First IEEE International Conference on Communications in China: Wireless Communication Systems (WCS)
Interference-Aware Channel Allocation for Device-to-Device Communication Underlaying Cellular Networks Yanfang Xu, Rui Yin, Tao Han, Guanding Yu Department of Information Science and Electronic Engineering Zhejiang Provincial Key Laboratory of Information Network Technology, Zhejiang University, Hangzhou 310027, P.R. China Email:
[email protected]
Abstract—Device-to-Device (D2D) communication underlaying cellular networks will become an important technology in future networks such as IMT-Advanced to improve spectral efficiency. In order to enhance the overall system performance, the mutual interference between cellular and D2D communication caused by reusing the spectrum should be properly coordinated and channel allocation is considered as one of the methods to coordinate the interference. In this paper, the problem of channel allocation in a single cell system with several D2D pairs wanting to communicate directly is modeled. Then, an optimal interferenceaware channel allocation scheme based on Hungarian algorithm is proposed. The scheme aims to maximize the number of permitted D2D communication pairs in a system meanwhile avoiding the strong interference from D2D communication to the cellular communication. Besides, we also propose a heuristic algorithm to reduce the computational complexity. Simulation results show that the proposed methods enhance the number of permitted D2D communication pairs significantly and the heuristic algorithm has a performance similar to that of the optimal algorithm which is based on Hungarian algorithm.
I. I NTRODUCTION In recent years, with the development of different kinds of multimedia services, there is an ever increasing demand for higher data rate transmission and higher spectral efficiency. For this reason, Device-to-Device (D2D) communication [1]–[3], which allows devices to communicate directly by sharing the resources with the cellular network, has received increasing attentions as a promising technology to improve spectral efficiency. It provides several advantages, such as improved spectral efficiency, reduced power consumption, increased system throughput, decreased base station (BS) load [1]–[6]. Interference management in a cellular network with D2D communication is a critical issue. The easiest way to coordinate the interference between cellular and D2D communication is to assign dedicated channels for D2D users, which will not cause mutual interference between D2D users and cellular users. However, dedicated channels for D2D communication will lead to inefficient use of the available channels. While reusing the cellular user’s channel will improve the spectral efficiency [4], [5]. Since D2D communication is controlled by BS [3], the interference between cellular communication and
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D2D communication can be coordinated by the BS with proper power control and resource allocation. In [7], the authors proposed a resource allocation scheme for generating local awareness of the interference between the cellular and D2D terminals at the base station, which exploited the multi-user diversity inherent in the cellular network to minimize the interference. In [8], the authors proposed two mechanisms to avoid the harmful inter-system interference in a hybrid system of cellular and D2D mode. One was mitigating the interference from cellular transmission to D2D communication by an interference tracing approach and the other one was reducing the interference from D2D transmission to cellular communication by a tolerable interference broadcasting approach. However, the resource for D2D communication was selected by each D2D pair individually. In [9], the authors proposed a mechanism of sharing uplink spectrum with a cellular network meanwhile avoiding the harmful interference from cellular communication to D2D transmission, which was realized by tracking the near-far interference and identifying the interfering cellular users. In [4], a novel resource allocation method that one D2D pair can reuse the resource of more than one cellular user was proposed. The interference management schemes proposed in the references mentioned above all focused on the resource allocation and power control criterion for only one individual D2D pair, in other words, the authors only considered the interference between cellular and D2D users. However, regarding to the real LTE-A system, when there are a certain number of D2D pairs existing in one cell and each D2D pair may reuse one channel with a cellular user, how should the interference be coordinated? Because in this case, not only the interference between cellular and D2D users should be coordinated but also the interference between D2D pairs should be managed. If BS just simply applies the interference management schemes proposed in the references, not all of the D2D pairs can be permitted to communicate since several D2D pairs may scramble for the channels with high performance. Hence, it presents another challenge in channel allocation in order to maximize the number of permitted D2D communication pairs.
