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車路通信環(huán)境下TD?LTE無線資源調(diào)度建模與仿真

2014-07-09 17:34白國柱趙祥模徐志剛陳婷
現(xiàn)代電子技術 2014年13期

白國柱+趙祥模+徐志剛+陳婷

摘 要: 為了改善現(xiàn)有車路通信方式覆蓋范圍小、交付時延大和傳輸速率低的現(xiàn)狀,將TD?LTE技術引入車路通信接入系統(tǒng)。提出了基于TD?LTE的車路通信接入系統(tǒng)無線資源調(diào)度模型;構建了車路通信仿真場景,對比例公平算法、指數(shù)比例公平算法和改進的最大權重時延優(yōu)先算法進行性能分析。仿真結果表明:車輛低速移動場景下,系統(tǒng)負載較低時指數(shù)比例公平算法性能較好,系統(tǒng)負載較高時改進的最大權重時延優(yōu)先算法表現(xiàn)更優(yōu),比例公平算法不適合車路通信多媒體業(yè)務流調(diào)度;車輛高速移動場景下,三者都不適合車路通信多媒體業(yè)務流調(diào)度。

關鍵詞: 車路通信; 時分長期演進; 無線資源調(diào)度; QoS保證; LTE?Sim仿真

中圖分類號: TN911.7?34; TP393.1 文獻標識碼: A 文章編號: 1004?373X(2014)13?0001?05

Research on resource scheduling algorithm in V2I communication

access system based on TD?LTE

BAI Guo?zhu, ZHAO Xiang?mo, XU Zhi?gang, CHEN Ting

(College of Information Engineering, Changan University, Xian 710064, China)

Abstract: To improve the existing V2I communication mode with small?scale coverage, long delivery latency and low transmission rate, TD?LTE technology was introduced into V2I communication access system. A radio resource scheduling model based on TD?LTE is proposed for V2I communication access system. Three typical resource scheduling algorithms of PF, EXP and M?LWDF were tested and contrasted in different vehicle mobile simulation scenarios. Simulation results show that in slow moving scenario, when the system load is low, EXP algorithm can provide better performance; M?LWDF algorithm can perform better as load is enhenced; PF algorithm is not suitable for multi?media resource scheduling. In high moving scenario, all the three algorithms are not suitable.

Keywords: V2I communication; time division long term evolution; radio resource scheduling; QoS guarantee; LTE?Sim simulation

0 引 言

車路通信接入系統(tǒng)作為智能交通重要子系統(tǒng)之一,是保障交通參與者之間通信渠道順暢,針對道路行車實現(xiàn)安全預警、高效引導,為乘客提供專業(yè)多媒體與移動互聯(lián)網(wǎng)應用服務的關鍵,在車聯(lián)網(wǎng)中扮演重要角色。

近幾年來,歐美、日本等發(fā)達國家將大量人力物力投入到基于車路通信系統(tǒng)的下一代智能交通(Intelligent Transport System,ITS)的相關研發(fā)中[1?3]。然而,已有車路通信系統(tǒng)大多采用IEEE 802.11技術或2.5G/3G移動通信網(wǎng)絡技術[4?5]。這些通信方式基站覆蓋范圍有限,車載設備需頻繁切換路側設備,網(wǎng)絡帶寬不支持高質(zhì)量數(shù)據(jù)并行實時傳輸,無法為多媒體信息服務提供高品質(zhì)保障[6]。隨著移動通信技術發(fā)展,LTE技術應運而生,許多學者和研究機構嘗試將LTE技術引入到車路協(xié)同通信網(wǎng)絡中[7]。在車路通信環(huán)境下,業(yè)務類型的多樣性及服務需求的差異性對車路通信接入系統(tǒng)的QoS(Quality of Service)控制提出了更高的要求。但是,LTE技術在車路通信領域應用正處于起步階段,鮮有針對車路通信接入系統(tǒng)無線資源調(diào)度性能仿真和適用性驗證的文獻。

