An Admission Control Algorithm for Multiuser
OFDMA-based Cognitive Radio Networks
Jerzy Martyna
Faculty of Mathematics and Computer Science Institute of Computer Science, Jagiellonian University
ul. Prof. S. Łojasiewicza 6, 30-348 Cracow, Poland Email; martyna@softlab.ii.uj.edu.pl Abstract—Cognitive radio (CR) has been proposed as a way of
exploiting unused spectrum bands (also called spectrum holes). However, several experiments have indicated that the currently allocated spectrum is underutilized due the static nature of the spectrum assignment. This paper presents an algorithm that allows us to obtain admission control of secondary users (SUs) in a multiuser OFDMA-based CR network implemented in the cellular system. We also analyse the effect of primary unit (PU) and secondary base station (SBS) activities on available resource allocation. Thus, the suboptimal sub-carrier and power allocation scheme with the minimization of the total transmission power keeping the allowed interference to the PUs and SBS are obtained. The simulation results demonstrate that the joint admission control and resource allocation problems are treated in a practical way.
Index Terms—cognitive radio networks, admission control algorithm, spectrum management
I. INTRODUCTION
The so-called cognitive communications, originally used to control radios [1], [2], promise to offer fast and more effective resource utilization by offering intelligent resource assignment. In order to achieve this goal, cognitive communi-cations will rely on information that is to be used by cognitive radio devices and network elements. This is a complex task to accomplish, thus making various learning methods for building these models truly useful.
As shown in Fig. 1, the CR system coexists with the primary system in the same geographic location. A primary system operated in the licensed band has the highest priority to use that frequency band (e.g. 2G/3G cellular, digital TV broadcasts, etc.). Other unlicensed users and/or systems can neither interfere with the primary system in an obtrusive way nor occupy the licensed band. By using the pricing scheme, each of the primary service providers (operators) maximises its profit under the QoS constraint for primary users (PUs). All of the unlicensed secondary users (SUs) are equipped with cognitive radio technologies, usually static or mobile. The primary users (PUs) are responsible for throwing unused frequencies to the secondary users for a fee. While the existing literature has focused on the communications needed for CR system control, this paper assumes a network of secondary base stations (SBSs). Every SBS can only have information on a small number of PUs or channels. It causes interference to PUs and SBSs.
Fig. 1. Downlink/uplink CR network.
The Orthogonal Frequency-Division Multiplexing (OFDM) has been introduced by Saltzberg [3] and Chang [4]. The idea behind it is the division of the broadband band into parallel sub-bands, called sub-carriers, where the high-rate data stream is split into low-rate streams. As the number of sub-carriers increases, the bandwidth of each sub-channel becomes narrower. The OFDM is currently used in digital audio and video broadcasting standards, and in broadband wireless access systems such as IEEE 802.16 (WiMAX), IEEE 802.20 (Mobile Broadband Wireless Access, MBWA). The OFDM system used in the multiuser version is called the Orthogonal Frequency-Division Multiple Access (OFDMA). In all of these systems, the multiple accesses are achieved by allocating a group of sub-carriers to a given user.
The OFDM system has been recommended as a candidate for the CR system due its ability to perform underlying sensing. The ability of the OFDM system to meet CR re-quirements can be studied according to approaches suggested by Mahmond et al. [5], as follows: spectrum sensing, ef-ficient spectrum utilization, interoperability, multiple access and spectral allocation. As explained in [6], the resource allocation technique has the potential to greatly improve power efficiency. To increase spectral efficiency, resource allocation schemes for OFDMA-based CR systems, such as a two-step
resource allocation algorithm in multicarrier based CR system [7] or power/bit loading in OFDM-based CR networks [8], have been proposed. Nevertheless, the traditional resource allocation algorithms for OFDMA systems cannot be directly used for CR systems due to the fact that the number of available sub-carriers varies according to time.
Admission control for the CR network has been used in a number of papers. For example, the optimal admission control of secondary users at cognitive radio hotspots using a semi-Markov decision process to solve maximization problems has been presented by Kim and Shin [9]. A fractional guard channel reservation method has been used by Pacheco-Paramo et al. [10] to control the balance between the blocking rate of arriving users and the dropping rate of ones already admitted. Nevertheless, none of the papers mentioned above analyze the dependencies between interference constraints and transmis-sion power in secondary systems.
The main contribution of this paper to the field is to provide an admission control algorithm devoted to implementation of SBSs in the downlink of multiuser OFDMA-based CR networks. It will allow us to allocate the available system resources optimally. It shows that by using the admission control algorithm, the number of SUs is maximized and the power allocation is optimized. Moreover, the proposed admission control algorithm can be efficiently used to reduce the drop rate of admitted SUs.
The rest of this paper is organized as follows. Section 2 provides the system model and describes the problem formulation. The solution is proposed in Section 3. Section 4 presents the numerical results. Conclusions are drawn in Section 5.
II. SYSTEMMODEL
This paper considers a multiuser downlink OFDMA-based cellular system with an implemented cognitive radio system (see Fig. 1). The accessible bandwidth B by the SU can be utilized as long as it is not actively used by the PU. This bandwidth is divided in the SBS belonging to the CR system into N sub-bands. The received signal at the k-th SU on the n-th carrier is given by
yk,n= hk,nxk,n+ vk,n (1)
where hk,n, xk,n, vk,nare the channel gain, transmitted
sig-nal and the zero means unit variance, i.e. circularly symmetric complex Gaussian noise associated with the kth SU and the nth carrier respectively.
