Voice Service Support over Cognitive Radio Networks

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1 Voice Service Support over Cognitive Radio Networks Ping Wang, Dusit Niyato, and Hai Jiang Centre For Multimedia And Network Technology (CeMNeT), School of Computer Engineering, Nanyang Technological University, Singapore Department of Electrical & Computer Engineering, University of Alberta, Canada Abstract In this paper, quality of service (QoS) provisioning for voice service over cognitive radio networks is considered As voice traffic is sensitive to delay, the presence of primary users and the requirement that secondary users should not interfere with them pose many challenges for QoS support for secondary voice users Two cognitive medium access schemes are proposed in this paper for the secondary voice users to access the available channel An analytical model is developed to obtain the voice service capacity (ie, the maximum number of voice users that can be supported with QoS guarantee) for the secondary users, taking the impact of primary users activities into consideration The analytical model is validated by the simulation The analytical results will be useful to support voice service in cognitive radio networks Keywords cognitive radio, medium access control, quality of service (QoS), voice service capacity, delay, packet loss I INTRODUCTION Cognitive radio, the idea firstly introduced by Mitola [], [2] and recently promoted by the US Federal Communications Commission (FCC) [3], provides an effective and efficient solution for the paradox between the shortage of the wireless spectrum resources and the under-utilization of the licensed spectrum An opportunistic (or cognitive) spectrum access approach has been proposed to allow the unlicensed users (also called secondary users) to exploit the spectrum that is not being used by the licensed users (also called primary users) [4] In this manner, a highly economical and efficient usage of the frequency spectrum can be achieved while allowing primary users to enjoy their licensed spectrum without facing any interference from the secondary users Because of this property, cognitive radio has recently drawn a lot of attention in academia [], [6], [7], [8], [9] Many research efforts focus on addressing the cooperative sensing of the primary users activities at the physical layer [6], [7], and little work has been done at the medium access control (MAC) layer In this work, our goal is to support the quality of voice service for secondary users at the MAC layer, and we assume that perfect channel sensing can be achieved at the physical layer The presence of primary users and the requirement of secondary users not interfering with them pose many challenges for quality of service (QoS) provisioning for secondary users First, an efficient and low-complexity cognitive medium access control scheme is needed for secondary users to share the available spectrum unoccupied by the primary users Second, in order to guarantee the QoS of voice service for secondary users, it is critical to obtain the voice service capacity (ie, the maximum number of voice users that can be supported), taking the impact of primary users activities into consideration In this paper, we propose two cognitive medium access schemes for the secondary voice users to access the wireless spectrum, and we also develop an analytical model to obtain the voice service capacity for these two cognitive medium access schemes The analytical results are validated by simulations The analytical results reveal how the activities of the primary users and the different cognitive medium access schemes affect the cognitive voice user capacity The analytical model can be used for the cognitive radio resource management and call admission control II THE SYSTEM MODEL Cognitive communication technology has been studied for different wireless networks including wireless metropolitan area networks (WMANs) and wireless local area networks (WLANs) [], [] In this paper, we consider a WLAN, where the activities of all the primary users can be sensed by all the secondary users The network has a single wireless channel, which is shared by all the primary and secondary users The channel is time-slotted We assume that at each time slot, a primary user will not occupy the channel with probability P i At the beginning of each slot, the secondary users sense the activity of the primary users If the channel is sensed idle, the secondary users can exploit the availability of the channel Constant rate voice traffic is supported for the cognitive users As voice traffic is sensitive to delay, a voice packet with a large delay will be considered useless Therefore, if a voice packet cannot be delivered successfully during the delay bound after its generation, it will be dropped by the voice sender In order to maintain satisfactory voice quality, the voice packet dropping probability should not be higher than a threshold P l Usually the threshold is set to be % III COGNITIVE MEDIUM ACCESS In cognitive networks, a cognitive medium access control scheme is needed for the secondary users to efficiently share the available wireless channel when the primary users are not active A cognitive medium access control scheme has two basic functions The first is to ensure that the secondary users will not interfere with the primary users The second is to achieve low-complexity, highly efficient, and fair medium access among secondary users Different cognitive medium access schemes may have different performance (eg, resource utilization), leading to different system capacities for secondary users In this section, two cognitive medium access control schemes are proposed One is contention based, and the other is contention-free The system capacities (ie, the voice service capacity) for these two schemes are analyzed in Section IV