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In this paper, we assume that one cellular channel can only be reused by one D2D pair and propose an interference-aware channel allocation scheme which maximizes the number of permitted D2D communication pairs in a system. We first assume all the D2D pairs should be permitted to communicate and formulate this problem to get a channel allocation solution. Then we conduct an admission control process to reject the D2D pairs which cause strong interference to the cellular communication. And finally, we propose a heuristic algorithm. The priority of cellular communication is guaranteed in the proposed methods by regarding the cellular users as primary users. Moreover, the methods cause minimal disruption to the cellular communication operation since no measurements by the cellular terminals are required. Numerical results show that the proposed methods improve the number of permitted D2D communication pairs significantly and the heuristic algorithm has a performance similar to that of the optimal algorithm which is based on Hungarian algorithm. The rest of this paper is organized as follows. Section II describes the system model. Section III studies the channel allocation problem and proposes an optimal algorithm and a heuristic algorithm. Section IV presents the numerical results and section V concludes the paper. II. S YSTEM MODEL We study the resource sharing between two types of communication, traditional cellular communication between base station and cellular user, and direct D2D communication between two devices. The system model includes a single cell environment illustrated in Fig. 1, where 𝑀 uplink cellular users and 𝐾 D2D pairs share the 𝑁 available uplink channels under the control of BS. Here, 𝑀 uplink cellular users are denoted as 𝑈𝐸1 , 𝑈𝐸2 , ⋅ ⋅ ⋅ , 𝑈𝐸𝑚 , ⋅ ⋅ ⋅ , 𝑈𝐸𝑀 . The 𝐾 D2D pairs are denoted as 𝐷2𝐷1 , 𝐷2𝐷2 , ⋅ ⋅ ⋅ , 𝐷2𝐷𝑘 , ⋅ ⋅ ⋅ , 𝐷2𝐷𝐾 . And each D2D pair is comprised of one transmitter 𝑆𝑘 and one receiver 𝑅𝑘 . In this system, the cellular users have already been allocated channels and are communicating with BS before D2D pairs send access request to BS. We assume that the BS can acquire information of channel gain between itself and all the terminals connected with it in the cell, such as 𝐻𝑚 (the channel gain between BS and 𝑈𝐸𝑚 ), 𝐻𝑆𝑘 (the channel gain between BS and 𝑆𝑘 ). 𝑅𝑘 can acquire information of channel gain between itself and its transmitter 𝑆𝑘 , and it will feed back this information to BS through control channel. We also assume that each uplink cellular user and each D2D pair can be allocated one channel at most. Besides, one channel cannot be reused by more than one D2D pair. 𝐷2𝐷𝑘 sends a direct D2D communication request to BS through control channel. At the same time, 𝑆𝑘 sends pilots to its receiver 𝑅𝑘 . Then 𝑅𝑘 feeds back the received information, such as its channel situation 𝐻𝐷𝑘 , noise 𝑁0 and the interference 𝐴𝑚,𝑘 , to the BS. Based on this acquired information and the predefined interference threshold, BS allocates channels to D2D pairs, and tells 𝑆𝑘 its transmission power. In this system, the cellular users are regarded as primary users and thus the priority of cellular communication is
BS
Communication link Interference link
Ik,m
UEm
Sk Am,k D2Dk Rk
Fig. 1: System Model
