王董禮 曹鵬 黃國策 孫啟祿 李連寶
摘要:針對短波頻譜利用率低下及頻率選擇不夠智能的局限性,提出一種基于隱馬爾可夫模型(HMM)的短波認(rèn)知頻率選擇方法。應(yīng)用認(rèn)知無線電原理,將短波傳統(tǒng)用戶作為主用戶,將采用認(rèn)知無線電技術(shù)的短波電臺作為認(rèn)知用戶。首先,建立隱馬爾可夫模型,結(jié)合頻譜感知歷史數(shù)據(jù)預(yù)測主用戶信道狀態(tài);其次,在預(yù)測空閑的基礎(chǔ)上估計信道參數(shù);最后,根據(jù)估計的信道參數(shù)選擇最優(yōu)頻率。仿真結(jié)果表明,所提方法能夠準(zhǔn)確預(yù)測傳統(tǒng)短波用戶信道狀態(tài),快速估計信道參數(shù)。在設(shè)定的仿真條件下,所提方法的成功傳輸率分別較HMM預(yù)測和能量感知隨機信道選擇方法有5.54%和10.56%的提升,能夠選擇最優(yōu)信道。
關(guān)鍵詞:短波認(rèn)知通信;隱馬爾可夫模型;信道狀態(tài)預(yù)測;參數(shù)估計;頻率選擇
中圖分類號:TN92 文獻標(biāo)志碼:A
Abstract:Since the limitation of inefficient use and unintelligent frequency selection of the HF (High Frequency) band, a method of HF cognitive frequency selection using Hidden Markov Model (HMM) was proposed. Applying cognitive radio principles to HF communications, HF legacy users were considered as primary users, and the HF radio using cognitive technologies were seen as the secondary user. Firstly, the HMM was established to predict channel states of HF legacy users based on the history data of spectrum sensing; secondly, channel parameters were estimated if the predicted state was idle; finally, the optimal frequency was selected among the channels whose predicted states were idle according to the estimated channel parameters. Simulation results show that the proposed method can be used to actually predict HF legacy users channel states and quickly estimate channel parameters. Under the given simulation conditions, the successful transmission ratio of the proposed method is 5.54% and 10.56% higher than the methods of random channel selection using HMM prediction and energy detection, therefore the proposed method can select the optimal channel.
Key words:High Frequency (HF) cognitive communication; Hidden Markov Model (HMM); channel state prediction; parameter estimation; frequency selection
0 引言
短波具有超視距通信能力,開通架設(shè)方便,一直是重要的遠(yuǎn)程和機動通信手段,用途十分廣泛。由于短波頻段用戶眾多,加上短波信道的時變衰落特性,使得真正可用短波頻率較少,頻譜資源十分緊張。短波工業(yè)協(xié)會(High Frequency Industry Association,HFIA)的研究表明,看似擁擠的短波頻段存在數(shù)量可觀的頻譜空洞[1-2],但是如何感知和選取頻譜空洞,這就要求短波通信系統(tǒng)具有認(rèn)知能力。傳統(tǒng)認(rèn)知無線電的研究主要集中在短波以上頻段,2009年,Koski等[3]從動態(tài)頻譜接入的角度首次提出將認(rèn)知無線電應(yīng)用到短波通信中。在短波中應(yīng)用認(rèn)知無線電技術(shù),能夠提高短波頻譜利用率,減少短波用戶之間非合作式頻率競爭導(dǎo)致的干擾沖突和用頻緊張[4-5]。結(jié)合短波頻段的特殊性,頻率選擇是短波通信的關(guān)鍵,而使用認(rèn)知無線電技術(shù)能夠為短波頻率選擇提供依據(jù),因此,將認(rèn)知無線電技術(shù)應(yīng)用到短波通信中,可以使短波認(rèn)知用戶根據(jù)周圍環(huán)境動態(tài)選擇最佳工作頻率,調(diào)整自身參數(shù)以優(yōu)化通信效果,提高短波通信質(zhì)量。
