Optimization Channel Assignment Method for Maximum Throughput under Communication and Positioning Requirements

Transcription

1 Optimization Channel Assignment Method for Maximum Throughput under Communication and Positioning Requirements Ming Li 1, Long Han 1, Weiqiang Kong 2, Shigeaki Tagashira 3, Yutaka Arakawa 2, and Akira Fukuda 2 1 Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan 2 Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan 3 Faculty of Informatics, Kansai University, Osaka, Japan Abstract In this paper, we first discuss a throughput estimate method based on RTS/CTS, and then propose a channel assignment method that could achieve two goals: (a) the maximum throughput of overall network can be guaranteed and (b) terminals can be located in our system. Traditionally, channel assignment is used to mitigate interference for communication. In the area of positioning, to meet the requirement of highly-accurate positioning, wireless Access Points (APs) are always assigned to a single channel. In other words, although mutual interference occurs seriously, channel assignment is not discussed in this area. To the best of our knowledge, we are the first to propose a tradeoff method that gives considerations to communication and location simultaneously. To confirm its effectiveness, we evaluate our approach by simulation. The results illustrate that the throughput of our channel assignment method is higher than other methods. Keywords: channel assignment, communication, positioning, throughput. 1. Introduction based wireless access is a widely used technology in public hot spots such as university campus, airports, coffee bars, and hospitals, etc. A typical development of it in recent years is Wireless LAN (WLAN) of Wi-Fi by which mobile terminals can access wireless networks smoothly through a WLAN Access Point (AP) [1]. However, with the extensive establishment of WLAN environment in public facilities, radio wave interference has become a severe problem. On the other hand, as wireless networks rapidly gained popularity, various services that are based on context-aware of ubiquitous have been changing our daily life. As an essential part of context-aware service, positioning technologies are important for improving convenience of context-aware software. The most well-known positioning system is GPS, which is broadly used in vehicles and mobile phones etc. However, a major problem of conventional GPS is that it cannot achieve a satisfactory accuracy degree for users in indoor environment such as in buildings or underground [2]. Therefore, technologies like ultraviolet, RFID and WLAN are researched and developed for indoor positioning [2][3]. In our research, wireless APs are utilized as positioning devices since rapid development of WLAN provides a platform for positioning through APs. From our point of view, there are two primary reasons of using WLAN in positioning system. 1) WLAN is used initially for communication and Internet access. Since existing infrastructures such as APs can be used for positioning purpose in our system, we do not need to install other special devices or software. 2) WLAN can be used in indoor environment as well as outdoor environment. It would be very convenient if both indoor and outdoor LBS could be invoked by using the same mobile devices. The foremost contribution of our research is that we are the first, to the best of our knowledge, to propose a channel assignment method that provides simultaneously wireless broadband communication service as well as precise positioning service. Based on CSMA/CA with RTS/CTS [11], we propose a throughput estimate method suitable for our research. The objective function of our channel assignment method is to achieve the maximum throughput based on the proposed estimate method. The necessity (or technical obstacles that have to be solved) of channel assignment in our research can be explained in detail as follows. To avoid radio wave interference (that impairs network throughput), it is required that an AP within the interference range of other APs is assigned with a different channel. In addition, to achieve the purpose of positioning, it is required that a mobile terminal could be able to receive radio waves from at least three APs since trilateration or multilateration location method [4] is used in our system for positioning. And thus, adjacent APs must be assigned to the same signal channel. Therefore, channel assignment is one of main work in this research. We extend the description of our work as follows. Section 2 discusses related work. Section 3 introduces background technologies related to this paper. Section 4 defines the problem to be addressed, formalizes the problem, and proposes a channel assignment method that could achieve maximum throughput for overall network. Section 5 evaluates the proposed method and compares with other methods. Section 6 concludes the paper and mentions future work.

