Modelling of routing and spectrum handoff in CR-MANETs
© Nejatian et al.; licensee Springer. 2014
Received: 25 March 2014
Accepted: 26 August 2014
Published: 7 September 2014
There is an extensive research interest in cognitive radio mobile ad hoc networks (CR-MANETs) to improve the spectrum efficiency by developing innovative design techniques through various layers of the protocol stacks. This paper presents the optimisation of CR-MANETs by exploiting the efficient usage of the available wireless spectrum through a framework for spectrum-aware handoff. In this paper, the concept of integrated handoff management in CR-MANETs is considered. An analytical model for a spectrum handoff scheme is introduced based on spectrum mobility in which secondary users (SUs) will move to another unused spectrum band, giving priority to a Primary User (PU), while satisfying its communication quality of service (QoS). The main contribution is using the Markov chain to model the evolution of the network (node position, node speed, channel quality, etc.) and to propose the combined spectrum handoff and routing. The performance of the network is analyzed based on the Markov chain. The comparison results from both analytical modelling and simulation clearly show an improvement in the performance of the SU network in terms of the route maintenance probability and the SU throughput. It is also proved that not only the PU activity affects the performance of the handoff management scheme but also the channel transmission range and the node mobility have a significant effect on the performance of the management scheme.
Recently, there have been major changes in wireless technologies that demand more spectrum bands for allocation to emerging wireless applications. The Federal Communication Commission (FCC) has shown low spectrum efficiency usage in current wireless networks. Low and poor spectrum efficiency is due to the underutilized spectrum usage because of the fixed spectrum allocation . The most influential technology that promises to improve spectrum efficiency is cognitive radio (CR) . CR users can capture and use the unused spectrum bands called spectrum holes .
The spectrum holes may shift over time and over space [4, 5]. In the CR system, the shifting of the spectrum holes is defined as spectrum mobility, which is cohesive with spectrum handoff. Spectrum handoff refers to the transfer of the ongoing data transmission of a CR user to another available spectrum band [6, 7]. During the spectrum handoff, a CR user will move to another unused spectrum band, giving priority to a Primary User (PU), while satisfying its communication quality of service (QoS) [8, 9]. Spectrum handoff is extremely challenging in CR networks, especially in cognitive radio mobile ad hoc networks (CR-MANETs), because of frequent topology variations, limited power and channel transmission range and bandwidth constraints in addition to a lack of a central controlling entity. In heterogeneous CR networks, a channel may be available over vast mutually exclusive spectrum bands, which present remarkable heterogeneity in terms of channel transmission range and channel error rate.
The challenges in maintaining a common link arise when the secondary user (SU) nodes move. 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 multi-hop CRNs, routing is a crucial issue which affects the performance of the whole network . 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 handoffs .
Previous work on spectrum handoff in CR networks only considers the PU's activity. In this paper, we consider the integrated handoff management scheme for CR-MANETs. The work considers the CR spectrum handoff problem and jointly addresses the local flow handoff issue. To propose the integrated handoff management scheme, the availability of spectrum holes in CR-MANETs is considered. The influence of different parameters and events on channel availability is considered in the analytical scheme to obtain a unified model for channel availability in CR-MANETs. The Markov chains are used to model the integrated handoff process in CR-MANETs. The effect of the integrated handoff management on the improvement of the handoff blocking probability is also demonstrated.
The rest of this paper is organized as follows: Section 2 describes the related works for spectrum handoff management. In Section 3, we propose a model for integrated spectrum handoff management and routing scheme. In Section 4, we propose a unified modelling and characterization of the channel availability in CR-MANETs. Section 5 shows the analytical model of the integrated spectrum handoff management. In Section 6, the results and discussion are elaborated. Finally, Section 7 concludes the paper and presents future work.
