1231721 玫、發_分日曰 1 一、發明所屬之技術領域】 本發明係關於無線诵％ i通成網路之技術領域，尤指一 種於無線通訊網路中以趟φ ^ 赵今 T以機率密度函數推估行動台個 數之方法。 【一、先前技術】 近年來由於無線通訊迅 , 、逐發展，無線通訊網路已 遂漸普及，人們不止期待盔绐 …、線通訊網路提供多樣化且 不同服務品質，更期待1狳福％如 …、、、泉通訊網路能迅速提供服 然而’當無線通訊網路中許多行動台欲鏈結至該 ·.、、線通訊網路要求服務時’該行動台需先登錄至-位 於該無線通訊網路中的基地台’而該基地台同一時槽 内只允許一行動台登錄，當同一時槽有許多行動台^ 進行登錄時，各行動台利用一上行鏈結傳送欲登錄之 資料至該基地台，由於各行動台所傳送之訊號間互相 干擾、重璺等因素，該基地台接收到一些難以辨識的 訊號，因此，該基地台利用一下行鏈結傳送一碰撞訊 號至各行動台’而各行動台需再進行一隨機程序（例 如：Controlled Slotted-Aloha， CS-Aloha)以決定 下一時槽是否進行登錄，若下一時槽欲登錄之行動台 個數亦不為1而再次產生碰撞時，則必須番族 /只至攸上述程 序，由於該基地台無法正確地估測欲昝铋 _ 且环 < 仃動台個 數’當有許行動台欲登錄時會反覆進行該隨機程序， 將使得無線通訊網路之效率不彰，而右早〜 乃J M iSC進之必 要0 6 1231721 發明人爰因於此，本於積極發明之精神，亟思一 種可以解決上述問題之「於無線通訊網路中以機率密 度函數推估行動台個數之方法」，幾經研究實驗終至 完成此項發明。 【三、發明内容】 本發明之主要目的係在提供一種可於無線通訊 網路中以機率密度函數推估行動台個數之方法，俾能 正確推估同時要求登入該無線通訊網路之行動台個 數。 依據本發明之一特色，係提出一種由於無線通訊 網路中以機率密度函數推估行動台個數之方法，該無 線通訊網路包含至少一基地台，其中，該基地台分別 預存有1至N個行動台同時要求登入該無線通訊網路 所造成的各式混合訊號之機率密度函數的分佈曲 線，該方法包括下述步驟：（A )計算該基地台所接 收到實際訊號之波封；（B )求取該波封之機率密度 函數的分佈曲線；（C )將該波封之機率密度函數的 分佈曲與該預存之機率密度函數的分佈曲線進行適 配比對處理，以推估目前同時要求登入該無線通訊網 路之行動台個數。 由於本發明構造新穎，能提供產業上利用，且確 有增進功效，故依法申請發明專利。 【四、實施方式】 71231721 Rose, hair _ minute day 1 1. The technical field to which the invention belongs] The present invention relates to the technical field of wireless communication, especially to a network in a wireless communication network. Method for estimating the number of mobile stations by density function. [I. Prior Technology] In recent years, due to the rapid development of wireless communication, wireless communication networks have gradually become popular. People not only look forward to helmets ..., wire communication networks provide diversified and different service quality, but also look forward to 1%. … ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,-,,-,-,-,-,,-,,-,,-,,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-, Base station 'and only one mobile station is allowed to log in to the base station at the same time slot. When there are many mobile stations in the same slot at the same time, each mobile station uses an uplink link to send the data to be registered to the base station. Due to factors such as mutual interference and repetition of signals transmitted by various mobile stations, the base station received some unrecognizable signals. Therefore, the base station used a link to send a collision signal to each mobile station 'and each operation The station needs to perform another random procedure (for example: Controlled Slotted-Aloha, CS-Aloha) to determine whether to log in at the next time slot. When the number of mobile stations is not 1 and a collision occurs again, you must use the above-mentioned procedures. Because the base station cannot correctly estimate the desired bismuth, and the < Some mobile stations will repeatedly perform this random procedure when they want to log in, which will make the wireless communication network inefficient, and right early ~ is necessary for the advancement of JM iSC. 0 6 1231721 Because of this, the spirit of active invention I am thinking about a method to estimate the number of mobile stations in a wireless communication network using a probability density function, which can solve the above problem. After several research experiments, this invention has been completed. [III. Summary of the Invention] The main purpose of the present invention is to provide a method for estimating the number of mobile stations using a probability density function in a wireless communication network, and to correctly estimate the number of mobile stations that require simultaneous login to the wireless communication network. number. According to a feature of the present invention, a method for estimating the number of mobile stations based on a probability density function in a wireless communication network is