針對這種情況,將最新的4G TD?LTE移動通信技術應用到車路通信接入系統(tǒng),提出了一種基于TD?LTE技術的車路通信接入系統(tǒng)無線資源調(diào)度模型,對車路通信環(huán)境中無線資源調(diào)度算法進行對比分析,給出車路通信環(huán)境下合適的TD?LTE無線資源調(diào)度算法。

1 無線資源調(diào)度模型

相比第三代移動通信技術[8],正交頻分復用技術(Orthogonal Frequency Division Multiplexing, OFDM)、多天線技術和自適應調(diào)制編碼技術(Adaptive Modulation and Coding, AMC)的應用使TD?LTE技術可以靈活分配時頻域上的無線資源,保證下行100 Mb/s、上行50 Mb/s的標準峰值速率和100 km半徑的長距離小區(qū)覆蓋?;谝陨咸匦?,建立了一種基于TD?LTE的車路通信接入系統(tǒng)資源調(diào)度模型,如圖1所示。

圖1 TD?LTE車路通信接入系統(tǒng)資源調(diào)度模型

模型將TD?LTE作為車路通信接入系統(tǒng)主干網(wǎng)絡通信方式,為車輛提供無線接入服務。TD?LTE基站(Evolved Node B,eNodeB)負責整個系統(tǒng)多用戶多業(yè)務調(diào)度。eNodeB在媒體訪問控制層(Media Access Control,MAC)對每一個接入系統(tǒng)中的用戶設備(User Equipment,UE)根據(jù)UE傳輸業(yè)務流度量[m]的大小進行分配。如式(1)所示:

[mj,k=maxi{mi,k}] (1)

式中:[mj,k]為第[j]個用戶在第[k]個無線資源塊(Resource Block, RB)的度量,若[mj,k]最大,就將第[k]個RB分配給第[j]個UE。

TD?LTE無線資源調(diào)度器與資源管理模塊交互過程分為以下步驟:

(1) UE計算信道質(zhì)量指標(Channel Quality Indicator,CQI),并將其反饋給eNodeB。

(2) eNodeB依據(jù)CQI為該UE指定資源分配策略,并填充RB的分配掩碼。

(3)自適應調(diào)制編碼模塊(Adaptive Modulation Coding,AMC)為UE選擇最優(yōu)調(diào)制編碼策略(Modulation and Coding Scheme, MCS)進行數(shù)據(jù)編碼。

(4) eNodeB將與UE相關的信息如分配的RB、選擇的MCS等通過物理下行控制信道(Physical Downlink Control Channel,PDCCH)發(fā)送給UE。

(5) UE獲取PDCCH上的信息后,在物理下行共享信道(Physical Downlink Share Channel, PDSCH)獲得無線資源,開始數(shù)據(jù)傳輸,完成整個資源調(diào)度過程。

2 無線資源調(diào)度算法分析

2.1 問題描述

在TD?LTE車路通信接入系統(tǒng)應用中,車輛數(shù)量集中、相對位置不斷變化,造成無線電波的多普勒效應、多徑效應,致使無線信道質(zhì)量不穩(wěn)定;車路通信接入系統(tǒng)中安全預警類信息服務極為重要,傳輸時延要求在100 ms以內(nèi);車輛行駛過程中多媒體應用信息服務對帶寬和傳輸速度要求較大。因此,無線資源調(diào)度算法性能好壞直接關系整個車路通信接入系統(tǒng)傳輸性能高低。

現(xiàn)有TD?LTE無線資源調(diào)度算法根據(jù)能否感知信道質(zhì)量和能否支持QoS保證,劃分為信道無感知調(diào)度策略、信道感知/QoS無保證調(diào)度策略、信道感知/QoS保證調(diào)度策略三類[9]。

由于行業(yè)應用的特殊性,TD?LTE車路通信接入系統(tǒng)無線資源調(diào)度算法應確保交通參與者所獲各種ITS信息服務始終滿足響應的QoS要求,特別是與行車安全密切相關的信息能夠得到及時準確的遞交。調(diào)度算法應該在服務業(yè)務分布不均、信道質(zhì)量起伏變化的情況下,靈活分配和動態(tài)調(diào)整TD?LTE車路通信網(wǎng)絡可用的無線資源。

