Optimized in-band control channel with channel selection scheduling and network coding in distributed cognitive radio networks

The Journal of China Universities of Posts and Telecommunications April 2012, 19(2): 48–56 www.sciencedirect.com/science/journal/10058885

http://jcupt.xsw.bupt.cn

Optimized in-band control channel with channel selection scheduling and network coding in distributed cognitive radio networks LIU Yang (), FENG Zhi-yong, ZHANG Ping Wireless Technology Innovation Institute, Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China

Abstract This article proposes an optimized in-band control channel scheme with channel selection scheduling algorithm and network coding based transmission paradigm in the distributed cognitive radio network (CRN). As well known, control channel plays an important role for establishment of wireless transmission. In order to improve spectrum efficiency in CRN, control channel is preferred to be deployed without dedicated spectrum allocation, i.e. the in-band way. In this study, the time slot division and dynamic channel selection scheduling algorithm is proposed to realize the in-band control channel with improved spectrum efficiency in the distributed CRN. Furthermore, to adapt to dynamic behavior of the primary users, network coding technology is employed to optimize the overhead of control information transmission so that the control information can be efficiently and reliably transmitted. The performance of the proposed in-band control channel scheme is verified by the extensive simulation results. Keywords

cognitive radio networks (CRN), control channel, distributed architecture, in-band, network coding

1 Introduction With the explosive growth of capacity-hungry wireless services and technologies, the scarcity of available spectrum resource is becoming a serious problem. However, it is reported in Ref. [1] that, spectrum is inefficiently utilized due to the static spectrum allocation policy. Recently, CRN derived from the concept of cognitive radio (CR) proposed by Mitola [2], which is defined as the wireless network with the capability of reconfiguring its infrastructure based on the experiences learnt from the continuously changing environment [3], is proposed to improve the spectrum efficiency in the wireless network. The spectrum utilization can be improved by dynamic spectrum access (DSA) technology [4–5], which is the typical application of CRN. The spectrum licensed to the primary users (PUs) can be sensed by the secondary users (SUs) in CRN to decide whether it is idle or occupied by PUs. Then, the idle Received date: 31-07-2011 Corresponding author: LIU Yang, E-mail: [email protected] DOI: 10.1016/S1005-8885(11)60245-8

spectrum can be dynamically accessed by SUs without any interference to PUs. In order to improve the spectrum sensing accuracy, the negotiation or cooperation shall be performed among SUs via control information exchange to enable the establishment of the wireless link among SUs in CRN [6]. In CRN with the centralized infrastructures such as the basestations, the control information can be broadcasted by the basestations. However, for CRN without the centralized infrastructures, it is one of the most challenges in distributed CRN to design the control channel to perform the information exchange among the SUs. The approaches to design the control channel in CRN can be divided into two categories: one is dedicated spectrum is allocated for the control information exchange, i.e. out-of-band control channel. The other is control information is exchanged without the dedicated spectrum, i.e. in-band control channel. However, the dynamic availability of spectrum in CRN makes it difficult to maintain a dedicated control channel for out-of-band control channel scheme. Thus, the in-band control channel is preferred in the distributed CRN. For in-band control

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channel design in the distributed CRN, there are still several challenges. Firstly, the spectrum for control channel has dynamic availability due to PUs’ activity [7]. When the PUs will start to use the spectrum, a new control channel must be immediately established among SUs for the efficient and reliable control information exchange. In Refs. [8–9], the pre-defined hop-sequence of control channels is constructed by using permutations of the available channels. This design can be robust to PUs’ activity, but it requires the significant time to re-establish a new control channel, and it is not practical to reserve the pre-defined hop-sequence in the distributed CRN. In Refs. [10–11], a group-based approach is proposed for control channel assignment in the distributed CRN. By exchanging channel quality information, SUs adaptively update their choice of control channels. As more SUs in the same group gradually agree upon the selected control channels, this method reduces the number of control channels in CRN. However, when two neighboring SUs observe the heterogeneous channel quality conditions, the assignment may fluctuate with the updates of choices. Thus, the performance of this method is not consistent to PUs’ activities. Secondly, the spectrum efficiency shall be improved compared with the out-of-band control channel under the constraint of reliable control information exchange. In in-band method, control information and data information share the same spectrum so that the spectrum efficiency is improved, but it is necessary to design the appropriate channel selection scheduling of control information and data transmission in the same channel to guarantee the accuracy of the information transmission [12]. Lastly, the overhead of control information exchange shall be optimized due to the changeable availability of spectrum. If the overhead of control information exchange is too much, the PUs may be present to cause the failure of control information exchange. In Ref. [13], the overhead of control information exchange is modeled as the access latency, and polling is proposed to match the chosen control channel among SUs. The overhead can be optimized with the cost of reduced accuracy of control information. Moreover, the control channel tends to be saturated as the number of SUs increases. To summarize, the open issue of designing an in-band control channel scheme which can be completely distributed and provide an efficient usage of the spectrum, shall include an effective strategy for the identification of available spectrum resources, and does not rely on the dedicated

