- Open Access
Proactive integrated handoff management in cognitive radio mobile ad hoc networks
© Nejatian et al.; licensee Springer. 2013
Received: 17 December 2012
Accepted: 19 August 2013
Published: 5 September 2013
In cognitive radio networks, the secondary users (SUs) switch the data transmission to another empty spectrum band to give priority to primary users (PUs). In this paper, channel switching in cognitive radio mobile ad hoc networks (CR-MANETs) through an established route is modeled. The probability of channel availability in this route is calculated based on the PU's activity, SU's mobility, and channel heterogeneity. Based on the proposed model, the channel and link availability time are predicted. These predictions are used for channel assignment in the proposed channel allocation scheme. A handoff threshold as well as a life time threshold is used in order to reduce the handoff delay and the number of channel handoffs originating from the short channel usage time. When the channel handoff cannot be done due to the SU's mobility, the local flow handoff is performed to find an appropriate node in the vicinity of a potential link breakage and transfer the current data flow to it. The local flow handoff is performed to avoid possible flow disruption and also to reduce the delay caused by the link breakage. The study reveals that the channel heterogeneity and SU's mobility must be considered as important factors, which affect the performance of the handoff management in the CR-MANETs. The results emphasize on the improvement of the route maintenance probability after using the local flow handoff. It is also stated that the amounts of handoff requirement and handoff delay are decreased after using the predicted channel usage life time and handoff threshold time.
Over the last few decades, the world has experienced an explosion of the wireless devices. This has led to some spectrum bands being heavily used, especially unlicensed bands, such as ISM bands, which can be attributed to interference and poor network performance. On the other hand, recent studies have shown that a large amount of the licensed spectrum bands remain under-utilized and inefficient . Hence, it was concluded that the traditional fixed spectrum allocation approach cannot efficiently regulate the spectrum access any longer. Dynamic spectrum access is an approach that permits wireless devices to use the idle frequency bands, namely spectrum holes,  with enabling technology of cognitive radio (CR). CR changes its transmission parameters based on the interaction with the surrounding environment and allows the secondary user (SU) to share the spectrum when the primary users (PUs) do not use these spectrum bands .
Spectrum hole availability is random due to the random appearance of PUs as well as the unpredictability of SUs' demand. The spectrum holes may shift over time and over space. In a CR system, the shifting of spectrum holes can be defined as spectrum mobility, which is cohesive to spectrum handoff. Spectrum handoff refers to the transfer of an ongoing data transmission of a CR user to another available spectrum band. Spectrum handoff is extremely challenging in CR networks, especially in cognitive radio mobile ad hoc networks (CR-MANETs), because of frequent topologic variations, limited power, limited channel transmission range, bandwidth constraints, and lack of the central controlling entity. The spectrum sharing in heterogeneous networks was proposed in , which considers the infrastructure-based network. In heterogeneous CR networks, a channel may be available over vast, mutually exclusive spectrum bands that present remarkable heterogeneity in terms of channel transmission range and channel error rate. The channels located in higher frequency bands have lower transmission ranges.
When considering the influence of node mobility on the channel availability, the effect of channel heterogeneity becomes more significant. In a CR system, node mobility and channel heterogeneity lead to frequent spectrum handoff. Thus, it is needed to propose a proper algorithm for unified, proactive integrated handoff management (PIHM) in CR-MANETs. The algorithm reduces the probability of handoff blocking, reduces route failure due to user mobility and channel heterogeneity, and maintains end-to-end route connectivity. It must also decrease the number of handoffs in the network considering the effects of different mobility events.
There are some challenges which make the PIHM difficult. The first challenge is differentiating the SU's mobility and spectrum mobility. Channel quality degradation happens because of the SU's mobility and channel heterogeneity in terms of transmission range. Therefore, there are different route failure types that necessitate different route recovery strategies. The second challenge related to integrated handoff management is finding the best new route and a channel to maintain the route while reducing the switching time and the number of handoffs. In this paper, the channel availability time is used as the main metric for channel allocation. This parameter is estimated by considering the channel heterogeneity and the SU's mobility. The handoff threshold is used to initiate a handoff procedure proactively. In some cases, the distance between two communicating nodes in a hop belonging to an active route exceeds a given threshold, and the channel handoff is not efficient because of the limited channel transmission range. In these cases, the node with the link breakage transfers the routing information to another appropriate sponsor node. This mechanism is called as local flow handoff, which aims to find a feasible route upon link breakage and transfer the traffic to another stable route based on the prediction. The motivation of this mechanism is to maintain end-to-end connectivity once a route is established for the purpose of sending data.