2 ??? time slot channel time?sensing part?contention part transmission part?ack part Fig A time slot structure A Contention-Based Medium Access A time slot is further divided into four parts, as shown in Fig The first part is called sensing part, which is used for all the secondary users to sense the activities of the primary users If the channel is sensed busy, no secondary user should contend for that slot The second part is called contention part, consisting of a number of mini-slots Each secondary user has a contention window Prior to every contention, each secondary user randomly chooses a backoff timer from the contention window Then the secondary user starts to sense the channel If the channel has been sensed idle for a duration of the backoff timer (in unit of mini-slots), the secondary user will transmit its packet; Otherwise, it will quit the contention for the current slot Thus, for each contention, the secondary user with the smallest backoff timer will win and transmit its packet in the third part (ie, transmission part) of the slot Note that it is possible that more than one secondary user may choose the same smallest backoff timer, resulting in a collision In order to determine whether or not a packet has been successfully transmitted, a receiver sends acknowledgment at the fourth part of each slot (which is at the end of each slot) to the sender upon a successful packet reception B Contention-free Medium Access Similar to the contention-based medium access, a time slot is also divided into four parts in the contention-free medium access The difference is that in the second part, the secondary users do not follow the backoff mechanism Instead, each minislot in the second part is assigned to a secondary user in a deterministic way (the mini-slot assignment procedure is to be discussed) A secondary user (say user A) with mini-slot index i first senses the channel from mini-slot to mini-slot i If the channel keeps idle (ie, no secondary user with minislot index smaller than i has packet to transmit), then user A can start transmission from mini-slot i till the end of the transmission part If the channel becomes busy from any minislot prior to mini-slot i, which indicates that another secondary user with a smaller mini-slot index has already started its transmission, user A should not transmit in the current slot Since a single secondary user will be assigned to one minislot, a collision-free medium access can be achieved Note that the chance that one user transmits in a slot largely depends on its mini-slot index The smaller the index, the larger the chance In order to maintain fair medium access among all the secondary users, the mini-slot index will be rotated after each slot For example, the user associated with the first minislot in the current slot will have the last mini-slot index in the next slot, and the user associated with the second mini-slot in the current slot will have the first mini-slot index in the next slot, and so on If the number of secondary users in the cognitive network is fixed, the mini-slot assignment procedure can be done once at the initialization of the network If the secondary users dynamically join or leave the cognitive network, a mini-slot assignment procedure needs to be performed upon every user joining and leaving events Any existing secondary user can be designated to perform the mini-slot assignment procedure We denote the secondary user who is in charge of the minislot assignment as MSA (Mini-Slot Assigner) When a new secondary user wants to join the cognitive network, it first broadcasts a JOIN message Upon receiving the JOIN message, the MSA sends a JOIN-ACK message, which includes the assigned mini-slot index, to the new user Similarly, when a user leaves the cognitive network, it also broadcasts a LEAVE message The MSA will then re-assign the mini-slots to all the existing secondary users, and broadcast the new assignment result to all the secondary users When the MSA leaves the cognitive network, it designates another existing user to perform the mini-slot assignment task before leaving, and includes in the LEAVE message the new MSA ID and information of other existing users Upon receiving the LEAVE message from the current MSA, the new MSA will then re-assign the mini-slots and broadcast the new result to all the existing secondary users The JOIN/JOIN-ACK/LEAVE message is given high priority to be sent, compared with voice packets To achieve this, the first mini-slot (we call it mini-slot ) in the second part of a slot is dedicated to