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spectrum resources. However, most of the proposed control channels in distributed CRN do not provide a comprehensive solution to all these issues above, but rather focus on a given subset of them. In this article, an optimized in-band control channel scheme is proposed for the distributed CRN. The scheduling algorithm of control information and data transmission is proposed in the in-band way so that the spectrum efficiency can be improved without any interference to PUs. The network coding (NC) technology is employed to optimize the overhead of control information exchange. Thus, the control information can be reliably and efficiently exchanged in the distributed CRN. The key principle on our proposed scheme is that SUs visit licensed channels in a pseudo-random fashion and exchange control information whenever they happen to meet in any channel. The control information exchanged by the SUs consists of all the information (such as intended receivers, PUs presence, etc.) which is needed to select channel switch patterns. The efficient dissemination of the control information to all SUs is achieved by means of NC. If the control information generated by each SU is successfully disseminated to all other SUs, then they can run the same DSA deterministic algorithm pre-defined with the same input information. Hence, channel allocation can be done in a distributed fashion without requiring a centralized control scheme. Given that all SUs already switch over all available channels in a pseudo-random fashion for control information dissemination purposes, it is possible for them to perform the comprehensive PU detection just by using a signal detection technique whenever they switch channel. The detection information by all SUs is then disseminated via the NC, so that every SU can independently run the same cooperative detection algorithm in order to determine the available spectrum resources. The use of cooperation provides the significant improvements with respect to the performance of a single detection attempt; thanks to this feature, the adoption of simple and cheap techniques, such as energy detection (ED) [14], can be very effective. The remainder of this article is organized as follows. Sect. 2 gives the system model and problem formulation. An optimized in-band control channel with channel selection scheduling (CSS) of control information and data transmission, employing NC technology to reduce the overhead of control information exchange, is proposed as the in-band NC-CSS scheme in Sect. 3. Sect. 4 analyzes the performances of the proposed in-band NC-CSS scheme

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from the spectrum efficiency, impact of PUs’ activity on control channel and the overhead of control information exchange. The numerical simulations in Sect. 5 are performed to show the performance improvement by in-band NC-CSS scheme compared with the existing control channel schemes. Finally, Sect. 6 concludes this article.

2 System model and problem formulation 2.1

System model

In this paper, as shown in Fig. 1, there are N SUs communicating with each other in the distributed CRN and opportunistically sharing the spectrum with M PUs. The spectrum is divided into C channels with the unit bandwidth, each of which can be expressed as Ck, (k = 1,

Fig. 1

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2,…,C). Transmissions of PUs and SUs are performed using the time division multiple access (TDMA) scheme in the access time period. SUs locating in the same cycle with PUs cannot access the same channel, e.g. The SU5 locates in both cycles of PU1 and PU2 so that its available channels are {C3, C4}, because channels {C1, C2} are accessed by PU1 and PU2 respectively. When any PU is sensed to be present, SUs must release the accessed channel. Therefore, SUs have to dynamically access the available channels. Control information shall be reliably and efficiently exchanged by SUs without an infrastructure to avoid collision among PUs and SUs. Furthermore, from the principle of DSA to improve spectrum efficiency, there is no dedicated spectrum allocated to SUs as control channel.