The rest of this paper is organized as follows. Section 2 describes the related works for spectrum handoff management. Section 3 introduces the proposed PIHM scheme, its requirements, and the design concepts. In Section 4, we propose a unified modeling and characterization of channel availability in CR-MANETs. Section 5 explains the different handoff types in CR-MANETs and introduces the proposed PIHM algorithm. In Section 6, the implementation of PIHM algorithm is performed. In Section 7, the results and discussion are elaborated. Finally, Section 8 concludes the paper and presents the further suggestions.
2 Related works
There are a few studies related to spectrum handoff in CR-MANETs. Giupponi and Perez-Neira  proposed a fuzzy-based spectrum handoff decision-making approach employing two fuzzy logic controllers. Each SU estimates the distances between itself and all the active PUs in the surrounding area using the first fuzzy logic controller. The other fuzzy logic controller determines whether the SU has to do a spectrum handoff or not. In some cases, the SU can avoid performing a spectrum handoff by appropriate adjustment of its transmission power. Feng et al.  developed a spectrum handoff technique from a single link concept to a multilink spectrum handoff scheme. The proposed algorithm tries to minimize the total link cost by taking into account the end-to-end network connectivity constraint. Another major contribution of this paper was that the rerouting mechanism was performed before the spectrum handoff event to increase the system throughput.
Song and Xie [6, 7] proposed a proactive spectrum handoff configuration based on the statistics of observed channel utilization. The network coordination and rendezvous issues were solved in this spectrum handoff scheme without using a common control channel. The collision among SUs was also deleted by a distributed channel determination scheme. Damljanovic explained the proper solutions and spectrum mobility necessities in cognitive radio networks . Duan and Li proposed a spectrum handoff strategy in which the optimal spectrum band was chosen based on a multiplex criterion considering the estimated transmission time, the PU presence probability, and the spectrum availability time . A cooperative spectrum sensing scheme was used to predict the spectrum idleness. The authors use a geo-location method in order to consider a spectrum handoff in the space domain. The simulation results indicate that the proposed spectrum handoff scheme outperforms conventional methods in terms of spectrum handoff delay. In this paper, the authors considered a per hop basis scheme. Moreover, they did not consider all the effective parameters on the spectrum handoff such as channel heterogeneity. Wu and Harms  proposed a proactive flow handoff for legacy mobile ad hoc networks. The major contribution of this scheme was maintaining end-to-end connectivity after a flow was established. This scheme introduced the consideration of user mobility and location information. Abhilash et al.  proposed a preemptive route maintenance scheme in which an established route is repaired before it breaks by considering the mobile ad hoc user's location information. They called this scheme local router handoff and implemented it into the Ad hoc On-demand Distance Vector protocol (AODV). Based on the results, the throughput of the system was increased under certain conditions. Caleffi et al.  proposed an optimal routing metric for cognitive radio ad hoc networks that considers the route diversity effects to overcome un-optimality and un-accuracy in CR routing. In this paper, the route diversity provided by the intermediate nodes is considered to calculate the end-to-end delay of a route considering the unique characteristics of cognitive radio networks. The results of the analytical model and simulation reveal the benefits of the proposed routing metric for cognitive radio ad hoc networks. In the proposed model, the authors did not consider the effects of the SU's mobility and spectrum heterogeneity on the routing metric. Chehata et al.  introduced the CR-AODV as a multi-radio multi-channel on-demand scheme that can manage the data transmission of cognitive users. Cacciapuoti et al.  proposed a reactive routing protocol by evaluating the feasibility of reactive routing for CR-MANETs. Nejatian et al.  pioneered handoff management in CR-MANETs. Factors and types of mobility were mentioned, which necessitate integrated mobility and handoff management in CR-MANETs. In this paper, a conceptual model was proposed for integrated handoff management in CR-MANETs.