To make the problem tractable, we define pk,n as the
transmission power associated with the n-th carrier and the k-th SU, namely
pk,n≈ βk,n(2rk,n− 1) (2)
where βk,n> 0 is a function of hk,nand the Bit Error Rate
(BER) requirement rk,n is the rate associated with the k-th
SU and the n-th carrier. Additionally, we assume that pk,n is
convex increasing in rk,n as it is necessary in optimization
methods.
In this paper, we assume that all system events such as SU arrival, SU departure, and PU activity changes are synchro-nized. It is achieved by use of a CR system clock.
III. ADMISSIONCONTROLALGORITHM
In this section, we present an admission control algorithm in the CR system. We suppose that the admission control algorithm should optimize the number of SUs in the CR system and minimize the number of SUs being dropped due to a lack of resources. Assuming the cellular structure of the CR network, some channels are reserved in this system to serve call handing over from neighbouring cells. Analogously, new admission requests are dropping from the lack of frequency carriers.
In order to obtain the admission control algorithm, the problem can be mathematically formulated as follows:
minN n=1 K k=1 ρk,npk,n (3) subject to N n=1 ρk,nbk,n≥ Rtark ∀k ∈ KRR (4) E N n=1 K k=1 ρkpk,nSk,n ≤ In (5) K k=1 ρk,n≤ 1 ∀n ∈ Nf ree (6) ρk,n∈ {0, 1} ∀k, n (7) pk,n≥ 0 ∀k, n (8)
whereN free is the set of free carriers, ρk,n is a subcarrier
assignment indicator, indicating whether the n-th subcarrier is assigned to the k-th SU or not, Rtar
k is the target bit rate
required by the k-th SU and the given average interference threshold of the PU, KRR. is the set of the already admitted rate required by SUs plus the newly arriving SUs.
The constraint (5) allows us to allocate the transmission power among SUs over fading channels. The resulting inter-ference Ik,n to the PUs band caused by the nth subcarrier is
given [11] by:
Ik,n= pk,n· Sk,n (9)
where Sk,nis the power spectrum density (PSD) of the fading
process and is defined as
Sk,n=| hspk,n|2 dn+Wp2 dn−Wp2 Ts sin(πf Ts) πf Ts 2 df (10)
Fig. 3. Total transmission power versus the number of SUs for different value ofRtar
k .
dn representing the frequency distance between the n-th
subcarrier and the band of PU.
An algorithm for admission control in the CR system is outlined in Fig. 2. The first procedure, called suboptimal carrier assignment, finds the suboptimal power allocation for the SUs in the CR system. Firstly, in the inner loop one SU at each iteration to determine its suboptimal ρ∗
k,n is selected. procedure suboptimal_carrier_assign; begin Cmax:= 0; n := 1 set ρk,n← Ωk ∀n; obtain pk,nusing pk,n= t ∗ k,n ρk,n where t∗ k,n= K·N1 · Ik,n Sk,n;
{compute rate requirements of all SUs and Ccurr };
for k = 1 to K do begin Rk req = k∈KRR n∈Nfreepk,n · ρk,n · Sk,n; Rk
req< Rtark then n := n + Δn;
compute Ccurr; else Cmax:= Ccurr; end; end; procedure obtain_the_no._of_SUs_with_highest_sum_rate; begin
let d := 1; { the number of SUs } compute| L |= K K − d ;
{L is the set of all SUs combinations }
find| A |;
{A is the set of admissible combination of SUs } if| A |>| L | then suboptimal_carrier_assign; else {| L ≥ A |}
d := d + 1; end;
Fig. 2. The algorithm for admission control in CR network.
Fig. 4. The average SU drop rate versus the SU arrival rate. If the target requirements are satisfied for thek-th SU, the number of sub-bands is increased until the number of SUs or sub-bands are exhausted.
The second procedure tests the all SU combinations that include a single SU for eventual removal. If a single SU removal provides no feasible combinations, all SUs combinations with two users removed are tested until the set of feasible combinations is obtained. In both cases, the number SUs of dropped in this way is established.
IV. SIMULATIONRESULTS
In this section the simulation results of the presented control admission algorithm for the CR system are presented.
The system parameters in our simulation are as follows. All SUs and PUs are distributed uniformly over 1 kms× 1 km. We set some parameters, such as: the PU transmit power equal to 100 mW, the SU transmit power equal to 10 mW for all SUs, and the noise level σ2 = −90 dBm. The target bit rate requirement increases from 0.5
bps/Hz to 2.0 bps/Hz.
Fig. 3 depicts the total transmission in the function of the number of SUs for different values of Rreq. It can be seen that the trans-mission power increases with the value ofRtar
k . It means that the
decrease of Rreq is associated with a smaller total transmission power. Fig. 4 shows the average number of dropped SUs in dependence of the SU arrival rate for two admitted density of SUs (No. of SUs / m2). We see that the admission control algorithm causes a large SU
drop rate for the high density of SUs in the simulated scenario.
V. CONCLUSIONS
In this paper, an algorithm for admission control of SU traffic rate in the multiuser OFDM-based cellular cognitive system was presented. An iterative algorithm is powerful solution for such problems because its iterative and distributed nature allows for many applications such as target rate requirements and eliminating central schedulers, taking them from possible commercial deployment. Due to its high complexity, the suboptimal algorithm was proposed. Nu-merical results showed that the proposed admission control algorithm may be an effective candidate to employ in the CR networks.
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