Opportunistic spectrum sharing in distributed CRN

For detection, cooperation detection among SUs is considered. This implies that it is possible to successfully adopt the simple detection techniques such as energy detection, which can reduce the complexity and cost of the detector compared with the sophisticated techniques such as cycle-stationary feature detection. As analysis in Sect. 1, if the control information generated by each SU is successfully disseminated to all other SUs, then they can run the same DSA deterministic algorithm pre-defined with the same input information. Hence, channel allocation can be done in a distributed fashion without requiring a centralized control scheme. The detection model can be referred to Ref. [15] as below: Let now dn,s(t)={0,1} be the output of a detection attempt, where dn,s(t)=1 if SU n detects the presence of a

PU in slot s of the allocation time period t (positive detection), and dn,s(t)=0 otherwise (negative detection). This detection information, gathered in the allocation time period t, is then disseminated to all SUs during the allocation period t+1. After dissemination, and just prior to determining the channel allocation and switch pattern, the cooperative detection is performed for the every channel Ck, k = 1,2,…,C. This is done by counting the number of positive detections Dc(t) as below: N

Dc ( t ) = ∑∑ d n, s ( t ) n =1

(1)

s

If Dc(t) is greater than a pre-defined threshold, then it is inferred that channel Ck is being used by a PU. In this way, the set of free channels available for secondary access is determined, and then can be used to determine the channel

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allocation. 2.2

Problem formulation

As introduced above, the in-band control channel shall be considered to improve spectrum efficiency so that it is essential to design the channel selection algorithm for scheduling of control information and data transmission in the same channel. The spectrum efficiency of system can be defined as follows [16]: ⎡ C ⎤ Xi ⎥ ∑ ⎢ E {η} = E i =1 (2) ⎢ ⎥ ⎣ C ⎦ where E {η} denotes the average spectrum efficiency. The channels are identified as Ck, k = (1,2,…,C). Xi equals to 1 if channel Ck contains a correct information transmission including control and date information, and equals to 0 if there is no or false transmission happening. Intuitively, the spectrum efficiency E {η} is related to the probability Pe which denotes that a generic SU correctly exchanges control information. Furthermore, due to the changeable PUs’ activities, SUs must release the accessed channels even if the control information transmission is not finished while PU abruptly activates. Therefore, the overhead of control information exchange shall be optimized to adapt to changeable PUs’ activities. In this paper, the overhead performance is defined as E {o} [16], which is the number of time periods required for successful exchanging control information of all SUs under constraint of the probability Pe.

Fig. 2

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From analysis above, the problem of in-band control channel design can formulated as: max E {η } ⎫ ⎪ s.t. PePh ⎪ E{o}Oh ⎪ ⎪⎪ (3) C0 ⎬ ⎪ X i = 1, or 0 ⎪ 0Pe 1 ⎪ ⎪ o0 ⎪⎭ where Ph and Oh are the threshold for Pe and E {o} required by system.

3 Proposed in-band NC-CSS scheme 3.1 In-band control channel scheme with channel selection scheduling (CSS) We assume that channels are accessed in TDMA scheme with access time period of T, which can be considered as the allocated time period t. In the proposed in-band NC-CSS scheme, the time period T sensed to be accessed by SUs, can be divided into three slots T=S1+S2+S3 as in Fig. 2. All SUs are synchronized at the slot level. The first slot S1 is used to perform spectrum sensing, the second slot S2 is used for transmission of application data, and the third slot S3 is used to exchange control information, e.g. for channel C3 in time period 1, SU 2 transmits the application data, and SUs {2, 4, 6} can exchange control information. T and C are the fixed system parameters.

Proposed in-band control channel with time slot division

S1 is related with the complexity of spectrum detection algorithm, and in this article it can be fixed and ignored since it is assumed that the perfect detection is performed in this article. For S2 and S3, there is E( S2 ) = T − S1 − E ( S3 ) , since S2 and S3 are both related with transmission detail in various time periods. Then, it shall be considered

how to schedule to pair the SUs and slots of channels which for application data or control information transmission. It is assumed that Cs = {Cs1,Cs2,…,CsL, L < N} denotes the sensed channels available for SUs. For each time period t and CslCs, uc(t) denotes the pair scheduling of which SU u transmits the application data in available