Maintaining the optimal routes in CR-MANETs is extremely difficult because of the randomness PU's activity, SU's mobility, and channel quality . Hence, a framework must be introduced for integrated handoff management and local flow handoff in CR-MANETs. Based on a review of the literature, there is no study that considers proactive unified spectrum handoff in CR-MANETs. In the next section, the proposed PIHM framework is explained, and assumptions regarding the network architecture are introduced.
3 Proposed PIHM framework
4 Characterization of channel availability in CR-MANETs
Symbols used in this paper and their definitions
Node transmission range
Total number of available channels
Number of possible channels at each node
Total number of channel types
Number of detected channels of each type at each node index
Probability of a particular channel availability at each node
Probability that there is at least one single channel among c channels between two nodes
Probability that there is at least one common channel among all hops in a route
Poisson density of nodes' spatial distribution in the network
Transmission range of a channel of type l
Signal power at transmitting antenna
Receiving power at distance r
Signal power threshold for preemptive channel handoff
W ch, l
Warning distance for nodes communicating on a channel of type l
Warning distance for preemptive local flow handoff region
Received power at channel transmission range of type l
Handoff threshold for the preemptive channel handoff
Handoff threshold for the preemptive local flow handoff
Signal power threshold for preemptive flow handoff
Power received at the node transmission range, R l
Interval from the warning till the break
Channel availability time for the channel of type l
Channel availability time for the channel of type l available in hop i
Link availability time
Location weight for case Di- 1 i and channel of type T l
Possibility of using the channel of type l, detected by both nodes belonging to the hop i (H i )
Possibility of using the channel z of type l for communicating in hop i
Possibility of using the channel of type l for data transmission in hop i
Channel allocation metric for channel z of type l
The set of detected channels by the two nodes belonging to the hop i
Channel z of type l belonging to the set of detected channels by the two nodes belonging to the hop i
The set detected channel that can be used for communication in hop i
4.1 System description
4.2 Characterization of channel availability and spectrum mobility in CR-MANETs
The effects of the spectrum heterogeneity and mobility of the SU on the probability of channel availability must also be considered. In a heterogeneous network, each channel experiences various levels of packet error rate and different channel transmission ranges. In the initial condition when the nodes are assumed to be fixed, different channels will have different transmission ranges. A channel with a lower frequency range needs lower transmission power. Thus, in a heterogeneous network with different channel transmission ranges, the distance between the SUs affects the probability of channel availability.
In practical CR networks, the sensing capability, which influences the reliable probability of channel availability, is not perfect. However, in this work, we follow the assumption of perfect sensing in which the probabilities of both false alarms and miss detections are zero.
Therefore, (21) reduces to (5) in which the system provides homogeneous channels.
Based on the channel availability modeling, the unified spectrum handoff scheme must be proposed to include different mobility events in CR-MANETs, such as spectrum and user mobility, channel quality degradation, and topologic variation.
5 Proposed PIHM algorithm
5.1 The SU's mobility
As shown in Figure 5a, route failure occurs when either node B or node F moves such that any channel cannot support their communication. Before the route failure, a local flow handoff is performed. To perform local flow handoff, a certain amount of overlapping of transmission range between node A, node F and the intermediate node that will take responsibility for routing the packets is needed.
5.2 The PU's activity dominates
Figure 5b shows the second scenario when the PU’s activity in a neighboring area of node C may cause the links A-E or E-F to fail. This route failure occurs once the PU starts its communication or node C is mobile and enters the PU’s activity area.
5.3 Spectrum heterogeneity and different channel transmission range
The mobility of a CR user can also lead to spectrum handoff due to spectrum heterogeneity and a variety channel transmission ranges. Assume that two mobile nodes with a distance less than R l are communicating in an active route while they are using a channel of type l for their data transmission. When their distance exceeds the R l , they must change their communication channel and find a channel with a transmission range longer than R l .
Based on these different scenarios, the various spectrum handoff types are proposed in Figure 6. They are defined as follows:
Forced intra-pool spectrum handoff: The operation frequency of the SU is changed to another spectrum band in the same spectrum pool. This type of handoff happens because of the appearance of the PU.