2.2 算法分析

針對上述問題,研究了比例公平算法(Proportional Fair Scheduler,PF)、指數(shù)比例公平算法(Exponential PF,EXP)和改進的最大權重時延優(yōu)先算法(Modified Largest Weighted Delay First,M?LWDF)在TD?LTE車路通信接入系統(tǒng)中無線資源調(diào)度的性能。其中,PF算法屬于信道感知/QoS無保證策略。EXP和M?LWDF算法專門為TD?LTE系統(tǒng)下行多媒體信息流調(diào)度而開發(fā),計算復雜度低;在資源調(diào)度過程中,能夠保證最低系統(tǒng)吞吐量和一定的公平性[10?11]。通過三者性能比較,給出一種合適的解決方案,支持QoS保證的多媒體信息流資源調(diào)度。

2.2.1 PF算法

PF算法根據(jù)用戶設備信道質(zhì)量和UE歷史吞吐量進行無線資源分配[12],使網(wǎng)絡在達到最大吞吐量的同時保證資源分配公平。PF調(diào)度算法度量通過公式(2)計算:

[mPFi,k=dik(t)Ri(t-1)] (2)

式中:[mPFi,k]為調(diào)度度量;[dik(t)]表示第[t]個TTI中第[i]個UE在第[k]個RB上獲得的期望吞吐量;[Ri(t-1)]為截止到[t]時刻第[i]個UE獲得的歷史平均吞吐量。[Ri(t-1)]通過遞歸式(3)得出:

[Ri(t)=βRi(t-1)+(1-β)ri(t)] (3)

式中:[ri(t)]為第[i]個UE在時刻[t]獲得的數(shù)據(jù)傳輸速率;[0≤β≤1]。

PF算法考慮了用戶在每一個信道的信道情況,即每一個UE的瞬時信道速率和前一段時間的平均信道速率。上一時刻UE分配了資源,那么UE的平均信道速率得到提高,下一個時刻UE被分配資源的機率減小,達到比例公平目的。

2.2.2 EXP算法

EXP算法將指數(shù)規(guī)則應用到無線資源分組調(diào)度過程,在這種調(diào)度算法下實時信息流隊頭時延很接近時延閾值。當實時業(yè)務交付時延接近目標時延閾值時,該算法確保它比非實時業(yè)務具備更高服務優(yōu)先權[11]。EXP實時業(yè)務流度量[mEXPi,k]由式(4)和式(5)定義:

[mEXPi,k=expαiDHOL,i-χ1+χdik(t)Ri(t-1)] (4)

[χ=1Nrti=1NrtαiDHOL,i] (5)

式中:[DHOL,i]是隊頭時延可接受的最大值;[Nrt]為下行實時活躍信息流的數(shù)目;[αi]為調(diào)節(jié)權值,由式(6)可得:

[αi=-logδiτi] (6)

式中:[τi]為第[i]個用戶的時延閾值;[δi]為隊頭數(shù)據(jù)包時延[DHOL,i]超過時延閾值的最大概率。

在EXP實時流調(diào)度算法中,一旦實時業(yè)務流的分組在目標時延期限內(nèi)沒有被分配RB,那么這個分組將從MAC層隊列中刪除,減少帶寬浪費。對于非實時流,EXP算法退化為簡單的PF算法。

2.2.3 M?LWDF算法

M?LWDF調(diào)度算法支持多用戶不同QoS需求[11],給出了分組交付時延上界,支持對QoS有不同要求的多重數(shù)據(jù)用戶。度量[mM-LWDFi,k]定義如式(7):

[mM-LWDFi,k=αiDHOL,i.(dik(t))[Ri(t-1)]] (7)