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channel Ck, and matrix U(t) = [uc(t)]N×C. Furthermore, for control channel scheduling, it can be expressed as matrix V(t) = [vu(t)]C×N, in which vu(t) denotes which the control slot of channel shall be accessed by SU u in time period t. Both of U(t) and V(t) can be constructed by the channel selection scheduling algorithm fy[ ⋅ ], and we have U(t) = fu[U(t − 1)] and V(t) = fv[V(t − 1)]. Then, U(t) and V(t) from SU u can be formed into the control information packet bu(t), so B(t) = {bu1(t),bu2(t),…,buN(t)} denotes the whole control packets to send to all SUs, which means that the control information includes the pair set of SUs participating transmission and their channel selection decision. If control information B(t) fails to be sent to a certain SU, the SU will mistake the channel scheduling so that the data transmission will fail. The channel selection scheduling (CSS) algorithm fy[ ⋅ ] can be elaborated as follows: Step 1 Initialization: let time period t=1. Make Cs= ∅ denotes the set of available channels sensed by SUs. U(t)={0} and V(t)={0} denotes the output matrixes of channel selection scheduling decision. Rs={1,2,…,Nr, Nr |Cs|. For

( N 2 ) |Cs|,

the channel selection scheduling is

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insignificant because there are enough idle channels for SUs. Thus, in our algorithm above, just the case of ( N 2 ) > |Cs| is mainly considered that all of the idle channels in Cs are allocated but there are still SUs left in Rs as Step 5. For ( N 2 )|Cs|, when all of the SUs in Rs are allocated the idle channels, i.e. Rs= ∅ , the channel selection scheduling will restart for the next time period as Step 4. Furthermore, for ( N 2 )|Cs|, there will be no SUs left without any idle channel allocated. Otherwise, for ( N 2 ) > |Cs|, some SUs must be left without the idle channel allocated, and the left SUs who cannot access the idle channel will be instructed to switch to a busy channel Ck{C − Cs} to do detection as Step 5. That is to say, the left SUs, which switch to a busy channel for detection, will not perform any transmission on that busy channel; for this reason, the performance of the transmission process will degrade when the fraction of the busy channels increases. Therefore, the choice of the exact number of SUs assigned to the detection task creates a tradeoff between the detection performance on one side, transmission and spectrum reuse efficiency on the other side. 3.2 Control information exchange via NC technology As analyzed above, if control information transmission fails, the performance of DSA operation will degrade so that the SU will also fail to transmit the application data. Due to the dynamic PUs’ activity, the transmission efficiency will be degraded for the control information exchange among SUs. Therefore, NC technology is employed to optimize the transmission efficiency against the impact of the dynamic PUs’ activity in our in-band NC-CSS scheme. NC technology is a data dissemination paradigm according to which packets generated by multiple sources are jointly processed at intermediate nodes in order to increase throughput, reduce delay and enhance robustness [17]. In the proposed in-band NC-CSS scheme, the original control information packet B(t) shall be encoded before the transmission of control packets based on the linear NC technology. In order to have a practical implementation of network coding, we refer to Ref. [18], where the authors propose a distributed scheme for practical network coding which obviates the need for a centralized knowledge about the encoding and decoding functions and, at the same time, allows asynchronous data exchange between nodes.

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According to the NC technology in Ref. [18], each of the SUs generates a control packet which is represented as a vector of symbols over the Galois field GF(2q) and stores it in the buffer. Every time a generic SU n is scheduled to perform transmission, it generates and transmits a linear combination of all the packets contained in its buffer. Equivalently, upon reception it stores the received packet in the buffer which after d receptions will contain Be(t) = [e1(t), e2(t),…, ed(t)]d×1, d1 , i.e., d coded packets that are linear combinations of the original packets bun(t) with coefficients GdN = [gun]d×N, n{1,2,…,d}, 1nN . That is, Be(t) = GdNB(t) where each row ρ of GdN contains the encoding cofficients gun associated to eρ(t). Note that if SU n has no packet to transmit, its original packet bn(t) will be bn(t)=0. Now, if the encoding vectors are generated randomly and their coefficients lie in a finite Galois field GF(2q) of sufficient size, GdN has full rank with high probability for dN [18]. Based on this approach, each node has to know the coefficients of the matrix GdN in order to decode all the information. To do so, we append within each transmitted packet, along with the coded packet eρ(t), the SU identifier u, and the corresponding N-dimensional encoding vector gρu that describes which linear combination of the source packets it contains. This way, the global encoding vectors needed to invert the encoding matrix at any receiver can be found within the incoming packets. Any SU identifier u can thus recover the control packets Be(t) by inverting the matrix GdN. Appending the encoding vectors to the packets will incur the additional overhead, which will be accounted for in the determination of the total control overhead of our in-band NC-CSS scheme. As to the identifiers to be used, the same practical considerations discussed in Sect. 3.1 apply. In this way, we obtain a fully distributed and efficient coding scheme which is robust against packet losses, as shown below: Step 1 Let counter d=1. SU u generates original control information packet bun(t) and NC encoding coefficient vector GdN = [gun]d×N, n{1,2,…,d}, 1nN . The encoding coefficient vector gρuGF(2q) can be generated from the Galois field GF(2q) and q is system parameters [19]. Store the encoded control information packet eρ(t)= gρubun(t) in buffer. Step 2 Do linear combination of encoded control information packet eρ(t) as long as SU u receives the new encoded control packet eγ(t) from another SU. Let Be(t) = [e1(t), e2(t),…, ed(t)]d×1, d1 .