proposed. The wireless communication network includes at least one base station, and each of the base stations pre-stores 1 to N base stations. The mobile station also requests the distribution curve of the probability density function of various mixed signals caused by logging into the wireless communication network. The method includes the following steps: (A) calculating the envelope of the actual signal received by the base station; (B) seeking Take the distribution curve of the probability density function of the wave seal; (C) Match the distribution curve of the probability density function of the wave seal with the distribution curve of the pre-stored probability density function to estimate the current simultaneous request for login The number of mobile stations in the wireless communication network. Since the present invention has a novel structure, can provide industrial use, and has indeed improved efficacy, it has applied for an invention patent in accordance with the law. [Four, implementation] 7
4M-H 1231721 為使貴審查委員能進一步瞭解本發明之結構、 特徵及其目的，茲附以較佳具體實施例之詳細說明如 后： 有關本發明之於無線通訊網路中以機率密度函 數推估仃動台個數之方法的較佳實施例，請先參照第 1圖所示之實施本發明之方法的系統架構圖，該無線 通訊網路包含至少一基地台10，其中，該基地台1〇 分別預存有1至N個行動台丨丨同時要求登入該無線通 訊網路之機率密度函數的分佈曲線，本發明之實施例 的N值為5，當該i個、2個、…或5個行動台同時要求 登入該無線通訊網路時，該基地台丨〇依據預存之機率 密度函數的分佈曲線之比對處理，以推估目前同時要 求豆入XJ亥無線通訊網路之行動台個數。 第2圖所不係本發明之於無線通訊網路中以機率 密度函數推估行動台個數之方法的實施示意圖，其係 在該基地台10之内，以一波封/相位偵測產生器2〇、 一分佈圖產生器30、一最佳比對器4〇及一資料庫5〇 所實現，該波封/相位偵測產生器2〇係將該基地台丄〇 所接收到之訊號轉換產生一對應之正規化波封/相 位，該分佈圖產生器30將該正規化之波封/相位轉換 成一分佈圖，該資料庫5〇預存1至5個行動台同時要求 登入该無線通訊網路時之機率密度函數的分佈曲 線，該最佳比對器4 0比對該資料庫5 〇預存的分佈曲線 與該波封/相位轉換分佈圖，以推估目前同時要求登 入該無線通訊網路之行動台個數。 κ 1231721 則述1至5個行動台同時要求登入該無線通訊網 路時之機率密度函數的分佈曲線可在離線求得，並預 存於負料庫5 0 ’如假設傳輸通道為附加白高斯雜訊 (Additive White Gaussian Noise，AWGN)通道，則 基地台所接收訊號R(t)在AWGN通道中係表示為： 盆 ’ ， （1 ) 八中’ Z為同時要求登入該無線通訊網路之行動台個 數 &為弟i個行動台在該基地台1〇處之功率平方 根’/〃為載波頻率，决仍為第i個行動台調變後之波形， 為平均值為〇、變異數為％之高斯雜訊。為方便 °兒明’假設各行動台之功率均相同，亦即A = s，令 吖U為#㈠之實數部分，故該 之特徵函數為： /ν(0 = e~{cxy,1) = J0L(St)e~{ay/2) /=1 , (2) 其中，Λ、4為第一類零階及第L類零階貝索函數 (Bessel function of the first kind and L kind 〇f order zero) ，為該接收訊號吖〇之波封函 數，故其機率密度函數為： 、"4M-H 1231721 In order to allow your reviewers to further understand the structure, characteristics and purpose of the present invention, detailed descriptions of the preferred embodiments are attached as follows: The invention is based on the probability density function in wireless communication networks. For a preferred embodiment of the method for estimating the number of mobile stations, please first refer to the system architecture diagram of the method for implementing the present invention shown in FIG. 1. The wireless communication network includes at least one base station 10, wherein the base station 1 〇 There are 1 to N mobile stations preliminarily stored. 丨 丨 The distribution curve of the probability density function required to log in to the wireless communication network at the same time. In the embodiment of the present invention, the N value is 5, when the i, 2, ..., or 5 When the mobile station requests to log in to the wireless communication network at the same time, the base station will process the comparison based on the distribution curve of the pre-stored probability density function to estimate the number of mobile stations that currently require simultaneous access to the XJHAI wireless communication network. Figure 2 is not a schematic diagram of the method of estimating the number of mobile stations in the wireless communication network by using the probability density function in the present invention. It is within the base station 10 and uses a wave seal / phase detection generator. 