Forced inter-pool spectrum handoff: The operation frequency of the SU is changed to another spectrum band in a different spectrum pool because of the appearance of the PU.
Inter-pool spectrum handoff: The CR user changes its spectrum bands from one spectrum pool to another different spectrum pool. This type of spectrum handoff occurs because of the mobility and channel quality degradation of the SU.
Local flow handoff: Due to the SU mobility, there is no channel that can support the data transmission.
6 Implementation of the proposed PIHM algorithm
6.1 Channel and local flow handoff prediction
Here, two different handoff thresholds are related to the signal power threshold. In this paper, the signal power of hello packets is used to approximate the distance between the transmitter and the receiver.
where PSLFTH is the signal power threshold for preemptive flow handoff and PNTR indicates the minimum power received by the receiver at the node transmission range, R T . Wlink is the warning distance for preemptive local flow handoff region.
The tw, which is the interval from the warning till the break, needs to be greater than or equal to the necessary time for performing the handoff.
6.2 Channel and link usage time prediction
Neighbor signal information table
Power strength/reception time
When the distance between two SUs is decreasing, P1 will be higher than P2 and P3. In this case, the power strength P1 is set to the latest signal power value, and P2 and P3 are set based on the new received signal power.
When the Ps is replaced with the PCTR, l , the channel availability time between two communicating nodes for the channel of type l () is an estimated value. The power signal Ps is also replaced by PNTR to calculate the link availability time (tava,L) between two communicating nodes.
6.3 Channel allocation scheme
After a route is established, any node in the route will monitor its next hop to predict the handoff. The entire nodes in the route also perform the spectrum sensing to monitor the PU's activity. Any handoff prediction due to the node mobility or channel quality degradation leads to channel handoff initiation. PU detection in sensing part also initiates the spectrum handoff. When two nodes go far away and there is no more available channel to support their communication, these nodes initiate the local flow handoff, which necessitates the spectrum handoff. In this part, the proposed channel allocation scheme in the decision part is proposed. The proposed scheme is introduced based on the unified formula in (21) for channel availability in CR-MANETs.
6.4 Handoff initiation and connectivity maintenance
To maintain end-to-end connectivity, topological variations and channel quality degradation due to node mobility are addressed using the handoff request (HREQ) packets. Also, the variations in spectrum availability because of the PU's activity are addressed using the primary user handoff request (PU-HREQ). The single-hop PU-HREQ packet informs the neighbor nodes that the PU's activity has been detected on a special channel and directs them to select another unused channel for data transmission. On the other hand, the HREQ is applied to inform the next hop node that the current link is breaking due to node mobility or channel quality degradation. If channel handoff occurs and no more empty channel is available to maintain the route, local flow handoff, a preemptive approach to address the route breaking, is applied.
In terms of the PU-HREQ, once an SU detects the PU's activity on a special channel, e.g., channel C li , the SU discards all the entries through channel C li and informs its neighbors that the channel is busy using a PU-HREQ. The PU-HREQ packet contains the available and detected channels of the current SU. The SUs that receive the PU-HREQ invalidate the entries through C li that involve the PU-HREQ source. Using the NSIT and NCIT based on the introduced channel allocation scheme, the SU that receives the PU-HREQ finds the channel z that maximizes the channel allocation metric described by (39). When the optimal channel is found, the node sends a handoff reply (PU-HREP) back. This PU-HREP contains the new channel information to perform handoff into it and continue the data transmission.
In terms of topological variation due to node mobility or channel quality degradation, once the SU predicts the handoff, it broadcasts a single-hop channel HREQ packet to its next hop node. When the next node receives the HREQ packet, it makes a decision using the NSIT and NCIT, by a method similar to the procedure for PU-HREQ.
In case that the route life time is larger than a threshold amount (Tth), node E is a candidate for local flow handoff. Node B compares all the life time connectivity information received from its neighbors. Then, it selects the best candidate through which the B and F maintain the longest life time.