guaranteed. Based on this assumption, there are three different cases with different values of 𝐾, 𝑀, 𝑁 : ∙ 𝑁 ≥ 𝑀 +𝐾. In this case, each of D2D pairs and cellular users will use dedicated channels since there is enough channel resource, and they cause no interference to each other. Hence, the channels can be randomly allocated to cellular users and D2D users. ∙ 𝑀 < 𝑁 < 𝑀 +𝐾. In this case, some D2D pairs will use dedicated channels whereas others have to reuse channels with cellular users. One of the challenges in this case is that some D2D pairs are chosen to use dedicate channels, which will not cause interference for cellular user, while others must reuse cellular link which will produce mutual interference. For those D2D pairs reusing cellular link, we should appropriately determine which cellular link is reused for each D2D pair. ∙ 𝑁 ≤ 𝑀 . In this case, D2D pairs have to reuse the channels with cellular users and we should appropriately determine which cellular link is reused for each D2D pair. In this paper, we focus on the second case and consider the uplink channel reusing. Since from the above analysis, we conclude that the channel allocation for the first case is quite easy and the method proposed for the second case in this paper can be easily extended to the third case. III. P ROPOSED INTERFERENCE - AWARE CHANNEL ALLOCATION SCHEME
A. Problem Formulation and Optimal Solution Firstly, let us consider the process of how the 𝑘−𝑡ℎ D2D pair reuses the 𝑚−𝑡ℎ cellular user’s channel. As illustrated in Fig. 1, during the process of D2D link setting up, 𝑅𝑘 senses the interference from cellular transmission to D2D communication
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𝐴𝑚,𝑘 . In order to enable D2D communication, the received 𝑆𝐼𝑁𝑅𝑘 should satisfy: 𝑃𝑆𝑘 𝐻𝐷𝑘 ≥ 𝑇0 𝑆𝐼𝑁𝑅𝑘 = 𝑁0 + 𝐴𝑚,𝑘
𝑇0 (𝑁0 + 𝐴𝑚,𝑘 ) 𝐻𝐷𝑘
(2)
However, the D2D pair that reuses the cellular user’s channel will cause interference to BS since BS is the receiver of the uplink cellular communication. The interference from D2D transmission to uplink cellular communication is: 𝐼𝑘,𝑚 = 𝑃𝑆𝑘 𝐻𝑆𝑘
(3)
Where 𝐻𝑆𝑘 is the channel gain between 𝑆𝑘 and BS. In order to guarantee the priority of cellular communication, if the interference caused by D2D transmission is larger than a predefined interference threshold, the D2D transmission is not permitted. Here, we use an admission control index 𝜃𝑘,𝑚 , which values 0 or 1, to indicate whether 𝐷2𝐷𝑘 is admitted to reuse the channel of 𝑈𝐸𝑚 . Let 𝐼0 be the predefined interference threshold for BS. If 𝐼𝑘,𝑚 ≤ 𝐼0 , the interference from the 𝑘−𝑡ℎ D2D communication to the 𝑚−𝑡ℎ uplink cellular communication is smaller than the threshold, we define 𝜃𝑘,𝑚 = 1, which means the 𝑘−𝑡ℎ D2D pair is admitted to reuse the 𝑚−𝑡ℎ cellular user’s channel. Else if 𝐼𝑘,𝑚 > 𝐼0 , the 𝑘−𝑡ℎ D2D pair is refused to reuse the 𝑚−𝑡ℎ cellular user’s channel, and we set 𝐼𝑘,𝑚 to be a very large constant 𝐶1 which is larger than 𝑁 × 𝐼0 for further calculation and define 𝜃𝑘,𝑚 = 0. If 𝐷2𝐷𝑘 is allocated a dedicated channel, we may regard it that 𝐷2𝐷𝑘 is reusing the channel with a virtual cellular user 𝑁0 , 𝑈𝐸𝑚 , 𝑀 < 𝑚 ≤ 𝑁 . In this case, 𝐴𝑚,𝑘 = 0, 𝑃𝑆𝑘 = 𝑇𝐻0𝐷𝑘 and 𝐼𝑘,𝑚 = 0. Thus, we obtain a 𝐾 × 𝑁 interference matrix I = [𝐼𝑘,𝑚 ] and a 𝐾 × 𝑁 admission control matrix 𝜽 = [𝜃𝑘,𝑚 ]. Now, let us consider the problem of channel allocation for D2D pairs in the system. We hope to get a channel allocation scheme that permits all the D2D pairs to communicate. We find that the D2D pair causing lower interference to the cellular link is more likely to be permitted. Hence, we assume that all the D2D pairs can be permitted to communicate and then our objective is to minimize the sum interference from D2D communication to the cellular system. In the above paragraphs, we have set 𝐼𝑘,𝑚 whose value is larger than 𝐼0 to be a very large constant 𝐶1 . Hence, in order to minimize the sum interference, the system will avoid choosing those reusing ways that cause strong interference to the cellular communication. Thus, the problem is formulated as
𝐾 ∑ 𝑁 ∑ 𝑘=1 ⎧ 𝑚=1
(1)
Where 𝑃𝑆𝑘 is the transmission power of 𝑆𝑘 , 𝐻𝐷𝑘 is the channel gain between 𝑅𝑘 and 𝑆𝑘 , 𝑁0 is the noise received by 𝑅𝑘 and 𝑇0 is the predefined 𝑆𝐼𝑁𝑅 threshold of 𝐷2𝐷𝑘 . Based on this information, BS calculates the minimal transmission power for 𝑆𝑘 : 𝑃𝑆𝑘 =
min
s.t.