20. A profile generator 30, an optimal comparator 40, and a database 50 are implemented. The waveband / phase detection generator 20 is a signal received by the base station 〇. The conversion generates a corresponding normalized envelope / phase. The profile generator 30 converts the normalized envelope / phase into a profile. The database 50 prestores 1 to 5 mobile stations and requests to log in to the wireless communication network at the same time. The distribution curve of the probability density function at the time of the road. The optimal comparator 40 compares the pre-stored distribution curve with the database 50 and the wave seal / phase shift distribution map to estimate the current simultaneous request to log in to the wireless communication network. The number of mobile stations. κ 1231721 The distribution curve of the probability density function when 1 to 5 mobile stations are required to log in to the wireless communication network at the same time can be obtained offline and pre-stored in the negative material storehouse 5 0 'If it is assumed that the transmission channel is additional white Gaussian noise (Additive White Gaussian Noise, AWGN) channel, then the signal R (t) received by the base station in the AWGN channel is expressed as: "Pan '," (1) Eight in the middle "Z is the number of mobile stations that require simultaneous access to the wireless communication network & is the square root of the power of the i mobile station at 10 of the base station '/ 〃 is the carrier frequency, and it is still the waveform after the i mobile station is adjusted, the average value is 0, and the number of variations is%. Gaussian noise. For the sake of convenience, it is assumed that the powers of the mobile stations are the same, that is, A = s, and let U be the real part of # ㈠, so the characteristic function is: / ν (0 = e ~ {cxy, 1) = J0L (St) e ~ {ay / 2) / = 1, (2) where Λ and 4 are Bessel functions of the first kind and L kind. f order zero), which is the sealing function of the received signal, so its probability density function is: "
Py(y) = f ytJ〇{yt)mdt^ ytJ0(yt)j0\st)e-^2^dt9 y>0 (3) 故該波封函數之正規化波封函數之機率密度函數為：Py (y) = f ytJ〇 {yt) mdt ^ ytJ0 (yt) j0 \ st) e- ^ 2 ^ dt9 y > 0 (3) Therefore, the probability density function of the normalized envelope function of the envelope function is:
Px(xH.A + \)x[te 1 2 ’ （4) 其中，心&=眞、L為目前同時要求登入之行動台個 數、Λ、4為第一類零階及第[類零階貝索函數，故依 據公式（4 )可離線計算該波封之機率密度，第、 1231721 3B圖即分別在訊號雜訊比（Signabt〇jQisePx (xH.A + \) x [te 1 2 '(4) where heart & = 眞, L is the number of mobile stations currently required to log in at the same time, Λ, 4 are the first type zero order and the first [type The zero-order Besso function, so the probability density of the envelope can be calculated offline according to formula (4). Figures 1231721 and 3B are respectively the signal-to-noise ratio (Signabt〇jQise
Ratio SNR)為l〇dB及20 dB時，1至5個行動台同時要 求登入該無線通訊網路時之正規化波封函數之機率 密度分佈圖，並將該1至5個行動台同時要求登入該無 Λ I汛、’周路時之正規化波封函數之機率密度分佈圖 預存至該資料庫5 〇中。 而右傳輸通道為窄頻多重路徑衰減（narr〇wband multipath fading)通道，則基地台1〇所接收訊號#幻 在窄頻多重路徑衰減通道中係表示為： _ =〜2例(’)小+公/e· } +吨)e^ 1 " J · ( 5) 八中Z為同時要求登入該無線通訊網路之行動台個 數’ &為第i個行動台在該基地台丨〇處之功率平方 根’ ^為載波頻率’辦0為第i個行動台調變後之波形， 為平均值為〇變異數為β之高斯雜訊，S = ， 我=^-4 ’故該接收訊號之相位機率密度分佈函數為： Ρβ^β I ^,) = Je^pWhen the ratio SNR) is 10dB and 20 dB, 1 to 5 mobile stations simultaneously request to log in to the normalized envelope function of the wireless communication network when the probability density distribution map, and the 1 to 5 mobile stations request to log in at the same time The probability density distribution map of the normalized wave-sealing function without Λ I flood and 'peripheral road time' is pre-stored in the database 50. While the right transmission channel is a narrow-band multipath fading channel, the signal received by the base station # 10 in the narrow-band multipath fading channel is expressed as: _ = ~ 2 cases (') small + Public / e ·} + ton) e ^ 1 " J · (5) The eighth Z is the number of mobile stations simultaneously requesting access to the wireless communication network '& is the i-th mobile station at the base station 丨 〇 The square root of the power '^ is the carrier frequency'. 0 is the waveform of the i-th mobile station after modulation. It is the Gaussian noise with an average of 0 and a variation of β. S =, I = ^ -4. The phase probability density distribution function of the signal is: ρβ ^ β I ^,) = Je ^ p