the users with JOIN/JOIN-ACK/LEAVE message A user with JOIN/JOIN- ACK/LEAVE message can transmit starting from the first minislot, while the users with voice packets have to monitor the channel in the first mini-slot If the channel is busy, the users with voice packets should not transmit in the current slot As JOIN/JOIN-ACK/LEAVE message is sent infrequently, collisions caused by more than two simultaneous JOIN/JOIN- ACK/LEAVE transmissions in one slot are negligible IV ANALYTICAL MODEL A Voice service capacity analysis In order to guarantee QoS of voice traffic, it is critical to have appropriate call admission control Call admission control is responsible for admitting or rejecting a new voice call based on the available resources, to ensure that the QoS requirements (eg, delay and packet loss rate) of all the admitted voice calls are satisfied To facilitate call admission control, it is essential to obtain the system capacity In cognitive networks, the system capacity for the secondary users is related to the number of primary users and their activities, and also related to the performance of the cognitive medium access scheme In this section, we present an analytical model to derive the voice service capacity for aforementioned two proposed cognitive medium access schemes For simplicity, we assume that the channel sensing at the physical layer always provides a correct outcome (our model can be easily extended to the case where

3 ,, -, -,2 -Ps,T a - - 2, T -P - s a 2,T a + 2,T a +2 3,2T a - 2,2T a - - n-,t i n-,t i + n-,t b -T a n-,t j - n,t j - n,t j+ n,t b - Fig 2 The state transition diagram the channel sensing error exists) Without loss of generality, we assume that one time slot is used to transmit one voice packet Let T s denote the time of one slot For presentation simplicity, we set T s = Denote the voice packet inter-arrival time and the voice packet delay bound as T a and T b (both in the unit of time slot), respectively We arbitrarily choose a secondary voice user as the tagged user Define state (n, t), where n is the number of voice packets in the queue of the tagged user, and t is queueing delay (in the unit of time slot) experienced by the voice packet that is at the head of the queue of the tagged user The initial state is (,), indicating that there is no voice packet at the tagged user As constant rate voice traffic is considered, after a certain time period (no more than the voice packet inter-arrival time T a), the first voice packet will arrive at the tagged user Therefore, the state will move to (,) with probability Since then, after each time slot, the state will evolve, moving to another state The state transition process is modeled by a discretetime Markov chain, shown in Fig 2 To describe this Markov chain, we use state (i, t k ) (i > ) as an example When t k < i T a, its next state is (i, t k + ) if the tagged user does not successfully transmit a voice packet in the current slot, (i, t k T a + ) if the tagged user successfully transmits a voice packet in the current slot Note that since voice traffic has a constant rate, the voice packet inter-arrival time T a is a fixed value For any two consecutive packets in the queue, the difference of their queuing delay (ie, the waiting time in the queue, not including the time in packet transmission) equals to T a When t k = i T a, its next state is (i +, t k + ) if the tagged user does not successfully transmit a voice packet in the current slot, (i, t k T a +) if the tagged user successfully transmits a voice packet in the current slot This is because when the delay of the packet at the head of queue equals to i T a, a new voice packet will arrive after one time slot Let denote the probability that the tagged secondary user - successfully transmits a voice packet in a randomly chosen time slot, given that the tagged user has packets to send, and P(n, t n, t ) denote the transition probability from state (n, t ) to state (n, t ) In the Markov chain, the one-step transition probabilities are P(,, ) = P(, t j +, t j ) =, t j < T a P(,, t j ) =, t j < T a P(2, t j +, t j ) =, t j = T a P(,, t j ) =, t j = T a P(i, t j + i, t j ) =, t j < it a, i 2 () P(i, t j + T a i, t j ) =, t j < it a, i 2 P(i +, t j + i, t j ) =, t j = it a, i 2 P(i, t j + T a i, t j ) =, t j = it a, i 2 P(i, T b T a i, T b ) =, if T b < it a P(i, T b T a i, T b ) =, if T b = it a Given all the one-step transition probabilities of the Markov chain listed in (), the steady state probability vector of the Markov chain can be obtained Denote π(i, t j ) as the steady state probability of state (i, t j ) Next, we derive for the two proposed cognitive medium access schemes The voice packet arrival rate of each secondary user is T a packets per slot The voice packet service rate of each secondary user is denoted as µ packets per slot Thus, the queue utilization of the secondary user is given by ρ = T a µ As aforementioned in Section II, at each time slot, a primary user will not use the channel with probability P i Thus, the probability that the channel is available for the secondary user to access P p idle = (P i) Np, where N p is the total number of primary users For the contention-based medium access, is