式中[DHOL,i]和[αi]定義同式(4)相同。

由公式(7)可知,對于實時業(yè)務流[αi]隨著[δi]的增大而減小,保證具有最小隊頭時延要求和最好信道條件的實時業(yè)務流優(yōu)先調(diào)度。對非實時業(yè)務流,M?LWDF使用PF算法進行調(diào)度。與PF算法相比,M?LWDF算法通過累計時延約束無線資源分配,最終在頻譜利用率、公平性和QoS保證之間獲得很好的平衡。

表1給出了PF算法、EXP算法和M?LWDF算法的輸入?yún)?shù),直觀給出了三種調(diào)度算法的差異。

3 仿真場景建模

采用LTE?Sim仿真工具對TD?LTE車路通信接入網(wǎng)絡無線資源調(diào)度性能進行仿真驗證[13]。仿真場景如圖2所示:小區(qū)半徑為1 km,包括1部eNodeB基站和5~40部TD?LTE 車載UE。其中,eNodeB基站位于仿真車道一側的中心位置,車輛移動方式為Way?Point模型[14],速度設定為30 km/h和120 km/h。此外,仿真場景中只有一個eNodeB,不存在相鄰基站的轉(zhuǎn)播干擾問題。

以下行鏈路為例,車路通信過程中,每個UE同時收發(fā)3種業(yè)務流類型:語音流(Voice over Internet Protocol,VoIP)[13]、視頻流(Video)和盡力而為流(the Best Effort Flow,BE)[16]如圖2所示。

圖2 仿真場景

FTP數(shù)據(jù)下載業(yè)務實現(xiàn)BE流;開/閉馬爾可夫模型實現(xiàn)G.729VoIP流;視頻測試序列“highway.yuv”模擬Video流[14]。

仿真使用隨機種子初始化,仿真時間設定為100 s,每次仿真過程至少進行10次,最終結果取平均值。仿真硬件環(huán)境為Linux操作系統(tǒng),2.6 GHz主頻,4 GB內(nèi)存。

eNodeB物理參數(shù)設置見表2。

4 實驗結果與分析

給定目標時延閾值,在不同UE數(shù)量和速度下對上述資源調(diào)度算法進行性能分析。滿足目標時延和一定公平指數(shù)的前提下,丟包率的大小明顯影響實時業(yè)務流的通信質(zhì)量。對于實時業(yè)務流,著重考察丟包率的變化情況,找出支持更低丟包率的調(diào)度算法;非實時業(yè)務流對QoS保證沒有嚴格要求,著重對比系統(tǒng)吞吐量和公平指數(shù)。

圖3和圖4分別給出了Video流和VoIP流在不同UE數(shù)量和不同速度下的丟包率曲線。由圖可知,隨著接入系統(tǒng)UE數(shù)量增加,并發(fā)業(yè)務數(shù)量增大,丟包率上升;同時速度越大,連續(xù)子幀信道變化越頻繁,導致選擇MCS時出錯頻率增加,丟包率增加。相同UE數(shù)量和速度下,VoIP流的分組丟包率要低于Video流,這是因為VoIP流的發(fā)送速率較Video流更低,而且具有更高的優(yōu)先調(diào)度級別。

圖3 Video流丟包率曲線

圖4 VoIP流丟包率曲線

值得注意的是,UE速度為120 km/h時,PF,EXP和M?LWDF算法實時流丟包率基本一致,超出可接受范圍;而UE速度為30 km/h時,三者的丟包率差異顯著,PF算法明顯高于EXP和M?LWDF算法。速度為30 km/h條件下,接入UE數(shù)目較小時,EXP算法和M?LWDF算法丟包率基本相同,EXP算法丟包率更低,稍好于M?LWDF算法。隨著UE數(shù)目增加,EXP算法和M?LWDF算法能夠保證實時業(yè)務流有更高的優(yōu)先調(diào)度級別,限制丟包率隨著UE數(shù)量增加而增長。接入UE數(shù)量進一步增加(>20),M?LWDF丟包率比EXP丟包率平均小2.403 7%,因為M?LWDF算法給予實時業(yè)務更高優(yōu)先級,是以損失一定的非實時流吞吐量換來的,圖5也給出了佐證。