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 needs to perform a spectrum handoff. 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 multi-link spectrum handoff scheme . The proposed algorithm attempts 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 a spectrum handoff event to increase the system throughput. Song and Xie [14, 15] proposed a proactive spectrum handoff configuration based on 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 prevented through 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. A geo-location method was used to perform a spectrum handoff in the space domain. The simulation results indicated that the proposed spectrum handoff scheme outperformed conventional methods in terms of spectrum handoff delay in a per hop basis. However, channel heterogeneity parameters are not considered in the spectrum handoff. 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. A novel channel allocation scheme for SUs is proposed in . In this study, an analytical model is proposed in which the Markov models are used to model the behaviour of both PU and SU. In this research, the on/off model is combined with the traditional queuing analysis model to show the effectiveness of the proposed method on the SU's channel allocation. 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. In , the integration of an energy-saving routing scheme and the open shortest path first (OSPF) protocol is used. The proposed integrated scheme allows the selection of the links to be switched off so that the negative effects of the topology reconfiguration processes are avoided. Handoff management in CR-MANETs was pioneered in . 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-MANET. Nejatian et al.  characterized and formulated the availability of spectrum bands in CR-MANETs. They explained and integrated the effects of various events on the availability of spectrum holes in CR-MANETs . In , Nejatian et al. introduced a new algorithm for integrated handoff management in which the handoff is performed considering the effects of all the parameters introduced in . 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.
As mentioned before, maintaining the optimal routes in CR-MANETs is extremely difficult because of the randomness of the PU's activity, the SU's mobility and the channel quality degradation. Although [27, 28] introduced and investigated the integrated handoff management in CR-MANETs as a new algorithm, analytical modelling of this concept can be also efficient. Hence, a framework is introduced to analytically model the integrated handoff management in CR-MANETs. The results of both analytical modelling and proposed algorithm are compared to show the effectiveness of the proposed solution.
3 Spectrum hole availability in CR-MANETs
3.1 System description
3.2 Characterization of channel availability and spectrum mobility in CR-MANETs
The different parameters used and their definitions
Total number of available channels
Number of detected channels at each node
Total number of channel types
Number of possible channels of each type at each node
Number of nodes in a route
Total number of the nodes in the network
Probability of a particular channel availability at each node
Poisson density of nodes' spatial distribution in the network
Transmission range of a channel of type l
The effects of the spectrum heterogeneity and mobility of the SU on the probability of channel availability is considered. In a heterogeneous network, each channel experiences various levels of packet error rate (PER) 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.
Based on the channel availability modelling, 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.
4 Routing and integrated spectrum handoff management in CR-MANETs
4.1 Proposed integrated framework
In the next subsections, the analytical modelling of the routing and integrated handoff management in CR-MANETs is performed considering the spectrum mobility and channel availability characterized in the previous section.
4.2 Analytical modelling of routing
4.3 Analytical modelling of integrated handoff
The Markov chains have different numbers of states based on the different position cases D l . As shown in Figure 2 previously, when the length of the hop is less than R1, or when the spectrum handoff occurs in the position case D1, the two nodes involved in the current hop can select one of the available channels of any L types. In the position case D1, the Markov chain is as shown in Figure 5a. In the case D2, the nodes involved in spectrum handoff can select one channel among available channels from type k, in which k ≠ 1, as shown in Figure 5b. When the distance between the involved nodes in the spectrum handoff is according to position case DL, the nodes can only select one channel among available channels of type L, as shown in Figure 5c. The other situations can be determined based on the claims above.
Suppose that two nodes are communicating in a channel of type k. There are two different conditions where nodes continue their communication in the current spectrum pool. These two conditions, in the position case of D l , are as follows:
The packet transmission is successful in the current channel of type k.
The packet transmission is not successful in the current channel of type k but only successful on another channel of spectrum pool k.
Unsuccessful packet transmission in a channel of type e, but only successful transmission in channel of type k.
Unsuccessful packet transmission in a channel of type e, but successful transmission in channel type sets:
where Pr(Rl - 1 < d < R l )is calculated using (12).
4.4 Integrated mobility and spectrum handoff management
4.4.1 SU mobility
As shown in Figure 6a, route failure occurs when either node B or node F moves such that no channel can support their transmission. Before the route failure occurs, local flow handoff is performed. A local flow handoff can be from node B to node E and finally joining node F. In this scenario, the unified routing and spectrum handoff management system tries to solve the problem by finding a node within the neighbouring area of the damaged links.