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Step 3 NC encoding coefficient matrix is GdN = [gun] d×N, n{1,2,…,d}, 1nN . If GdN has full rank, the whole encoded control information packet Be(t) is sent to all SUs in in-band control channel. Otherwise, repeat from Step 1 and counter d=d+1. Finally, the whole encoded control information packet Be(t) can be expressed as follows: ⎡ g11 g12 ... g1N ⎤ ⎡ b1 (t ) ⎤ ⎢g g22 ... g 2 N ⎥⎥ ⎢⎢ b2 (t ) ⎥⎥ Be (t ) = GdN B(t ) = ⎢ 21 (4) ⎢ M M M ⎥⎢ M ⎥ ⎢ ⎥⎢ ⎥ ⎣ g d 1 g d 2 ... g dN ⎦ ⎣bN (t ) ⎦ Note that the NC technology in Ref. [18] has the static dimension of the encoding matrix. Even if there are some SUs without transmission requirement, they should be considered during the NC process (their original packets bn(t) will be bn(t)=0). Thus, the cost of SU devices such as processor and memory buffer will increase. However, compared with the improvement of the transmission efficiency of control information, the increased cost of SU device can be ignored, especially for some important scenarios such as military and emergency.

4 Performance analysis As shown in Sect. 2, the performance of control channel design in CRN can be evaluated from the spectrum efficiency, the impact of PUs’ activity on control channel, and the overhead of control information exchange. Intuitively, the overhead of control information exchange is related to the impact of PUs’ activity on control channel. The less impact of PUs’ activity on control channel is, the more optimized overhead of control information exchange is. Furthermore, the transmission with optimized overhead can efficiently and reliably transmit control information so that more available channels can be successfully accessed by SUs. Therefore, the spectrum efficiency can be improved. 1) Spectrum efficiency The most advantage of in-band control channel scheme is the improvement of spectrum efficiency due to no required dedicated spectrum resource compared with the out-of-band scheme. If there is loss for control information packets during transmission, the transmission will fail due to either the channel access collision or the failed communication. Therefore, the probability of correct control information exchange Pe shall be considered. As mentioned in problem formulation in Sect. 2, the spectrum

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efficiency can be deduced as below: C