Sxrzo%6 rdr， (6) 其中’相位0值介於—冗及冗之間，系第一類零階 夕 P白貝索函數（zero-th order modified Bessel function 〇f the f irst kind)，以 w取代《，公式 (6 )可改寫為： _Λ/) = ά》ΧΡ；{夸+ ΣΛ，-ν^>—) fl/0(V2A/ +4ΛΛ,· -4A,^co^) rdr. ^ ^ ^ 去除公式（7)中的條件機率，公式（7)可改寫成： —)=f ...f _ 八抓).··ΜΛ 少八丨為， (8) 10 1231721 其中，/7(Λ,·)係接收訊號之訊號雜訊比的機率密度分佈 函數，ρ(θ)為目前同時要求登入之行動台個數及訊號 雜訊比之函數’故依據公式（8 )可離線計算該相位 之機率密度’第4A、4Β圖係分別在訊號雜訊比 (Signal-to - Noise Rati〇, SNR)為 1〇dB&2〇dB時，i 至5個行動台同時要求登入該無線通訊網路時之相位 函數之機率密度分佈圖，並將該1至5個行動台同時要 求登入該無線通訊網路時之相位函數之機率密度分 佈圖預存至該資料庫5 0中。 本發明之於無線通訊網路中以機率密度函數推 估行動台個數的流程圖可見於第5圖，首先，於步驟 S 3 0 1中’該基地台1 〇接收多個行動台同時所傳送要求 登錄之訊號。 若傳輸通道為附加白高斯雜訊通道，則求取該基 地台所接收到訊號之正規化波封機率密度函數的分 佈曲線’於步驟S 3 0 2中，該波封/相位偵測產生器2 〇 係將該基地台1 0所接收到之訊號轉換產生一相關之 波封，並產生一正規化之波封，於步驟s 3 〇 3中，該分 佈圖產生器3 0將該正規化波封轉換成一分佈圖。 於步驟S 3 0 4中，該最佳比對器4 〇比對該資料庫5 〇 預存的分佈曲線與該波封轉換分佈圖，以推估目前同 時要求登入該無線通訊網路之行動台個數上。 若傳輸通道為窄頻多重路徑衰減通道，則求取該 基地台所接收到訊號之相位機率密度函數的分佈曲 線，於步驟S 3 0 2中，該波封/相位偵測產生器2 〇係將 該基地台1 0所接收到之訊號轉換產生一相關之相 11 4M4 1231721 位，於步驟S 3 Ο 3中，該分佈圖產生器3 0將該相關之相 位轉換成一分佈圖。 於步驟S 3 0 4中，該最佳比對器4 0比對該資料庫5 0 預存的分佈曲線與該相位轉換分佈圖，以推估目前同 時要求登入該無線通訊網路之行動台個數i。 於步驟S 3 0 4中，該最佳比對器4 0所使用之比對方 法可為最小平方法、權重最小平方法、最大概似法或 Maximum a Posteriori法中之任何一種。 由上述說明可知，本發明之無線通訊網路中以機 率密度函數推估行動台個數之技術由於預存之機率 密度函數分佈曲線而能估測1至5個行動台同時要求 登入該無線通訊網路之行動台個數。 綜上所陳，本發明無論就目的、手段及功效，在 在均顯示其週異於習知技術之特徵，為無線通訊網路 行動台個數推估之設計上的一大突破，懇請 貴審 查委員明察，早曰賜准專利，俾嘉惠社會，實感德便。 惟應注意的是，上述諸多實施例僅係為了便於說明而 舉例而已，本發明所主張之權利範圍自應以申請專利 範圍所述為準，而非僅限於上述實施例。 1231721 【五、圖式簡單說明】 第1圖係一無線通訊網路使用示意圖。 第2圖所示係本發明之於無線通訊網路中以機率密度 函數推估行動台個數之方法的實施示意圖。 第3A、3B圖係本發明分別於SNR=10dB及SNR = 20dB時1 至5個行動台同時要求登入該無線通訊網路時之正規 化波封函數之機率密度分佈圖。 第4A、4B圖係本發明分別於SNR=10dB及SNR = 20dB時1 至5個行動台同時要求登入該無線通訊網路時之相位 函數之機率密度分佈圖。 第5圖係本發明推估方法之流程圖。 【圖號說明】 基地台 10 行動台 11 波封/相位偵測產生器 20 分佈圖產生器 30 最佳比對器 40 資料庫 50Sxrzo% 6 rdr, (6) where 'phase 0 value is between-redundant and redundant, is the first zero-th order modified Bessel function 〇f the f irst kind, Replace w with ", the formula (6) can be rewritten as: _Λ /) = ά》 ΧΡ; {+ + ΣΛ, -ν ^ > —) fl / 0 (V2A / + 4ΛΛ, · -4A, ^ co ^) rdr. ^ ^ ^ Remove the conditional probability in formula (7), formula (7) can be rewritten as: —) = f ... f _ eight grabs). ·· ΜΛ less eight 丨 as, (8) 10 1231721 where / 7 (Λ, ·) is the probability density distribution function of the signal-to-noise ratio of the received signal, and ρ (θ) is a function of the number of mobile stations and the signal-to-noise ratio that are currently required to log in at the same time. The probability density of the phase can be calculated offline. The 4A and 4B graphs are required when i to 5 mobile stations simultaneously when the signal-to-noise ratio (SNR) is 10dB & 20dB. The probability density distribution map of the phase function when logging in to the wireless communication network, and the 1 to 5 mobile stations simultaneously request the probability density distribution map of the phase function when logging in to the wireless communication network are pre-stored in the database 50. The flowchart of the present invention for estimating the number of mobile stations using a probability density function in a wireless communication network can be seen in Fig. 5. First, in step S301, the base station 10 receives multiple mobile stations and transmits them simultaneously. Sign-up required. If the transmission channel is an additional white Gaussian noise channel, obtain the distribution