Suppose that in Figure 9, the node E is the best candidate for the local flow handoff. Node B sends a handoff request (HR) to node F through node E using CCC. The HR contains information, such as the ID of node B as the local source, the ID of node F as the local destination, and the channel availability list of the current node. To avoid loops, node E ignores the HR packets when there is corresponding routing information. Once node E receives the HR as a candidate for local flow handoff, then:
Node E compares its own available channels Cava,int with the available channels of the local source Cava,locs in HR. The usable channel set in this hop can be shown as follows:(40)
Node E determines the channel z, which maximizes the channel allocation metric from the channel set , using (39).
Let z be the selected channel, node E updates HR with its own information, the ID of node B as the local source, the ID of node F as the local destination, and its available channel list.
Once the CCC is available, it sends the HR to the local destination node F. Finally, this HR will be saved in a handoff table.
When the local destination node F receives the HR, like intermediate node E, it selects a proper channel for its upper hop. The local destination node F sends the handoff acknowledgment (HA) packet back to the local source node B through node E. The HA message sets up a new route between B and F, which is the route B → E → F. Then, the routing tables in nodes B, E, and F are updated. Once the new route is established, the data flow will be passed along the new route. In the case that the local flow handoff is not possible, the global flow handoff will be performed by the source node.
7 Results and discussion
7.1 Probability of channel availability in CR-MANETs
Based on these figures, we can see that the probability of channel availability through a route is dependent on the activity of the PU and the total number of available channels, and it decreases as the number of hops increases.
7.2 The effects of different parameters on the Pcar,c
In the second part, we show the effect of different parameters on the Pcar,c. We suppose that there are two types of channels with a transmission range of R1 = 75 m and R2 = 125 m and a maximum node transmission range of RT = 150 m. We also assume that the activity of the PU on different channels is identical.
7.3 Link maintenance, handoff blocking, and spectrum handoff investigation
In this section, performance comparisons of different schemes are conducted using network simulator 2 (NS-2) . The SU's route maintenance probability, handoff blocking probability, and the number of anticipated spectrum handoff are investigated. There is a total number of available channels C = 10, classified into two different types, c1 = 5 and c2 = 5. The transmission ranges of different channel types and the node transmission range are set to R1 = 75 m, R2 = 125 m, and RT = 150 m, respectively. The mobile SUs are distributed in a network with 3,000 m × 3,000 m area, and their speed is uniformly distributed from 1 to 10 m/s. Both channel usage time and the link life time threshold are set to 8 s.
Spectrum handoff is extremely challenging in cognitive radio networks, especially in CR-MANETs because of frequent topological variations, limited power and channel transmission range, bandwidth constraints, and lack of a central controlling entity. In this paper, channel switching in CR-MANETs, for an established route, is modeled, and the probability of channel availability in this route is calculated based on PU's activity, SU's mobility, and channel heterogeneity. The study reveals that the channel heterogeneity and the SU's mobility must be considered as important factors, which affect the performance of handoff management in the CR-MANETs. Based on the introduced scenarios for handoff initiation in CR-MANETS, a proactive integrated handoff management (PIHM) is introduced for this network. The results show that the proposed integrated handoff management scheme achieves more data transmission opportunities. Based on the results, the route maintenance probability is increased, while the number of spectrum handoff is reduced.
This work was supported in part by the Ministry of Science, Technology and Innovation (MOSTI) Malaysia, and Research Management Center (RMC), University Technology Malaysia under GUP research grant no. R.J130000.7923.4S063.