C

⎡ C ⎤ ∑ E [ X i ] ∑ Pe X i ⎥ i =1 E [η ] = E ⎢ ∑ (5) = = n =1 = Pe ⎢ i =1 ⎥ C C ⎣ C ⎦ where Pe denotes that a generic SU correctly exchange control information according to the definition above. Therefore, E[Xi] can be counted as E[Xi]= Pe + 0×(1 − Pe)= Pe. Pe will be discussed later. 2) Impact of PUs’ activity on control channel PUs’ activity can be modeled based on the two-state Markov model, in which 0 denotes that PU is inactive, and 1 represents that PU is active. Pλμ is the transition probability from state λ to state μ. P01 and P10 can be derived from property of PU [19]. Therefore, the steady state probability of active PU Pp can be calculated as follow: P01 (6) Pp = P10 +P01 3) Overhead of control information exchange In order to optimize the overhead of control information exchange, which is related with PUs’ activity, NC technology is employed in proposed in-band NC-CSS scheme. According to Sect. 2, the E(o), the average number of time periods required for successful exchanging control information among all SUs under constraint of the probability Pe, is modeled as the overhead of control information exchange optimized by NC technology as follow [16]: ( M −1) z ⎤ ⎞ ⎛ ⎡ ⎛ ⎞ − − C 1 P 1 ( ) p ⎜ ⎟ E(o) = C ⎜ ∏ ⎢⎢1 − ⎜⎜ C (1 − P ) ⎟⎟ ⎥⎥ ⎟ (7) p ⎜ z =1,2,..., ⎣⎢C ⋅Pp ⋅Pe ⎦⎥ ⎢ ⎝ ⎥⎦ ⎟⎠ ⎠ ⎣ ⎝ From Eq. (6), if Pp gets smaller, which means the PUs are more inactive, the E(o) can be reduced so that the overhead of control information is optimized. Note that E(o) is also related with the probability Pe. 4) The probability of correct control information exchange From analysis above, the performance indicators of proposed in-band NC-CSS scheme include the spectrum efficiency, the impact of PUs’ activity on control channel, and the overhead of control information exchange, which are all related with the probability Pe. The correct control information exchange will happen if all conditions are satisfied as follow: a) The number of available channel for SUs is C(1 − Pp). The two SUs of transmitter and receiver communicate in

(

)

2012

the same channel, so the required number of available channels is ⎢⎣ N 2⎥⎦ at most. If ⎢⎣ N 2 ⎥⎦C (1 − Pp ) , then all available channels will be used for communications, otherwise there are ⎢⎣ N 2⎥⎦ available channels required. Thus, a certain available channel is chosen as with the probability

{min ( ⎢⎣ N 2⎥⎦ , C (1 − P ))} ⎡⎣C (1 − P )⎤⎦ . p

p

b) Both SUs of transmitter and receiver have correctly exchanged the control information with probability Pe. For two SUs, one SU will not receive the control information generated by the other SU with the probability ⎡C (1 − Pp ) − 1⎤ ⎡C (1 − Pp ) ⎤ . Therefore, This happens with ⎣ ⎦ ⎣ ⎦

(

Pe = 1 − ⎡⎣1 C (1 − Pp ) ⎤⎦

).

N −1 2

c) None of M PUs transmits in the same time period, which

happens

with

the

(1 − P )

probability

p

M

=

⎡⎣1 − ( P01 ( P10 +P01 ) )⎤⎦ . Based on analysis above, there are overall C(1 − Pp) available channels, so Pe can be calculated as follows: M

2

N −1 ⎛ ⎤ ⎞ M ⎛⎢N ⎥ ⎞⎜ ⎡ 1 ⎥ ⎟ (1 − Pp ) Pe = min ⎜ ⎢ ⎥ , C (1 − Pp ) ⎟ 1 − ⎢ ⎝⎣ 2 ⎦ ⎠ ⎜⎜ ⎢⎣ C (1 − Pp ) ⎥⎦ ⎟⎟ ⎝ ⎠ (8) Substitute Pe into the Eq. (4) so that the E [η ] of the

proposed in-band NC-CSS scheme can be calculated as follows: ⎛⎢N ⎥ ⎞ E [η ] = Pe = min ⎜ ⎢ ⎥ , C (1 − Pp ) ⎟ ⋅ ⎝⎣ 2 ⎦ ⎠ 2

N −1 ⎛ ⎡ ⎤ ⎞ M 1 ⎜1 − ⎢ ⎥ ⎟ C (1 − Pp ) (9) ⎜⎜ ⎢ C (1 − P ) ⎥ ⎟⎟ p ⎦ ⎝ ⎣ ⎠ Note that the spectrum efficiency is also related with the number of the SUs and channels. Moreover, there is a tradeoff between the number of the SUs and impact of PUs’ activity. If all SUs require transmission and the available channels are enough, i.e. ( N 2 )C (1 − Pp ) ,

(

)

E [η ] can be improved follow with the increased number

of SUs.