圖5 BE流吞吐量曲線

圖5給出了三種算法下不同速度下的BE流吞吐量。隨著接入UE數(shù)量增加,三者系統(tǒng)吞吐量呈下降趨勢。在用戶較小時(5~20),三種系統(tǒng)吞吐量基本相同,隨著用戶數(shù)量的增多,EXP算法和M?LWDF算法吞吐量較PF算法吞吐量下降幅度明顯增大,這是保證實時流優(yōu)先調(diào)度必須付出的成本。

非實時業(yè)務流的公平指數(shù)由圖6給出,EXP和M?LWDF算法提供了QoS保證同時,與PF算法相比,公平指數(shù)并沒有顯著降低,仍在可接受的范圍內(nèi)。

圖6 BE流公平指數(shù)曲線

圖7給出了三種算法在UE數(shù)量為20條件下Video流的CDF時延累計函數(shù)曲線,VoIP流也具有相似的規(guī)律。結果表明,EXP算法和M?LWDF算法滿足實時業(yè)務流QoS需求,保證分組交付時延在目標時延之內(nèi)(100 ms)。它們會丟棄時延超過設定閾值的分組,這一點和PF算法有很大不同。

5 結 語

針對車路通信環(huán)境下車輛多媒體信息流高速實時可靠交互需求,提出了一種基于TD?LTE技術的車路通信接入系統(tǒng)資源調(diào)度模型,構建了基于該模型的車路通信仿真場景,研究了PF,EXP和M?LWDF算法在該模型中的無線資源調(diào)度性能。根據(jù)仿真結果可知,在半徑為1 km的小區(qū)且同時支持VoIP流、Video流和BE流的下行調(diào)度過程中:

圖7 UE數(shù)量為20時Video流CDF曲線

(1) UE低速移動時,當負載較小(接入UE數(shù)5~20)時,EXP算法和M?LWDF算法調(diào)度性能基本一致,EXP算法稍好于M?LWDF算法。但是隨著負載增加(>20),在丟包率上M?LWDF算法顯著優(yōu)于EXP算法,不過這是以犧牲一部分吞吐量為代價的。在時延和丟包率上,PF算法表現(xiàn)較差,不適合車路通信系統(tǒng)多媒體信息資源調(diào)度。

(2) UE高速移動時,PF,EXP和M?LWDF算法丟包率過高,難以滿足多媒體業(yè)務的QoS保證。若仍將TD?LTE網(wǎng)絡作為車路接入通信基礎網(wǎng)絡,應從修改物理設配置和尋找新算法兩方面著手。

(3) 整體來說在車路通信環(huán)境下,推薦使用M?LWDF算法進行TD?LTE無線資源調(diào)度。

參考文獻

[1] AMANNA A. Overview of intellidrive/vehicle infrastructure integration (VII) [R]. USA: Virginia Tech Transportation Institute, 2009.

[2] TOULMINET G, BOUSSUGE J, LAURGEAU C. Comparative synthesis of the 3 main European projects dealing with cooperative systems (CVIS, SAFESPOT and COOPERS) and description of COOPERS demonstration site 4 [C]// 2008 11th International IEEE Conference on Intelligent Transportation Systems. [S.l.]: IEEE, 2008: 809?814.

[3] FUJIMOTO A, SAKAI K, OGAWA M, et al. Toward realization of smartway in Japan [C]//15th World Congress on Intelligent Transport Systems and ITS America's 2008 Annual Mee?ting. New York, NY: [s.n.], 2008: 23?31.

[4] CAMPOLO C, VINEL A, MOLINARO A, et al. Modeling broadcasting in IEEE 802.11 p/WAVE vehicular networks [J]. IEEE Communications Letters, 2011, 15(2): 199?201.