𝐶1 : ⎨𝐶2 : ⎩𝐶3 :
𝜌𝑘,𝑚 𝐼𝑘,𝑚 𝜌𝑘,𝑚 ∈ {0, 1} , ∀𝑘, 𝑚; 𝑁 ∑ 𝜌𝑘,𝑚 = 1, ∀𝑘;
(4)
𝑚=1 𝐾 ∑
𝜌𝑘,𝑚 ≤ 1, ∀𝑚;
𝑘=1
where, 𝜌𝑘,𝑚 is the potential channel allocation variable, which is a 0-1 variable. If 𝜌𝑘,𝑚 = 1 and 1 ≤ 𝑚 ≤ 𝑀 , it means the 𝑘−𝑡ℎ D2D pair has a probability to be allocated the 𝑚−𝑡ℎ cellular user’s channel. Notice that here we use the words "has a probability to be allocated" rather than "is allocated", and the reason will be explained later in this subsection. If 𝜌𝑘,𝑚 = 1 and 𝑀 + 1 ≤ 𝑚 ≤ 𝑁 , it means the 𝑘−𝑡ℎ D2D pair is allocated a dedicated channel. Otherwise, 𝜌𝑘,𝑚 = 0. The objective is to minimize the sum interference from D2D transmission to the cellular system. Equality 𝐶2 means that each D2D pair has one channel to use. Inequality 𝐶3 means that one channel cannot be assigned to more than one D2D pair. Problem (4) is a simple 0-1 integer programming problem. In fact, since all of the 𝐼𝑘,𝑚 are already known, it is an assignment problem and can be solved by Hungarian algorithm. However, not all of the D2D pairs can be permitted to communicate in all cases. For example, there are 4 D2D pairs and 3 free channels in a cell, and all of the interference from the D2D communication to the cellular communication is larger than the threshold. In this case, each D2D pair has to use a dedicated channel, which means one of the four D2D pairs cannot be permitted to communicate. However, with the above problem (4), we get four 𝜌𝑘,𝑚 whose value is 1. Hence we still need to conduct an admission control process to get the final solution of channel allocation. Here, a 𝐾 × 𝑁 matrix x = [𝑥𝑘,𝑚 ] is used to denote the final solution of channel allocation. 𝑥𝑘,𝑚 is the channel allocation variable, which is a 0-1 variable. If 𝑥𝑘,𝑚 = 1 and 1 ≤ 𝑚 ≤ 𝑀 , it means the 𝑘−𝑡ℎ D2D pair is allocated the 𝑚−𝑡ℎ cellular user’s channel. If 𝑥𝑘,𝑚 = 1 and 𝑀 + 1 ≤ 𝑚 ≤ 𝑁 , it means the 𝑘−𝑡ℎ D2D pair is allocated a dedicated channel. In the above, we have mentioned the admission control index 𝜃𝑘,𝑚 which indicates whether 𝐷2𝐷𝑘 is admitted to reuse the channel of 𝑈𝐸𝑚 . Hence, if 𝜌𝑘,𝑚 = 1 and 𝜃𝑘,𝑚 = 1, the 𝑘−𝑡ℎ D2D pair is permitted to reuse the 𝑚−𝑡ℎ cellular user’s channel. In other words, we can obtain the final solution of channel allocation by taking 𝜌𝑘,𝑚 and 𝜃𝑘,𝑚 into 𝑥𝑘,𝑚 = 𝜌𝑘,𝑚 𝜃𝑘,𝑚 . Notice that 𝑥𝑘,𝑚 is the channel allocation variable which indicates the final solution of channel allocation, while 𝜌𝑘,𝑚 is the potential channel allocation variable which is a intermediate variable of channel allocation without conducting the admission control process. The complete procedure of the proposed interference-aware channel allocation scheme can be illustrated as follows:
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1) BS calculates the interference 𝐼𝑘,𝑚 from each D2D transmission to each cellular communication. If 𝐼𝑘,𝑚 ≤ 𝐼0 , it sets the admission control index 𝜃𝑘,𝑚 = 1. Else if 𝐼𝑘,𝑚 > 𝐼0 , it sets 𝜃𝑘,𝑚 = 0 and 𝐼𝑘,𝑚 to be a very large constant 𝐶1 . 2) Assuming all the D2D pairs can be permitted to communicate, the problem is formulated as (4). Solve the Problem (4) to obtain the potential channel allocation solution 𝝆 = [𝜌𝑘,𝑚 ] by using Hungarian algorithm. 