given by = P p idle ( k )ρ (Ns ) (2) k= where N s is the total number of secondary users, and is the contention window size of the secondary users The term in the summation indicates the probability that the tagged user chooses a backoff timer value k, and other active secondary users (ie, the users whose queues are not empty) choose backoff timer values larger than k For the contention-free medium access, is given by N s = P p idle ( ρ) i (3) N s i= where the term in the summation indicates the probability that for a randomly chosen slot, the tagged user has mini-slot index i, and all other secondary users with mini-slot index smaller than i have no packet to transmit To determine ρ, we need to characterize the average service time of a voice packet Given that the voice packet at the µ head of the queue has already waited t j slots, the average time (in the unit of slot) needed to serve this packet T s(t j ), ie, the

4 time to let the packet leave the queue (either due to successful transmission or due to packet dropping), is given by T s(t j ) = T b t j k= ( ) k k+( ) T b t j (T b t j ) (4) The average service time of a voice packet µ µ = t j = π(m(t j), t j ) T s(t j ) t j = π(m(t j), t j ) is derived as where m(t j ) is the corresponding number of voice packets in the queue, given that the queueing delay of the voice packet at the head of the queue is t j With a constant voice packet arrival rate T a, it is straightforward to have tj + m(t j ) = T a Given equations (), (4), and (), along with equation (2) or (3), can be solved numerically for the two proposed cognitive medium access schemes The steady state probability vector for the Markov chain can further be obtained Let P drop denote the voice packet dropping probability P drop can be expressed as P drop = () t j = π(m(t j), t j ) ( ) T b t j t j = π(m(t (6) j), t j ) Note that P drop is a function of N s, denoted by P drop (N s) In order to guarantee the QoS of voice traffic, P drop (N s) should not exceed the voice packet dropping rate bound P l Thus, the capacity for voice service of secondary users is the maximum integer N s (denoted by N s ) satisfying P drop (N s) P l B Average overhead In addition to voice service capacity, the other important performance metric of the proposed cognitive medium access is the average overhead, which is measured as the average number of mini-slots needed in each slot before a successful transmission Let O c and O f denote the average overhead of the contention-based and the contention-free medium access schemes, respectively We have N s ( Ns ) ( O c = ρ i ( ρ) Ns i i i ( j ) )i j, i= j= where the term ( N s i ) ρi ( ρ) Ns i indicates the probability that out of N s, i secondary users are active in a random slot, and the term in the second summation indicates that j mini-slots are needed before a successful transmission when an active secondary user chooses a backoff timer value j, and other active secondary users choose backoff timer values larger than j For the contention-free medium access, we have O f = Ns i= ρ ( ρ)i i Ns, i= ρ ( ρ)i where the denominator is the probability of a successful transmission in a randomly chosen slot, and the term in the summation in the numerator indicates that the number of minislots needed before a successful transmission is i when all the The cognitive voice capacity 3 2 Contention, Analysis Contention, Simulation Contention free, Analysis Contention free, Simulation Fig 3 The cognitive voice capacity with P i = 9% secondary users with mini-slot index smaller than i have no packet to send, and the secondary user with mini-slot index i has packet to send V NUMERICAL RESULTS AND DISCUSSIONS We validate our analytical results by simulations using Matlab The simulation for each run consists of time slots Without loss of generality, we choose T a = 4 and T b = 4 The voice packet dropping rate bound P l is set as % We vary the other parameters such as N p, P i, and to investigate their impact on the voice service capacity A Voice Service Capacity First, we fix the value of P i as 9% and the contention window size as 4 mini-slots, and vary the number N p of primary users in the system The cognitive voice service capacity (ie, the maximum number N s of secondary voice users that can be supported with QoS guarantee) is calculated by using the proposed analytical model The analytical results are shown in Fig 3 It can be seen that when the number of primary users increases, the capacity of secondary voice users decreases due to the reduced available channel resources The capacity of the contention-free medium access is larger than that of the contention-based medium access The reason is that the contention-free medium access utilizes the channel more efficiently than the contention-based medium access by eliminating collisions, resulting in a larger capacity The simulation results are also shown in Fig 3 In the simulation, if a voice packet cannot be delivered within the delay bound T b, it will be dropped Voice capacity is obtained as the maximum number of voice users such that the voice packet dropping rate is less than P l As shown in Fig 3, the simulation results match well with the analytical results in all cases Next, we change P i from 9% to 92%, the corresponding capacities of the two proposed medium access schemes are shown in Fig 4 It is obvious that with a lower P i, fewer channel resources are left for the secondary users, leading to a smaller capacity Again, the simulation results conform to the analytical results For the contention-based medium access, the choice of also has impact on the capacity Fig compares the capacity