5 Numerical simulation results To show the advantages of the proposed in-band NC-CSS scheme, the numerical simulations are shown in

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this section. It is compared with the out-of-band control channel scheme in Ref. [20] and the existing in-band scheme in Ref. [21]. In Ref. [20], a dedicated spectrum band is allocated to SUs as the out-of-band control channel. In Ref. [21], the existing in-band scheme is performed without NC technology, just focusing on the dynamic channel selection scheduling. In simulations, the parameters are set as: the number of PUs M=20; the state transition probability of PUs P01=0.2, P10=0.3 and Pp = P01 ( P10 +P01 ) = 0.4 ; there are overall channels C=30 with the unit bandwidth. There are different numbers of SUs N to analyze the performance. Fig. 3 shows the performance comparison of the spectrum efficiency among the proposed in-band NC-CSS scheme, the out-of-band scheme [20], and existing in-band scheme [21]. It is shown that the two in-band NC-CSS schemes have higher spectrum efficiency compared with the out-of-band one. The spectrum efficiency is improved with increased SUs N. This is due to the fact that the idle channels can be accessed by more SUs. With the number of SUs increases to be larger than the critical number ( M + N ) 2 = C , all channels can be accessed by PUs and SUs, and the spectrum efficiency can be most improved. If ( M + N ) 2 < C , there are always idle channels so that the spectrum efficiency is improved slowly.

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active PU Pp. Due to more active PUs, the idle channel will get less so that it will take more time periods to successfully exchange control information. Furthermore, because there is no channel selection scheduling and NC technology to optimize the overhead for the existing in-band scheme [21], it requires more average time periods E(o) than the in-band NC-CSS scheme. Therefore, the in-band NC-CSS scheme reduces the overhead of control information exchange, and it is more robust to the activity of PUs than the existing in-band scheme.

Overhead performance under impact of active PUs

Fig. 4

Fig. 5 shows the performance of successful control information exchange under the different total numbers of channels. There are SUs N=40. It is shown that the probability of successful control information exchange Pe increases with the increased number of channels (there is the fixed Pp=0.4). The out-of-band scheme [20] has the best performance of successful control information exchange due to the dedicated spectrum allocated as control channel. The in-band NC-CSS scheme has much better performance than the existing scheme [21], which means that the control information exchange can be more reliably performed. Especially, the in-band NC-CSS scheme has the approximately similar performance to the out-of-band scheme when the total

(

)

number of channels increased beyond ( N 2 ) ⎡⎣C 1 − Pp ⎤⎦ , i.e.

( N 2)

⎡C (1 − Pp )⎤ . ⎣ ⎦

Fig. 3 Spectrum efficiency comparison among three control channel schemes

Fig. 4 shows the impact of PUs’ activity on the control information exchange. There are SUs N=40. The activity probability of PUs Pp changes from 0.05 to1 with step 0.05. Because there is the dedicated spectrum as control channel, the out-of-band control channel scheme [20] requires the least time periods in the three schemes, and is hardly influenced by increased Pp. For the two in-band schemes, it can be shown that the required number of time periods for the successful exchanging control information E(o), increases with increased

Fig. 5

Probability of successful control information exchange

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Note that due to the dedicated spectrum allocated as control channel, the out-of-band scheme [20] has the best overhead performance and reliable control information exchange than existing in-band scheme. However, it has the lowest spectrum efficiency. The existing in-band scheme [21] improves the spectrum efficiency, but it has more overhead so that control information exchange is not reliable and efficient. Compared with the above two schemes, the proposed in-band NC-CSS scheme not only has much better spectrum efficiency, but also optimizes the overhead performance so that the reliable and efficient transmission can be guaranteed.

7.

8.

9.

10.

6 Conclusions This study proposes a novel in-band NC-CSS control channel scheme based on time slot division in the distributed CRN, in which the channel selection scheduling algorithm (CSS) is designed to guarantee the dynamic spectrum access by secondary users without any interference to primary users. Furthermore, the overhead of control information transmission is optimized via NC technology. Computer simulations show that the proposed in-band NC-CSS scheme improves spectrum efficiency with efficient and reliable control information transmission, and is adaptive to the dynamic activities of primary users.

11.

12.

13.

14.

Acknowledgements

15.

This work was supported by the National Basic Research Program of China (2009CB320400), the Sino-Finland ICT Collaborations

16.

Programme Project on ‘Future Wireless Access Technologies’ (2010DFB10410), and the National Key Technology R&D Program of China (2010ZX03003-001-01)

17.

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(Editor: WANG Xu-ying)