primary and secondary user in a small scenario whose outcome was analyzed beforehand. The results are as predicted and show the usefulness of this approach.
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Project Partners

  • German Academic Exchange Service (DAAD).
  • Higher Education Commission (HEC) of Pakistan.