- FCC: Notice of proposed rulemaking and order, no.03-222. Washington, DC: Federal Communications Commission; 2003.Google Scholar
- Ding Y, Xiao L: Channel allocation in multi-channel wireless mesh networks. Comput. Commun. 2011, 34: 803-815. 10.1016/j.comcom.2010.10.011View ArticleGoogle Scholar
- Guoqin N, Duan J, Su J, Qiu D: Spectrum sharing based on spectrum heterogeneity and multi hop handoff in centralized cognitive radio networks, in 20th Annual WOCC. Newark, NJ; 2011:1.Google Scholar
- Giupponi L, Perez-Neira AI: Fuzzy-based Spectrum Handoff in Cognitive Radio Networks. In 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications CrownCom. Singapore; 2008:1-6.Google Scholar
- Feng W, Cao J, Zhang C, Liu C: Joint Optimization of Spectrum Handoff Scheduling and Routing in Multi-hop Multi-radio Cognitive Networks. In 29th IEEE International Conference on Distributed Computing Systems. Montreal, QC; 2009:85-92.Google Scholar
- Song Y, Xie J: ProSpect: a proactive spectrum handoff framework for cognitive radio ad hoc networks without common control channel, IEEE trans. Mobile Comput. 2011, 11(99):1.Google Scholar
- Song Y, Xie J: Performance analysis of spectrum handoff for cognitive radio ad hoc networks without common control channel under homogeneous primary traffic. IEEE INFOCOM 2011, 2011(10–15):3011-3019.Google Scholar
- Damljanovic Z: Mobility management strategies in heterogeneous cognitive radio networks. Springer Sci. Mag. 2010, 18(1):4-22.Google Scholar
- Duan J, Li Y: An optimal spectrum handoff scheme for cognitive radio mobile ad hoc networks. AECE 2011, 11: 11-16.View ArticleGoogle Scholar
- Wu K, Harms J: Performance study of proactive flow handoff for mobile ad hoc networks. Wireless Netw. Springer 2006, 12: 119-135. 10.1007/s11276-006-6155-8View ArticleGoogle Scholar
- Abhilash P, Perur S, Lyer S, Router H: An approach for preemptive route repair in mobile ad hoc networks. Lect. Notes Comp. Sci. 2002, 2552: 347-357. 10.1007/3-540-36265-7_33View ArticleGoogle Scholar
- Caleffi M, Akyildiz IF, Paura L: OPERA, optimal routing metric for cognitive radio ad hoc networks. IEEE Trans. Wireless Commun. 2012, 11(8):2884-2894.Google Scholar
- Chehata A, Ajib W, Elbiaze H: An on-demand routing protocol for multi-hop multi-radio multi-channel cognitive radio networks. In Wireless Days 2011 IEEE conferences. Niagara Falls, ON; 2011:1-5.View ArticleGoogle Scholar
- Cacciapuoti AS, Caleffi M, Paura L: Reactive routing for mobile cognitive radio ad hoc networks. Ad. hoc. networks 2011, 10(5):803-815.View ArticleGoogle Scholar
- Nejatian S, Syed Yousof SK, Abdol Lattif NM, Asadpour V: Proactive Integrated handoff management in CR-MANETs: a conceptual model. In IEEE Symposium on Wireless Technology and Applications (ISWTA). Bandung; 2011:33-38.Google Scholar
- Lee WY, Akyildiz IF: Spectrum-aware mobility management in cognitive radio cellular networks. IEEE Trans Mobile Comput. 2012, 11(4):529-542.View ArticleGoogle Scholar
- Pfeiffer PE: Concepts of probability theory. Mineola, NY: Courier Dover Publications; 1978:47-48.Google Scholar
- Cheng YC, Robertazi TG: Critical connectivity phenomena in multi hop radio models. IEEE Trans. Communications 1989, 37(7):770-777. 10.1109/26.31170View ArticleGoogle Scholar
- Hou T-C, Li VO-K: Transmission range control in multihop packet radio networks. IEEE Trans. Commun. 1986, 32(1):38-44.Google Scholar
- Goff T, Abu-Ghazleh NB, Phatak DS, Kahvecioglu R: Preemptive Routing in Ad Hoc Networks. In Proceedings of ACM SIGMOBILE. Rome; 2001:43-52.Google Scholar
- Guan QS, Yu FR, Jiang SM: Prediction-based topology control and routing in cognitive radio mobile ad hoc networks. In Proceedings of IEEE INFOCOM. San Diego, CA; 2010:1-6.Google Scholar
- Qin L, Kunz T: Increasing Packet Delivery Ratio in DSR by Link Prediction. In Proceedings of the 36th Hawaii IEEE International Conference on System Sciences (HICSS’03). Big Island; 2003:6-9.Google Scholar
- UC Berkeley, LBL, USC/ISI, Xerox PARC: The Vint Project, the ns Manual (formerly ns Notes and documentation). Edited by: Fall K, Varadhan K. Berkeley: UC Berkeley; 2010.Google Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.