根據(jù)現(xiàn)有短波頻譜靜態(tài)分配機制和認(rèn)知無線電原理,將3kHz帶寬傳統(tǒng)用戶作為主用戶,主用戶無需采用任何智能策略即可使用授權(quán)頻譜。將采用認(rèn)知無線電技術(shù)的短波電臺作為認(rèn)知用戶,為避免與非合作傳統(tǒng)用戶之間產(chǎn)生相互干擾,短波認(rèn)知用戶必須能夠預(yù)測傳統(tǒng)用戶的信道狀態(tài),從而在傳統(tǒng)用戶信道空閑的情況下接入使用, 因此短波認(rèn)知用戶頻譜接入機會很大程度上依賴于主用戶的信道狀態(tài),而針對其可采用馬爾可夫模型進行描述[6-7]。文獻[8]將傳統(tǒng)短波用戶信道狀態(tài)建模為隱馬爾可夫模型(Hidden Markov Model,HMM),用14MHz頻段實測數(shù)據(jù)驗證該模型的正確性和可靠性,準(zhǔn)確率達95%。文獻[9]在文獻[8]模型的基礎(chǔ)上,用8min的實測結(jié)果對傳統(tǒng)短波用戶信道狀態(tài)進行預(yù)測,平均預(yù)測錯誤率僅為5.8%。但是文獻[9]只對信道狀態(tài)進行預(yù)測,沒有對預(yù)測出的可用信道進行評估,本文在此基礎(chǔ)上提出基于HMM的短波認(rèn)知頻率選擇方法。該方法通過建立HMM,利用頻譜感知歷史數(shù)據(jù)對傳統(tǒng)短波用戶信道狀態(tài)進行預(yù)測,對預(yù)測空閑的信道估計相應(yīng)參數(shù),據(jù)此結(jié)合短波業(yè)務(wù)傳輸需求選擇最優(yōu)頻率。
2.4 頻率選擇
假設(shè)存在多個3kHz傳統(tǒng)短波用戶信道,在每個信道上短波認(rèn)知用戶頻率選擇的流程如圖2所示。首先,使用頻譜感知獲得觀察數(shù)據(jù),對建立的模型進行訓(xùn)練,結(jié)合觀察數(shù)據(jù)和訓(xùn)練后的模型對傳統(tǒng)短波用戶信道狀態(tài)進行預(yù)測;其次,如果預(yù)測的信道狀態(tài)為空閑(即q*T+1=0),則使用訓(xùn)練后反映真實信道情況的HMM參數(shù)λ*=(π*,A*,B*),對預(yù)測結(jié)果為空閑的信道進行參數(shù)c=(μ,θ,rSNR)的估計;最后,在保證短波認(rèn)知用戶業(yè)務(wù)傳輸時間小于預(yù)測空閑信道的平均空閑時間Toff=1/θ的情況下,根據(jù)信噪比rSNR選擇滿足短波業(yè)務(wù)服務(wù)質(zhì)量(Quality of Service,QoS)需求的最佳頻率。
在保證信道狀態(tài)預(yù)測具有較高準(zhǔn)確率的同時,對預(yù)測結(jié)果空閑的信道進行參數(shù)估計。根據(jù)表1參數(shù),通過式(1)、(2)、(7)和模型訓(xùn)練得到的狀態(tài)轉(zhuǎn)移概率矩陣A、觀察概率矩陣B的估計值能夠獲得信道參數(shù)c,因此對c的估計可以轉(zhuǎn)化為對信道狀態(tài)HMM真實參數(shù)的估計。在=0.5,Tinter=22 時,仿真采用的參數(shù)如表2所示,HMM各個參數(shù)收斂過程及最終的估計結(jié)果如圖4、5所示,從圖中可以看出,經(jīng)過22次迭代后,矩陣A和B能夠快速收斂于真實值,因此估計的信道參數(shù)能夠準(zhǔn)確反映主用戶信道狀況,通過信道參數(shù)c,短波認(rèn)知用戶能夠選擇最優(yōu)頻率進行業(yè)務(wù)傳輸。
假設(shè)有3條獨立短波信道,信噪比分別為0dB、-5dB、-10dB,其他參數(shù)如表1。相同條件下,分別對本文方法、HMM預(yù)測隨機信道選擇和能量感知隨機信道選擇方法進行仿真對比,結(jié)果如圖6所示,在時隙T小于1000時,HMM預(yù)測隨機信道選擇Rsuccess略優(yōu)于能量感知隨機信道選擇,HMM預(yù)測最優(yōu)信道選擇Rsuccess最優(yōu)。對頻譜感知歷史數(shù)據(jù)進行學(xué)習(xí)能夠提高成功傳輸率,能量感知隨機信道選擇不具有學(xué)習(xí)功能,HMM預(yù)測隨機信道選擇利用部分學(xué)習(xí)結(jié)果,HMM預(yù)測最優(yōu)信道選擇能夠利用全部學(xué)習(xí)結(jié)果,因而具有較高的成功傳輸率,隨著T增加,HMM預(yù)測最優(yōu)信道選擇的成功傳輸率為85.47%,相較HMM預(yù)測隨機信道選擇有5.54%的提升,較能量感知隨機信道選擇有10.56%的提升。
相同條件下上述3條信道,Rsuccess中選擇0dB信道的比率越高,方法性能越好,采用Roptimal表示不同方法0dB信道的選擇比率。仿真結(jié)果如圖7所示,由于0dB信道并非任意時隙處于空閑狀態(tài),因此該信道并非任意時隙都被選擇,HMM預(yù)測最優(yōu)信道選擇方法的Roptimal隨著時隙T增加穩(wěn)定于68.01%,低于圖6中的成功傳輸率,與理論分析一致,HMM 預(yù)測隨機信道選擇和能量感知隨機信道選擇的Roptimal穩(wěn)定于26.21%,約為相應(yīng)成功傳輸率的1/3, 因此,在相同條件下,本文方法能夠在預(yù)測信道空閑基礎(chǔ)上,優(yōu)先選擇信噪比最高的信道,提高短波通信質(zhì)量。
4 結(jié)語
頻率選擇是提高短波通信質(zhì)量的關(guān)鍵。本文提出一種基于HMM的短波認(rèn)知頻率選擇方法,該方法建立HMM,利用統(tǒng)計學(xué)習(xí)方法對頻譜感知歷史數(shù)據(jù)進行學(xué)習(xí),在保證具有較高預(yù)測準(zhǔn)確率的同時,能夠精確估計信道參數(shù)選擇最優(yōu)頻率,較HMM預(yù)測隨機信道選擇和能量感知隨機信道選擇方法具有更好的性能。由于短波的超視距傳輸特性,在發(fā)射端通過認(rèn)知技術(shù)選擇的可用頻率,在接收端未必可用,因此將認(rèn)知無線電應(yīng)用到短波通信中,需要結(jié)合頻率探測,才能夠使短波認(rèn)知用戶選擇最佳通信頻率,是下一步的研究重點。
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