2 2. Related Works As based equipments have been vastly utilized, their supporting communication devices have correspondingly developed and become spatially dense. It leads to a severe mutual interference among devices which results in a poor communication throughput. Most related works thus merely target on how to realize maximum throughput for high-speed communication through optimized channel assignments. Different from those works, our research discusses channel assignments by taking both communication performance and positioning into account at the same time. Channel assignment problem can be classified from different point of views. Based on AP management, it can be classified into centrally managed mode and uncoordinated mode. The former is mainly applied in public places such as campus or airports where all APs are managed by a central entity. The latter is often used in residential neighborhoods or private hot spots without a central manager. In both modes, an efficient mechanism for addressing interference issue to improve WLAN performance is needed. Based on centrally managed mode, the work in [5] discusses the problems of channel assignment and AP placement simultaneously, and proposes an approximate solution with Integer Linear Programming (ILP). By adjusting the number of mobile terminals connected to APs, it evaluates network performance such as throughput. The main purpose is to find out optimized (minimized) AP locations from AP candidate points while considering a channel assignment method with a maximized throughput. However, a problem of this work is that the proposed algorithm takes an exponential computation time due to exhaustive searching. Thus, it is considered to be not suitable for large scale networks. In [6], to investigate the fairness issue of channel assignment in resource sharing among mobile terminals, the authors proposed, based on centrally managed mode, a close-to-optimal approach called patching algorithm, which is better than exhausting searching w.r.t. time complexity. Furthermore, the work proposes a probability-based throughput estimation method. However, to evaluate throughput performance, the authors compare the method with other throughput evaluation standard. Due to the difference between calculation methods, it is difficult to illustrate that the method outperforms others. The work in [7] uses centrally managed mode, in which AP placement and channel assignment problems are optimized by mathematical programing. In particular, the objective is to minimize overlapping coverage areas and to maximize network throughput. The authors propose estimated accumulation of overlapping coverage and throughput, respectively. To balance these two aspects, a tradeoff parameter α was introduced into integrated functions. By tuning α, the value of multi-objective functions can be obtained. The mode used in [8] is uncoordinated, in which a distributed, self-configure channel assignment scheme is proposed for uncoordinated WLANs. Core feature of this work is client-assisted, which means that APs are assisted with feedback from clients for gathering adjacent devices traffic information. Since WLAN becomes uncoordinated and independently managed with high AP density, an automatic channel assignment method like the one in [8] becomes important. However, realization of this proposed approach is restricted by hardware development of communication devices. All the above mentioned related works utilize nonoverlapping channels. Another viewpoint for classifying channel assignment problem is based on overlapping channels. The work in [9] uses the b/g standard for channel assignment, in which Interference-factor (I-factor) is introduced to judge whether adjacent nodes are overlapping with each other. I-factor is the signal-to-noise ratio (SNR), which depends on the extent of frequency overlap between adjacent channels. Particularly, in [10], they propose an idea that partially overlapped channels are not always harmful, and they judge the interface according to threshold of SNR, not simply by the color graph theory. 3. Technology Background WLAN can be worked in infrastructure mode or ad-hoc mode, where one of the difference between them lies on how they are connected. In infrastructure mode, APs are connected to each other with wired link to form backbone network (that can be utilized by terminals). In ad-hoc mode, APs interconnect through single/multiple hop wireless links to the backbone. And we consider the former mode in our research. 3.1 Channel Assignment and Data Rate Based on specifications, mainly consist of b/g and a. 1 Because of the limitation of a in outdoor environment, and thus it is not further considered in this paper. The ISM (Industrial, Scientific and Medical) band of b/g contains channels. Inferred from Fig.1, there are only 3 non-overlapping channel in b/g (namely, channel 1, channel 6 and channel 11) [12]. 2 We utilize three non-overlapping channels in this paper. IEEE k was established and completed [13] to transfer and measure information of adjacent APs. According to k, AP channel and neighbor information can be periodically transmitted along with beacon. By this mechanism, APs can clear the channel assignment information of neighborhood. Therefore, k is useful for the development of channel assignment problem. In our 1 Although not considered in this paper, our work is applicable to the newest specification n as well. 2 Actually, b has one more channel channel 14 in japan, but we do not discuss this case.