curve of the normalized waveband probability density function of the signal received by the base station. In step S302, the waveband / phase detection generator 2 〇 Converts the signal received by the base station 10 to generate a relevant envelope and generates a normalized envelope. In step s 3 03, the profile generator 3 0 converts the normalized wave The seal is converted into a distribution map. In step S304, the optimal comparator 400 compares the pre-stored distribution curve of the database 50 with the envelope conversion distribution map to estimate the number of mobile stations currently requesting access to the wireless communication network at the same time. Count on. If the transmission channel is a narrow-band multi-path attenuation channel, the distribution curve of the phase probability density function of the signal received by the base station is obtained. In step S302, the envelope / phase detection generator 2 will The signal conversion received by the base station 10 generates a correlated phase 11 4M4 1231721 bits. In step S 3 0 3, the profile generator 30 transforms the correlated phase into a profile. In step S 304, the optimal comparator 40 compares the pre-stored distribution curve of the database 50 with the phase shift distribution map to estimate the number of mobile stations currently required to log in to the wireless communication network at the same time. i. In step S304, the comparison method used by the best comparator 40 may be any one of the least square method, the weighted least square method, the most approximate method, or the Maximum a Posteriori method. As can be seen from the above description, the technology for estimating the number of mobile stations based on the probability density function in the wireless communication network of the present invention can estimate 1 to 5 mobile stations requesting to log in to the wireless communication network simultaneously due to the pre-stored probability density function distribution curve. Number of mobile stations. In summary, the present invention, regardless of its purpose, means, and effect, shows its characteristics that are different from the conventional technology, and it is a breakthrough in the design of wireless communication network mobile station estimation. The members clearly observed that they would grant a quasi-patent as early as possible. However, it should be noted that the above-mentioned embodiments are merely examples for the convenience of description. The scope of the claimed rights of the present invention should be based on the scope of the patent application, rather than being limited to the above-mentioned embodiments. 1231721 [Fifth, a simple description of the diagram] Figure 1 is a schematic diagram of the use of a wireless communication network. Fig. 2 is a schematic diagram showing the implementation of the method for estimating the number of mobile stations in the wireless communication network by using a probability density function. Figures 3A and 3B are the probability density distribution diagrams of the normalized envelope function when one to five mobile stations simultaneously request to log in to the wireless communication network when the SNR = 10dB and SNR = 20dB, respectively. Figures 4A and 4B are probability density distribution diagrams of the phase function of the present invention when 1 to 5 mobile stations simultaneously request to log in to the wireless communication network when the SNR = 10dB and SNR = 20dB, respectively. FIG. 5 is a flowchart of the estimation method of the present invention. [Illustration of drawing number] Base station 10 Mobile station 11 Wave seal / phase detection generator 20 Distribution map generator 30 Best comparator 40 Database 50