This equation is in accordance with (28).
4.4.2 PU activity dominates
Figure 6b shows the second scenario when the activity of the PU in the neighbourhood of node E may cause the links A to E or E to F to fail. This route failure occurs once the PU starts its transmission or when node E enters the coverage area of the PU.
4.4.3 Spectrum heterogeneity and different channel transmission range
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.
5 Data rate of the secondary user
Therefore, by using the Markov chain, the dynamic utilization of the empty licensed bands for SUs without conflicting with the PU can be captured. Calculation of the spectrum utilization of the SUs from a statistical point of view and of their stationary behaviour is also possible.
6 Results and discussion
6.1 Analytical results
In the first part, analytical results are illustrated to support the analysis.
Channel availability and spectrum mobility consideration
In this section, we show the effect of different parameters on the Pcar,c. In all of the following figures, we suppose that there are only two types of channels with a transmission range of R1 = 75 m and R2 = 125 m and a maximum node transmission range of R T = 150 m. We also assume that the activity of the PU on different channels is identical.
Link maintenance probability
SU's data rate Figure 13 compares the effects of channel heterogeneity and PU activity on the SU data rate. Based on this figure, the higher transmission range leads to a higher data rate because the number of handoffs will be reduced. Therefore, the effect of channel heterogeneity in terms of transmission range and path loss must be considered on the performance of the integrated handoff management.
6.2 Simulation results
In this subsection, performance comparisons of three different schemes are conducted using Network Simulator 2 (ns-2) . To study the handoff blocking probability, three different handoff management schemes are considered. These three different versions of the handoff management scheme are defined as the SH scheme, the reactive unified spectrum handoff (USH) scheme and the proactive unified spectrum handoff (PUSH) scheme. The first scheme only deploys the spectrum handoff, while the remaining two schemes deploy the unified spectrum handoff in which the local flow handoff will be added to the management system. One of these two schemes, USH, does not consider the handoff threshold; whereas PUSH considers the handoff threshold for the preemptive handoff region.
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 are set to R1 = 75 m and R2 = 125 m. The mobile SUs are distributed in a network with a 2,000 m × 2,000 m area, and their speed is set to 3 m/s. The transmission range of the static PUs is set to 200 m, and the activity of PUs is modelled as a two-stage on/off procedure with an exponential distribution.
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 . The tw, l , which is the interval from the warning till the communication link break off, needs to be greater than or equal to the necessary time for performing the handoff.
Link maintenance, handoff blocking, handoff delay and spectrum handoff performance
In this part, the SU's route maintenance probability or handoff blocking probability is investigated. The handoff threshold time is set to 6 s, and both the PU's and the SU's arrival rates are set to be 0.25. The reactive AODV  routing protocol is used for route formation over CR-MANET.
Spectrum handoff management is still an open issue in CR networks. It is particularly challenging in CR-MANETs. In CR-MANETs, the available spectrum bands vary over time and space, while they are distributed nonadjacently over a broad frequency range. However, in CR-MANETs, the fluctuation of PU activity and the SU mobility make the issue of maintaining optimal routes more complex. In this work, we present an integrated spectrum handoff management and routing scheme that considers spectrum mobility in the time and space domains and considers the network topology variations. We propose a network architecture that considers the heterogeneous spectrum availability and its variation over time and space and distributed nodes. Then, the probability of channel availability in this dynamic radio environment is calculated. Based on this unified architecture, an integrated routing and spectrum handoff management scheme is proposed. The proposed scheme considers the CR-MANETs spectrum handoff problem and incorporates the routing issue. Both the analytical and simulation results verify the improvement in the network performance using the introduced management scheme.
SN is a researcher of the Universiti Teknologi Malaysia under the Post Doctoral Fellowship Scheme for the Project: 'SELF ORGANIZING INTELLIGENT-BASED COGNITIVE RADIO LEARNING SYSTEM FOR INTELLIGENT P-PUSH’.
This work was supported in part by the Ministry of Science, Technology and Innovation (MOSTI) Malaysia, and the Research Management Center (RMC), University Technology Malaysia under GUP research grant no. R. J130000.7923.4S063.
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