Without loss of generality, it is assumed that all the existing CR users are initially located and operated on different frequency spectrums. The information that the oc-cupancy of each channel by its corresponding CR user is available to all the CR users.
In the case that a CR user intends to conduct spectrum handoff, it will broadcast a handoff message on the common control channel in order to announce all the users re-garding the change of network condition. Since there may exist more than one CR user that need to broadcast its handoff message simultaneously in the same time slot, there is potential that these messages from different CR users can collide with each other.
A random backoff contention window is therefore utilized in the proposed M-POSH scheme in order to resolve the potential packet collision problem. Each CR user that intends to delivery the handoff message on the control channel will wait for a random number in a pre-specified interval such as to ensure the message can be successfully received.
The handoff message includes three fields as follows: (a) access number, (b) original channel, and (c) candidate set of target channels. The access number is assigned to each CR user that intends to perform spectrum handoff, whose value is randomly selected by the CR user within a predefined interval. The original channel field records the ID of the channel that the CR user is currently in use before handoff. The candidate set of target channels for each specific CR user denotes the available channels to potentially conduct spectrum handoff, i.e. Dr = [dr,1, ..., dr,n] where dr,i represents the ith priority in the target channel set of user r. The procedure for user r to acquire the candidate set of target channels Dr can be expressed in Algorithm 1 as follows.
The concept of the candidate set of target channels for each CR user is to acquire the formation of unoccupied channels based on the criterion of minimal waiting time.
As shown in Algorithm 1, the target candidates are selected sequentially based on the
corresponding cost function Ψ. It is noted that the parameter m denotes the number of CR users that intend to conduct spectrum handoff at time slot k, which consist of the user set Rm. If the selected action is observed to exist in ˜Ak, the chosen a∗ will be replaced by the original channel and recorded in the candidate set. As a result, this replacement criterion can ensure that none of the CR user’s candidate set Dr will be identical. This can facilitate the negotiation process will for the CR users to select a designate target channel from their candidate set, which will be described as in Algorithm 2.
Algorithm 1: Acquiring Candidate Set of Target Channels Dr for User r Input : ˜Ak with size (?? n), Ak with size N
Add original channel to Dr 9
end
10
end
11
As illustrated in Algorithm 2, after collecting the information of handoff message from the m CR users, the target channel for each user can therefore be determined by a negotiation procedure between the users. Let Tk denotes the set of target channel that are selected by the CR users at the occurrence of spectrum handoff in time slot
CR users within the network can choose its target channel without collision with the other CR users. It is noticed that with the consideration of other CR traffic within the network, the occupied channel sets of CR users ˜Ak will also be updated based on the information from both the original channel and the target channel of the user set Rm that conduct spectrum handoff. In summary, the proposed M-POSH protocol can provide a negotiation mechanism for each CR user to select its target channel without being collide with the selection made by other CR users in the network.
Algorithm 2: Selection of Target Channel Input : Dr with size n, Rm with size m Output: Target channel of each CR user ak,r foreach CR users in Rm do
Chapter 6
Performance Evaluation
In this chapter, simulations are presented to demonstrate the performance of proposed POSH and M-POSH protocols. The major focus in the simulations is to obtain the re-quired waiting time slots for the secondary user while it has been directed to the target channel. Since full channel state information is required by all of the existing spectrum handoff algorithms, it is considered unfair to compare the existing schemes within the environment adopted by the proposed POSH and M-POSH algorithms, where only par-tial channel information is observable. Therefore, the proposed scheme will be compared with two different cases as mentioned in Section 4, including both the NSH scheme and the RCS mechanism. The traffic of the primary user follows the poison distribution, and the service time is assumed to be a uniform distribution with mean 1/µ = 1.
Three channels are considered in the simulations, i.e. sk = [c1,k, c2,k, c3,k]; while the discount factor in (3.10) is selected as ρ = 1. The reduced state strategy is utilized in the simulations to obtain the numerical results of the POMDP-based optimization
0.1 0.2 0.3 0.4 0.5 0.6
Traffic Arrival Rate (λ)
Expected Number of Waiting Slots
Figure 6.1: Performance validation: the number of waiting time slots versus traffic arrival rate.
6.1 Model Validation
The analytical models for required waiting time slots of the three schemes, including POSH, NSH, and RCS algorithms, as presented in (4.1), (4.3), and (4.7) are validated via simulations results as shown in Fig. 6.1. It can be observed that the expected number of waiting time slots from all these three schemes increase as the traffic arrival rate (λ) of the primary user is augmented. Under different arrival rates, the proposed POSH algorithm can provide the smallest waiting time slots comparing with the other two schemes. Furthermore, it can also be seen that the simulation results of both NSH and RCS schemes match with their corresponding analytical results. On the other hand, there exists slight difference between the analytical and simulation results of the proposed POSH scheme. The major reason for this deviation can be contributed to the imprecise modeling of POSH scheme based on stationary probabilities.
In order to clearly illustrate the difference between these two results, the biased percentage β is introduced and is defined as β = naw,ζns−nsw,ζ
w,ζ × 100 where naw,ζ and nsw,ζ correspond to the expected waiting time slots obtained from analysis and simulation
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Traffic Arrival Rate (λ)
Biased Percentage (β)
RCS & NSH POSH with 106 slots POSH with 105 slots POSH with 104 slots
Figure 6.2: Performance validation: the biased percentage β versus traffic arrival rate.
respectively. The parameter ζ indicates the either one of the three spectrum hand-off schemes. Fig. 6.2 illustrates the biased percentage β for the three schemes under different traffic arrival rates. It is noted that the proposed POSH method is imple-mented under the simulation runs with different number of transmission time slots, i.e.
T = 104, 105, and 106. It can be observed that even the behavior of belief state can not be exactly modeled and analyzed, the analytical results derived by stationary proba-bility can still approach to the simulation values within 3% of estimation difference. It can also be seen from Fig. 6.2 that the bias can be diminished as the number of trans-mission time slots for the simulations are increased. This results reveal the case that with longer time of simulation, the incomplete network information can be updated more accurately. The simulation results will tend to possess stationary behaviors as is presented by the analytical model in (4.7).
0 20 40 60 80 100 120 140 160 180 200
Figure 6.3: Performance comparison: the number of waiting time slots versus the number of spectrum handoff.