3) The final channel allocation solution x = [𝑥𝑘,𝑚 ] can be obtained by conducting the admission control process by taking 𝜌𝑘,𝑚 and 𝜃𝑘,𝑚 into 𝑥𝑘,𝑚 = 𝜌𝑘,𝑚 𝜃𝑘,𝑚 . B. Heuristic Algorithm We can obtain the optimal solution of channel allocation by the algorithm described above. However, the computational complexity of the which is based on Hungarian ) ( algorithm, algorithm, is 𝑂 𝑁 2 𝑙𝑜𝑔𝑁 . Hence, we propose a lower computational complexity heuristic algorithm. The proposed heuristic algorithm also follows the rule that the D2D pair causing lower interference to the cellular link is more likely to be permitted. Since there are 𝑁 − 𝑀 available dedicated channels and the D2D pairs that are allocated these dedicated channels will not cause any interference to cellular communication, so the 𝑁 − 𝑀 free channels definitely will be allocated to D2D pairs. Hence, we only need to determine which 𝐾 + 𝑀 − 𝑁 D2D pairs should be allocated to reuse which cellular user’s channel. Whereas the remaining 𝑁 − 𝑀 D2D pairs will be allocated dedicated channels. In order to maximize the number of permitted D2D communication pairs, a practical method is to let the D2D pair which causes strong interference be allocated a dedicated channel whereas the D2D pair which causes weak interference be allocated a reused channel. Hence, we search for the minimal interference in the 𝐾 × 𝑀 interference matrix and mark the corresponding D2D pair and cellular user as 𝑘 ∗ ,𝑚∗ . If 𝐼𝑘∗𝑚∗ ≤ 𝐼0 , then the 𝑘 ∗−𝑡ℎ D2D pair is allocated the 𝑚∗−𝑡ℎ cellular user’s channel. Next, we search for the minimal interference in the interference matrix which is composed by the remaining D2D pairs that haven’t been allocated channels and the cellular users whose channels haven’t been reused. Then we mark the corresponding D2D pair and cellular user and allocate the channel if 𝑚𝑖𝑛 (𝐼𝑘,𝑚 ) ≤ 𝐼0 . Repeat this step for 𝐾 + 𝑀 − 𝑁 times. In other words, repeat this step until the number of remaining D2D pairs that haven’t been allocated channels is 𝑁 −𝑀 . During this process, if 𝑚𝑖𝑛 (𝐼𝑘,𝑚 ) > 𝐼0 , which means there is no D2D pairs can be admitted to reuse cellular user’s channel, we should stop allocating reused channels. Then, we allocate dedicated channels to the remaining D2D pairs until there are no dedicated channels. The proposed heuristic algorithm consists of three steps as shown in Algorithm 1. In the first step, all sets and variables are initialized. In the second step, the reused channels are allocated. Cellular user’s channel is allocated to the D2D pair which minimizes the interference. If 𝑚𝑖𝑛 (𝐼𝑘,𝑚 ) > 𝐼0 for 𝑘 ∈ K, 𝑚 ∈ M or the number of D2D pairs that haven’t been
Algorithm 1 Proposed heuristic algorithm Step 1: initialization Set K = {1, 2, ⋅ ⋅ ⋅ , 𝐾}; M = {1, 2, ⋅ ⋅ ⋅ , 𝑀 }; Ns = {𝑀 + 1, 𝑀 + 2, ⋅ ⋅ ⋅ , 𝑁 }; 𝑥𝑘,𝑚 = 0, ∀𝑘 ∈ K, 𝑚 ∈ M ∪ Ns Step 2: allocating reused channels while ∣K∣ > ∣Ns ∣ and 𝑚𝑖𝑛 (𝐼𝑘,𝑚 ) < 𝐼0 for 𝑘 ∈ K, 𝑚 ∈ M do ⌊ ∗ ∗ (𝑘 , 𝑚 ) = 𝑎𝑟𝑔 𝑚𝑖𝑛 (𝐼𝑘,𝑚 ) , ∀𝑘 ∈ K, 𝑚 ∈ M 𝑘,𝑚
let 𝑥𝑘∗𝑚∗ = 1, M = M ∖ {𝑚∗ } , K = K ∖ {𝑘 ∗ } Step 3: allocating dedicated channels set 𝑚∗ = 𝑀 + 1 while Ns ∕= Ø do ⌊ ∀𝑘 ∗ ∈ K, let 𝑥𝑘∗𝑚∗ = 1, Ns = Ns ∖{𝑚∗}, K = K ∖{𝑘 ∗ } , 𝑚∗ = 𝑚∗ + 1.
allocated a channel is 𝑁 − 𝑀 , then stop allocating the reused channels. In the third step, each of the dedicated channels is allocated to the D2D pairs. The computational ) complexity of ( the proposed heuristic algorithm is 𝑂 𝐾 2 𝑀 and it reduces the computational complexity significantly compared with the the optimal algorithm especially when the number of D2D pairs is far less than that of available channels, i.e. 