3 Fig. 1: b/g 2.4GHz Channels. research, channel information can be gathered according to this protocol. According to IEEE802.11b/g standard specification, data rate can be automatically selected by connection quality. IEEE802.11g works in 2.4MHz with a maximum raw data rate of 54Mbps. And the maximum raw date rate of IEEE802.11b is 11Mbps. The data rate is changed according to signal quality and network environment. In this paper, we assume that change of data rate is only related with distance between APs and terminals. In general, transmission range of APs or terminals can be divided into communication range and interference range. If packets are sent/received between APs and terminals, they have to be located in a mutual communication range. Medium contentions occur if APs or terminals are in the mutual interference range. The received sensitivity thresholds of the two ranges are defined by the APs hardware. 3.2 Medium Access Control At present b/g is widely used in WLAN environment. According to communication protocol of Ethernet, mechanism of MAC layer is called CSMA/CA [11]. However, it cannot avoid collision problem such as hidden terminal problem and multiply simultaneous terminal requests. Therefore, the RTS/CTS handshake-based MAC is proposed. In our research, RTS/CTS is involved when discussing Potential Restrainer. As shown in Fig.2, the two terminals (i.e., t 1 and t 2 ) are in the communication range of ap, and they may not know the mutual existence of each other. The general access procedure of RTS/CTS is as follows. 1) Terminal t 1 wants to send data through accessing ap by sending a message RTS (Request To Send). 2) After receiving RTS, ap sends a receipt message CTS (Clear to Send). The CTS can be detected by other communication devices (such as t 2 ) that are in the interference range of ap. And all devices except t 1 and ap must keep silence until the confirmation message ACK (Acknowledgment) is received by ap. Of course t 1 will wait for a period if ap is busy. 3) t 1 then obtains an authorization to send data to ap. On the contrary, t 1 can also receive data from ap. 4) When this data transmission finishes, ap sends ACK to all the other devices in its interference range, informing that they could now send RTS messages. ap becomes idle again and waits the next RTS from terminals such as t 1 or t 2. We can summary the above access procedure as four-way handshakes of RTS-CTS-DATA-ACK. To avoid the situation that t 1 and t 2 send RTS messages simultaneously, ap waits a random time, and the terminal whose RTS is received first can send data. According to the principle, when ap sends CTS, terminals in the interference range of ap can be restrained, hence we analysis four types of Potential Restrainers in subsection 4.2. Fig. 2: CSMA/CA with RTS/CTS. 3.3 Location Method In this subsection, we describe the mechanism of our positioning system and the multilateration positioning method [4] used in this paper. Firstly, in our positioning system, the strength of data frame is observed and used to estimate the distance between APs and terminals. A terminal can communicate with a AP in a period of time. However, the communication (exchange data frame) strength can be observed by other APs which work in the same channel. Considering the principle of multilateration used in our system, we require a terminal must observe three APs at least for positioning. Next, we explain the multilateration by RSSI (Received Signal Strength Indication) for positioning. RSSI can be detected by mobile devices. It is an advantage for us that we estimate accuracy by RSSI of APs, while do not depend on special hardware. It means that the positioning environment is established by existed equipment of WLAN. Y 0 A(xa,ya) B(xb,yb) (a) D(x,y) C(xc,xc) Fig. 3: Triangle and Multilateration Method for Positioning. We can measure the distance between transmitters and receivers by RSSI and calculate coordinate by pythagorean X n 1 (b) 2 4 3

4 theorem. For example, there are three points A(x a, y a ), B(x b, y b ), and C(x c, y c ) which are known, and shown as Fig.3(a). The coordinate of intersection point D(x, y) is unknown. We denote the distance form point D to A,B,C as r a, r b, r c respectively. We can acquire the equations as follows and solve it. (x xa ) 2 + (y y a ) 2 = r a (x xb ) 2 + (y y b ) 2 = r b (x xc ) 2 + (y y c ) 2 = r c However, in real environment, there are not only three transmitters(aps) emitting signals. Hence we have to consider multiple known points such as n which shown as Fig.3(b), and the equations can be described as follows. (x x1 ) 2 + (y y 1 ) 2 = r 1 (x x2 ) 2 + (y y 2 ) 2 = r 2. (x xn ) 2 + (y y n ) 2 = r n Obviously, the coordinate of D is clear if the (x, y) are solved. The equations above cannot be solved directly so easily because it is a non-linear equations. However, we can solve it by Maximum-Likelihood Estimation (MLE). 