5 The cognitive voice capacity 2 Contention, Analysis Contention, Simulation Contention free, Analysis Contention free, Simulation TABLE I THE AVERAGE OVERHEAD OF THE TWO PROPOSED COGNITIVE MEDIUM ACCESS N s Contention based Analysis = Simulation Contention based Analysis = 4 Simulation Contention-free Analysis Simulation Fig 4 The cognitive voice capacity with P i = 92% The cognitive voice capacity 2 =4, Analysis =4, Simulation =, Analysis =, Simulation 4 Fig The cognitive voice capacity of the contention-based medium access with P i = 9% and different for the contention-based medium access with two different sizes When the number of primary users is small, a relatively large number of secondary users can be admitted A larger can effectively reduce the collisions among them, resulting in a slightly larger capacity However, with the increase of primary users, less secondary users can be admitted into the system (eg, less than 7 secondary users can be admitted when the number of primary users is larger than from Fig ) With a small number of contenders, collisions rarely occur Therefore, a larger cannot help to increase the capacity Note that with a small size of, the collision probability may be high, while a large size of can alleviate the collisions However, the overhead also increases Therefore, there exists a tradeoff How to choose an optimal size is an interesting problem and will be studied in our further research B Average Overhead To obtain the average overhead (ie, the average number of mini-slots needed before a successful transmission), we fix the value of N p as, P i as 9%, and vary the number of secondary users in the system Table I compares the analytical and simulation results of the average overhead of the two proposed medium access schemes For the contention-free medium access, when the number of secondary users increases, the average overhead increases since more mini-slots are needed to accommodate the secondary users For the contention-based medium access, the average overhead decreases when the number of secondary users increases The reason is that with a fixed size, the larger the number of contenders, the more chances that the winner (ie, the contender with the smallest backoff timer) will choose a smaller backoff timer For the similar reason, with a smaller size, the average overhead for the contention-based medium access will be smaller, as shown in Table I Note that this result does not mean that a small is favored for the contention-based medium access As small may cause serious collisions, the resources wasted by collisions should also be taken into account when choosing VI CONCLUSION In this paper, we have proposed two different cognitive medium access schemes to support the cognitive voice service in presence of primary users The analytical model is developed to investigate the performance of the two cognitive medium access schemes, including voice service capacity and average overhead The correctness of the analytical model is verified by the simulation This work can provide helpful insights to voice service support over cognitive radio networks REFERENCES [] J Mitola, Cognitive radio: An integrated agent architecture for software defined radio, Doctoral dissertation, Royal Inst Technol (KTH), Stockholm, Sweden, [2] J Mitola and GQ Maguire Cognitive radio: Making software radios more personal, IEEE Personal Communications, vol 6, no 4, pp 3 8, Aug 999 [3] Federal Communications Commission, Cognitive Radio Technologies Proceeding (CRTP), ET Docket No 3-8 [Online] Available: [4] S Mangolld, Z Zhong, K Challapali, and C-T Chou, Spectrum agile radio: radio resource measurements for opportunistic spectrum usage, in Proc IEEE GLOBECOM 4, vol 6, pp , Dec 4 [] S Haykin, Cognitive radio: Brain-empowered wireless communications, IEEE J Sel Areas Commun, vol 23, pp 2, Feb [6] S Mishra, A Sahai, and R Brodersen, Cooperative sensing among cognitive radios, in Proc IEEE ICC 6, pp , June 6 [7] J Zhao, H Zheng, and G-H Yang, Spectrum sharing through distributed coordination in dynamic spectrum access networks, Wireless Communications and Mobile Computing, in press [8] J Mitola, Cognitive radio for flexible mobile multimedia communications, Mobile Networks and Applications, vol 6, no, pp 43 44, [9] H Jiang, L Lai, R Fan, and H V Poor, Optimal selection of channel sensing order in cognitive radio, IEEE Trans Wireless Commun, vol 8, 9 [] C-T Chou, N Sai Shankar, H Kim, and K G Shin, What and how much to gain by spectrum agility? IEEE J Sel Areas Commun - Wireless Series, vol 2, no 3, pp 76 88, April 7 [] S Geirhofer, L Tong, and B M Sadler, Cognitive medium access: A protocol for enhancing coexistence in WLAN bands, in Proc IEEE GLOBECOM 7, Washington, DC, Nov 7

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