𝑁 ≫ 𝐾. IV. S IMULATION RESULTS In this section, we compare the performance of the proposed heuristic algorithm, the optimal algorithm, the random algorithm which allocates channel resource randomly to D2D pairs. We consider a system of a single cell with a radius of 500m. There are altogether one BS, 20 uplink cellular users, 5 D2D pairs, and 23 available uplink channels in the system. Cellular users are distributed uniformly over the system area. One user of the D2D pair is distributed uniformly over the system area whereas the other user is distributed uniformly upon a disk centered by the first D2D user. And the radius of the disk which gives the maximum distance between D2D pairs is given as a simulation parameter. The other simulation parameters are set up according to [10], [11] and are given in TABLE I. TABLE I: Main Simulation Parameters parameter Cell radius Path loss model for cellular link Path loss model for D2D link Shadow fading standard deviation Noise spectral density System bandwidth SINR threshold for D2D receiver Simulation times
value 500m 128.1+37.6log10(d[km]) 148 + 40log10(d[km]) 10 dB for cellular mode links and 12 dB for D2D mode links -174 dBm/Hz 10MHz -10 dB 100000
Fig. 2 shows the number of permitted D2D communication pairs versus the interference threshold of BS. It shows that
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Fig. 2: Number of permitted D2D communication pairs versus the interference threshold of BS
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Fig. 4: Number of permitted D2D communication pairs versus the maximum distance between D2D pairs
average interference caused by each D2D transmission (dBm)
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Fig. 3: The average interference caused by each D2D transmission versus the interference threshold of BS
for all the algorithms, the number of permitted D2D communication pairs increases with the increase of the interference threshold. It also shows that the proposed heuristic algorithm achieves almost the same performance as the optimal algorithm. We can see from the figure that the performance improvement of the heuristic algorithm over the random algorithm is significant, especially when the interference threshold is lower than -120dBm where the gap of the number between the two algorithms is larger than 1. Since we set the objective as minimizing the sum interference from D2D communication to the cellular system when formulating the problem and allocate reused channel firstly to the D2D pair whose interference is minimal in the heuristic algorithm, the schemes we proposed bring an additional benefit that the interference from D2D transmission to the cellular
communication is reduced to some extent. Hence, we also evaluate the performance of interference. Fig. 3 shows the average interference caused by each D2D transmission versus the interference threshold of BS. Here the average interference caused by each D2D transmission is defined as the ratio of the sum interference from D2D communication to the cellular system divided by the number of permitted D2D communication pairs. It shows that the average interference increases with the increase of the interference threshold. The reason is that the accepted interference caused by D2D communication will increase as the interference threshold of BS increases. Fig. 3 shows that the average interference caused by each D2D communication of the proposed heuristic algorithm is about 1~2dBm higher than the optimal algorithm. It also shows that the performance improvement of the proposed heuristic algorithm and the optimal algorithm over the random algorithm is significant. From the figure we can see that all of the average interference of the proposed heuristic algorithm and the optimal algorithm is significantly lower than the interference threshold. For example, when the interference threshold is -120dBm, the average interference of the proposed heuristic algorithm is -134.5dBm, whereas that of the optimal algorithm is -136dBm. Fig. 4 shows the number of permitted D2D communication