4. The Proposed Method Based on the technologies mentioned in the previous section, we first propose a throughput estimation method, and then propose an optimized channel assignment method with a maximized overall network (terminals) throughput. Meanwhile, since the best solution must satisfy the requirements of both positioning and communication, we summary some assumptions/preconditions made in this work as follows: (a) To achieve the goal of positioning, every terminal must be able to observe in its interference range three APs of the same channel. (b) To satisfy the requirement of communication, every terminal must be able to connect with a AP for communication that is in its communication range. (c) The APs whose coordinates are known can be placed as a uniform deployment or not in a field beforehand. (d) Every device (AP and terminal) has only one Network Interface Card (NIC) in this work, and thus, the channel of communication AP is the same as the channel of positioning APs. 4.1 Problem Formulation We first define some core concepts the sets AP and T of APs and Terminals, respectively, that are used in the work. The set of APs: AP = {ap i i = 1, 2,..., m}, where each ap i is an AP. The set of Terminals: T = {t j j = 1, 2,..., n}, where each t j is a terminal. Based on the three non-overlapped channels of b/g, we consider that each AP can be assigned with a channel k (k {1, 6, 11}), and thus the set AP is divided into three subsets AP k, where each ap AP k is assigned with channel k. For k, k ( {1, 6, 11}), AP k AP k = Φ and AP k = AP. Since each AP is assumed to have one interface only and thus an AP only works with one channel. In addition, all APs are assigned with a channel k, where k {1, 6, 11}. The distance between an AP ap i and a terminal t j can be calculated by a function D(ap i, t j ). As mentioned in subsection 3.1, every AP or terminal has an interference range and a communication range. We use R and r (R r) to denote the corresponding radius respectively. To judge whether a terminal t j is located in the interference range of ap i, we define the function AT (t j, ap i ) as follows. { 1 if D(api, t AT (t j, ap i ) = j ) R where i {1, 2,..., m}, j {1, 2,..., n}. To check whether an AP ap i is assigned with a channel k, we defined the function AC(k, ap i ) as follows: { 1 if api AP AC(k, ap i ) = k (2) where i {1, 2,..., m}, k {1, 6, 11}. The meaning of function (2) is that if ap i works with channel k, then AC(k, ap i ) = 1. Next, we use S jk to denote the number of APs that are assigned with channel k and are in the interference range of terminal t j. S jk = (1) m AT (t j, ap i ) AC(k, ap i ) (3) i=1 where i {1, 2,..., m}, j {1, 2,..., n}, k {1, 6, 11}. We formulate the two assumptions/preconditions (a) and (b) mentioned in the beginning of this section as follows. Note that we denote them as "Restriction 1" and "Restriction 2" respectively, for illustration simplicity in the algorithm in subsection 4.3. Restriction 1 (on Positioning): The basic condition for positioning is that in the interference range of any terminal t j, there are at least three APs working in the same channel as this terminal. So we describe the assumption as follows. j, k S jk 3. (4) where j {1, 2,..., n}, k {1, 6, 11}. Restriction 2 (on Communication): Every terminal must be able to connect with a AP for communication. To satisfy

5 this, it is required that at least one AP is in the communication range of the terminal, which can be described as follows. i, j D(t i, ap j ) < r (5) where i {1, 2,..., m}, j {1, 2,..., n}. In fact, there may exist multiple APs in the communication range of a terminal. So we define a set AP T j = {ap i D(t j, ap i ) < r}. The element APs of set AP T j are those that can communicate with terminal t j in their communication range. In addition, a set H j, whose element APs are those that must be satisfied for both positioning and communication for terminal t j, is defined as follows: { j H j AP T j H j Φ i ap i H j k AC k (ap i ) S ik 3 For providing wireless broadband, terminals are required to connect their nearest AP which is selected from the AP set that satisfies above formula. The function O(t i, ap j ) is used to define this issue. O(t j, ap i ) = 1 ap i H j ( i (ap i H j i i) D(ap i, t j ) D(ap i, t j )) (6) If ap i is the nearest AP to t j, the value of function O(t i, ap j ) is 1, otherwise it is 0. In brief, one terminal can only be worked in a channel, and this channel must be taken both communication and positioning into account simultaneously. 