1.IntroductionThe cognitive radio (CR) forms a technique for sensing the vacant bands and enabling the use of the available bands to transmit data.
It can operate in the licensed spectrum band, where the CR refers to the secondary user (SU) and acquires access when not used by the primary user (PU). The philosophy of dynamic access gathers interest to foster the cognitive radio enabled devices engage the spectrum efficiently with the available bands.A cognitive radio sensor network (CRSN) constitutes a multichannel network capable of transferring data between a source and a destination. It inherits two main differences from a traditional wireless sensor network (WSN) in the sense that the number of available channels differ from time to time and the set of available channels differ for each node in the CRSN. The nodes of a single network in the WSN usually use the same set of the available channels.While the challenges in WSN that include low energy and hardware limitation increase the complexity of spectrum management, the CRSN does not consider the energy and hardware limitations as constraints.
Though the wireless sensor networks (WSNs) offer a fault tolerant nature, serve to be flexible, and find wide spread use, it experiences the constraints of link connectivity, limited bandwidth and processing capability. Besides the theory of clustering allows an efficient way to design efficient network architecture and facilitate effective routing schemes. It reduces the communication overhead, increases reliability and being a structured topology serves to increase the system capacity and stability.
However when thechannelexperiencesfadingandshadowing, a co-operativespectrumsensingapproach gathers strength to augment the degraded performance. It encompasses twosuccessivestages, where inthesensingstage,everycognitiveuserperforms spectrumsensingindividually and inthereportingstage it communicates the localsensingobservations toacommonreceiver and allows thelatter to makeafinaldecision either ontheabsenceor thepresenceoftheprimaryuser. It selects the most favourableuser(clusterhead)withthelargestreportingchannel gaintocollectthesensing resultsfromtheother usersinthesameclusterandforward themtothecommon receiver.
1.1 Related worksThe CR enabled WSN has been seen to reduce congestion, increase the throughput of the network and offer a reliable performance 1, 2. It has been operated with fixed spectrum allocation characterized by resource constraints in terms of communication and processing capabilities. The CR enabled sensor nodes have been endowed with the potential ability to access the multiple alternative channels.
The clustered CRSNs have been formed with a number of clusters and periodically transmit their sensed data to the sink through hierarchical routing 3. The sensor nodes have been equipped with sense and switch facility with the licensed channel by dynamic channel access to reduce the energy consumption.The sensing strategies have been related to the sensing order optimization and acquiring the stopping time in sequential manner in the event of the channels being sensed one after the other 4. A time schedule has been assigned to each secondary user for sensing each particular channel at a particular instant. A co-operative spectrum sensing approach has been implemented to increase the efficiency of sensing and reduce the sensing time 5 for allowing multiple SU’s sense the same channel at the same time.
A cluster based cooperative spectrum sensing has been proposed in cognitive radio systems for reducing the reporting errors by the fading channels. The decision fusion and energy fusion schemes have been orchestrated to circumvent the drawbacks 6.An online decision scheduling algorithm has been suggested to determine the sensing period together with a sequential detection for spectrum sensing, suitable for short term channel change 7.Two problems have been witnessed due to spectrum sensing and channel state estimation and augur efforts for maximizing the secondary user (SU) throughput. It has been solved by means of the secondary user (SU) reporting their sufficient statistics to a fusion centre (FC) and enabling a level triggered sampling 8.
The primary user has been facilitated to transmit its information to the PU’s receiver directly or assisted by the SU depending on maximization of the throughput of the secondary user and primary user in each time slot 9.A game based spectrum allocation mechanism has been proposed for the different number of channels and the dynamic bidding game based spectrum allocation strategy developed 10.A co-operative sensing scheduling embedded in partially observable Markov decision process has been analyzed as an efficient method of spectrum sensing for decreasing the transmission time of the secondary user for exploiting the other channels effectively 11.
An energy efficient spectrum sensing technique has been outlined for reducing the sensing duration for each user 12.In group based co-operative spectrum sensing, the secondary users have been grouped such that different groups become responsible for performing different sensing rounds. Three efficient adaptive assignment heuristics have been explained to perform the assignment of users to the group and the assignment of groups to the sensing rounds in a way that the throughput efficiency remains maximized 13.A partially myopic access strategy has been articulated to prove that it allocates SU traffic to idle spectral bands on an energy efficient framework 14. The TDMA/round-robin fashion has been used to ensure that the secondary station efficiently shares the specific resources and exhibits perfect coordination. 15.
The cooperative spectrum sensing embedded with energy harvesting secondary user has been showcased to reduce the sensing time and decrease the energy efficiency with increased throughput 16. A prioritized ordering heuristic has been developed to order channels under the spectrum and a scheduling assignment included for achieving optimal solution 17.Two heuristic algorithms have been put forth for spectrum sensing and compared with the optimal one-convex concept as applied in the design of an algorithm to solve the heterogeneous scenario optimally18.
An ant colony based energy efficient sensor scheduling algorithm has been elucidated to provide the required sensing performance and increase the overall secondary system throughput19. The CSMA-CA has been laid to achieve fair and efficient throughputs in multi-hop networks by characterizing the worst case bounds for CSMA-CA in one-hop neighborhood topology 20.The probability of collision has been applied to vari-ous traffic patterns thus relaxing the assumption of saturated conditions 21. A new carrier sense multiple access (CSMA) protocol has been outlined based on the interference of power measurements in the chan-nels to facilitate the use of a distributed channel selec-tion scheme 22.Despite the continuous efforts, still the influence of a cluster of the routing scheme and its subsequent benefits on the performance invites attention.