pairs versus the maximum distance between D2D pairs when the threshold of BS is -140dBm. It shows that for all the algorithms, the number of permitted D2D communication pairs decreases with the increase of the maximum distance between D2D pairs. This is because with smaller distance between D2D users, the D2D link becomes stronger and is likely to produce less interference to cellular communication and therefore much more likely to be permitted to communicate. It also shows that the performance improvement of the proposed heuristic algorithm and optimal algorithm is significant. Compared with the random algorithm, the proposed heuristic algorithm and
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average interference caused by each D2D transmission (dBm)
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which is based on Hungarian algorithm, a heuristic algorithm is proposed. Simulation results show that the performance improvement of our methods over the random algorithm is significant.
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ACKNOWLEDGMENT
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This work was supported in part by the National Science and Technology Major Project of China (No. 2012ZX03003013005), the Zhejiang Provincial Natural Science Foundation of China (No. Y1110368), the National Natural Science Foundation of China (No.61001098).
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0.06 0.08 0.1 0.12 0.14 0.16 maximum distance between D2D pairs(km)
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0.2
Fig. 5: The average interference caused by each D2D transmission versus the maximum distance between D2D pairs
the optimal algorithm can permit much more D2D pairs to communicate. Fig. 5 shows the average interference caused by each D2D transmission versus the maximum distance between D2D pairs when the threshold of BS is -140dBm. It shows that the average interference caused by each D2D communication of the proposed heuristic algorithm is only about 1dB higher than the optimal algorithm. Fig. 5 also shows that for all the algorithms, the average interference caused by each D2D communication increases at first and then decreases with the increase of the maximum distance between D2D pairs. This is because with smaller distance between D2D users, the D2D link becomes stronger and is likely to communicate with lower transmit power and therefore produces less interference to cellular communication. But when the maximum distance is larger than 50m, the D2D link becomes weaker and is likely to communicate with higher transmit power and therefore produces more interference to cellular communication. Hence, some D2D pairs may be refused to access the network since the interference they cause is larger than the threshold. Thus, the rejection of these higher interference produced by D2D pairs leads to lower average interference. V. C ONCLUSION An interference-aware channel allocation scheme for D2D communication underlaying cellular networks is proposed in this paper. The scheme we proposed regards the cellular users as primary users and thus guarantees the priority of cellular communication. Moreover, it causes minimal disruption to the cellular communication operation since no measurements by the cellular terminals are required. Our scheme maximizes the number of permitted D2D communication pairs in a system meanwhile avoiding the strong interference from D2D communication to the cellular communication. Due to the high computational complexity of the optimal algorithm
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