4.2 Throughput Estimation In our research, we estimate terminal throughput according to data rate and the number of potential restrainers. We assume a WLAN environment without interference and obstacle, and that AP has no delay in switching communication from one terminal to another. We imagine that there are one terminal and one AP merely in an ideal environment. If the terminal is in the area of 54Mbps, we consider that the throughput of this terminal is 54Mbps. On the other hand, if the number of terminals increases, the phenomenon of Medium Access Contention Constraints (MACC) [12] happens obviously. In this paper, we estimate throughput of overall network by considering accumulation of potential restrainers. Therefore, we analyze four types of potential restrainers for an arbitrary terminal t 1 that communicates with AP ap 1. Type1:As shown in Fig.4(a), mobile terminals in the interference range of t 1 are considered as restrainers of type1. If mobile terminals near to t 1 are in its interference area, potential MACC happens directly. The number of potential type1 restrainers is denoted by RST 1, where in Fig.4(a) r 1 and r 2 are such restrainers. Fig. 4: Four Types of Potential Restrainers. Type2:Different from type1, mobile terminals, which are in the interference range of ap 1 that connects with terminal t 1, are considered as restrainers of type2. potential MACC also happen in this case. The number of potential type2 restrainers is denoted by RST 2, where in Fig.4(b) r 3 and r 4 are such restrainers. Type3:As shown in Fig.4(c), mobile terminals, which communicate with those APs that besides ap 1 but also in the interference range of t 1, are considered as restrainers of type3. According to the principle of CSMA/CA with RTS/CTS, MACC occurs between those terminals and t 1. The number of potential type3 restrainers is denoted by RST 3, where r 5 and r 6 are such restrainers. Type4:As shown in Fig.4(d), mobile terminals, which communicate with those APs that are in the interference range of ap 1, are considered as restrainers of type4. Similar to type3, MACC also occurs between those terminals and t 1. The number of potential type4 restrainers is denoted by RST 4, where r 7 and r 8 are such restrainers. Based on these types of potential restrainers, the function of calculating throughput for an arbitrary mobile terminal t T can be defined as follows, where t j t: T H(t) = DR(t) n j=1 RST (t, t j) where { 1 if tj is the potential restrainer of t RST (t, t j ) = (8) DR(t) is the data rate of t which is calculated by the RSSI (Received Signal Strength Indication) received from its connecting AP. In this research, we converse it according (7)

6 to the distance between AP and terminal. For terminal t, the number of all of potential restrainers can be represented by n j=1 RST (t, t j). Function RST (t, t j ) is used to check terminal whether t j is the potential restrainer of t. Therefore, the function of calculating throughput for overall terminals can be defined as: n T H(t j ) (9) j=1 4.3 Channel Assignment Algorithm The objective of the research is to find out the maximum throughput of overall terminals through channel assignment. Pseudo code of the proposed algorithm is described as follows. Channel Assignment Algorithm Initialization: All aps are assigned to channel 1; MAX T H = n j=1 T H(t j); Optimization: Exhaustive search for any possible combinations of aps channels { If (Restriction 1 && Restriction 2) Calculate throughput T H of this channel combination; If (T H > MAX T H ) MAX T H = T H; } Output: The channel assignment when MAX T H ; The value MAX T H. Initially, all aps are assigned to the same channel such as channel 1. The throughput of overall terminals is calculated according to this channel assignment. Then aps channels are changed by exhaustive enumeration. For every possible combination of aps channels, check whether it satisfies both Restriction 1 and Restriction 2. Finally, find out, from all satisfied combinations, the channel assignment method by which a maximum throughput is obtained. 5. Evaluation and Analysis 5.1 Simulation Parameters We calculate the throughput of our proposed method in this section. Since we are the first to propose the channel assignment method by considering both communication and positioning and there are no similar researches, we have to compare it with single methods and random methods. By single methods we mean the methods in which all APs are assigned with the same channel. By random methods we mean the methods in which APs select three isolated channel randomly. As shown in the table 1, we test our simulation in a (m) area. The radiums of communication and radius of interference are set as 11m and 16m, respectively. We test Table 1: The Simulation Parameters Simulation Parameters Value Service area size (m) Number of APs 6 15 Number of terminals 2 24 Channel Set {channel 1, channel 6, channel 11} The Employed Specify b, g Radius of Communication (m) 11 Radius of Interference (m) 16 every case under two specifies of b and g. And only three isolated channels can be used in our paper. 5.2 Scenarios and Analysis We consider two test scenarios for different numbers of APs and terminals, respectively. In the first scenario, we fix the number of APs as 11 such as shown in Fig.5, whereas the number of terminals is changed from 2 to 24. According to the result of simulation shown in Fig.6, status change of throughput are similar for b and g. Take the specify of g as an example, the throughput of our proposal is optimal obviously. As a quantitative analysis, the throughput of our proposed method is about three times higher than single methods and 1.5 times higher than random methods. As the the number of terminals grows, the throughput keeps a stable value in every case. However, the average throughput is calculated and shown in Fig.7. It is clear that as the number of terminals growing, the average throughput per terminal decreases for every case. Nevertheless our proposal is always better than other methods in general. Fig. 5: An Example of AP Deployment. On the other hand, to present an example of channel assignment, we show an assignment pattern according to our proposal when the number of APs is 11 and the number of terminals is 14 such as shown in Fig.5. Based on our assignment, the throughput of overall network is Mbps (802.11b) and 180 Mbps (802.11g), respectively, which is better than other methods. In the second scenario shown in Fig.8, we fixed the number of terminals, and change the number of APs from 6 to 15. As the number of APs increase, the overall throughput of proposed method is higher than others in two specifies respectively. Furthermore, we have to point out that the growth

7 Fig. 6: Overall Throughput of Terminals for Fixed APs. Fig. 7: Average Throughput of Terminals for Fixed APs. rate of our proposal is optimal obviously. In this section, we evaluate our simulation by changing some parameters. The results are clear that our proposal is better than other two methods with respect to network throughput. Fig. 8: Overall Throughput of Terminals for Fixed Terminals. verify its effectiveness, we compare the method with single methods and random methods with respect to throughput by using our proposed estimate method. The results appear that our method is better than others in every case that we tested. In the future, we plan to evaluate the positioning aspect of our proposed method, namely whether positioning could reach the optimal objectives of communication and positioning. Moreover, we will improve the performance of channel assignment method and try to avoid extensive search of all possibilities. References [1] ABI Research, [2] P. Bahl and V.N. Padmanabhan, RADAR: An In-Building RF-based User Location and Tracking System, Proc. IEEE INFOCOM 2000, pp , [3] T. Kitasuka, T. Nakanishi, and A. Fukuda, Wireless LAN based Indoor Positioning System WiPS and Its Simulation, Proc IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM 03), pp , [4] Axel Kupper, Location-Based Services: Fundamentals and Operation, John Wiley & Sons, Ltd, [5] Y. Lee, K. Kim, and Y. Choi, Optimization of AP Placement and Channel assignment in Wireless LANs, Proc. IEEE Conf. Local Computer Networks, pp , [6] X. Ling, and K. L. Yeung, Joint Access Point Placement and Channel assignment for Wireless LANs, IEEE Transactons on Wireless Communications, Vol. 5, No. 10, pp , October [7] A. Eisenblatter, H. F. Geerdes, and I. Siomina, Integrated Access Point Placement and Channel assignment for Wireless LANs in an Indoor Office Environment, Proc. 8th IEEE Intl. Symposium on a World of Wireless, Mobile and Multimedia Networks, pp. 1 10, June [8] Xiaonan Yue, Chi-Fai Michael Wong, and Shueng-Han Gary Chan CACAO: Distributed Client-Assisted Channel assignment Optimization for Uncoordinated WLANs, IEEE Transactions on Parallel and Distributed Systems, Vol. 22, No. 9, pp , September [9] A. Raniwala, and T.C. Chiueh, Architecture and Algorithms for an IEEE Based Multi-channel Wireless Mesh Network, Proc. IEEE INFOCOM 05, pp , [10] A. Mishra, V. Shrivastava, S. Banerjee, and W. Arbaugh, Partially Overlapped Channels not Considered Harmful, Proc. ACM. SIG- METRICS Performance Evaluation Review, Vol. 34, pp , [11] A. Colvin, CSMA with Collision Avoidance, Computer Communication, Vol.6, No.5, pp , [12] IEEE. IEEE Std g T M (amendment to IEEE std ): Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications, [13] S. D. Hermann, M. Emmelmann, O. Belaifa, and A. Wolisz, Investigation of IEEE k-based Access Point Coverage Area and Neighbor Discovery, Proc. 32nd IEEE Conference on Local Computer Networks, pp , October Conclusion In this paper, a throughput estimate method according to the number of potential restrainers is proposed based on CSMA/CA with RTS/CTS. Furthermore, we propose a method for channel assignment, which, to the best of our knowledge, are the first channel assignment method that considers communication and positioning simultaneously. To