[5] WEWETZER C, CALISKAN M, MEIER K, et al. Experimental evaluation of UMTS and wireless LAN for inter?vehicle communication [C]// 2007 7th International Conference on ITS Telecommunications. [S.l.]: IEEE, 2007: 1?6.

[6] WELLENS M, WESTPHAL B, MAHONEN P. Performance evaluation of IEEE 802.11?based WLANs in vehicular scena?rios [C]// IEEE 65th Vehicular Technology Conference. [S.l.]: IEEE, 2007: 1167?1171.

[7] MANGEL T, KOSCH T, HARTENSTEIN H. A comparison of UMTS and LTE for vehicular safety communication at intersections [C]// 2010 IEEE Vehicular Networking Conference. [S.l.]: IEEE, 2010: 293?300.

[8] GERLA M, KLEINROCK L. Vehicular networks and the future of the mobile internet [J]. Computer Networks, 2011, 55(2): 457?469.

[9] CAPOZZI F, PIRO G, GRIECO L, et al. Downlink packet scheduling in lte cellular networks: Key design issues and a survey [J]. IEEE Communications Surveys & Tutorials, 2013, 15(2): 678?700.

[10] KELA P, PUTTONEN J, KOLEHMAINEN N, et al. Dyna?mic packet scheduling performance in UTRA long term evolution downlink [C]// 2008 3rd International Symposium on Wireless Pervasive Computing. [S.l.]: IEEE, 2008: 308?313.

[11] BASUKALA R, MOHDRAMLI H A, SANDRASEGARAN K. Performance analysis of EXP/PF and M?LWDF in downlink 3GPP LTE system [C]// 2009 First Asian Himalayas International Conference on Internet. [S.l.]: IEEE, 2009: 1?5.

[12] CHOI J G, BAHK S. Cell?throughput analysis of the proportional fair scheduler in the single?cell environment [J]. IEEE Transactions on Vehicular Technology, 2007, 56(2): 766?778.

[13] PIRO G, GRIECO L A, BOGGIA G, et al. Simulating LTE cellular systems: an open?source framework [J]. IEEE Tran?sactions on Vehicular Technology, 2011, 60(2): 498?513.

[14] CAMP T, BOLENG J, DAVIES V. A survey of mobility mo?dels for ad hoc network research [J]. Wireless Communications and Mobile Computing, 2002, 2(5): 483?502.

[15] Arizona State University. Video trace library [EB/OL]. [2011?05?20]. http://trace.eas.asu.edu/yuv/index.html.

參考文獻

[1] AMANNA A. Overview of intellidrive/vehicle infrastructure integration (VII) [R]. USA: Virginia Tech Transportation Institute, 2009.

[2] TOULMINET G, BOUSSUGE J, LAURGEAU C. Comparative synthesis of the 3 main European projects dealing with cooperative systems (CVIS, SAFESPOT and COOPERS) and description of COOPERS demonstration site 4 [C]// 2008 11th International IEEE Conference on Intelligent Transportation Systems. [S.l.]: IEEE, 2008: 809?814.

[3] FUJIMOTO A, SAKAI K, OGAWA M, et al. Toward realization of smartway in Japan [C]//15th World Congress on Intelligent Transport Systems and ITS America's 2008 Annual Mee?ting. New York, NY: [s.n.], 2008: 23?31.

[4] CAMPOLO C, VINEL A, MOLINARO A, et al. Modeling broadcasting in IEEE 802.11 p/WAVE vehicular networks [J]. IEEE Communications Letters, 2011, 15(2): 199?201.

[5] WEWETZER C, CALISKAN M, MEIER K, et al. Experimental evaluation of UMTS and wireless LAN for inter?vehicle communication [C]// 2007 7th International Conference on ITS Telecommunications. [S.l.]: IEEE, 2007: 1?6.

[6] WELLENS M, WESTPHAL B, MAHONEN P. Performance evaluation of IEEE 802.11?based WLANs in vehicular scena?rios [C]// IEEE 65th Vehicular Technology Conference. [S.l.]: IEEE, 2007: 1167?1171.

[7] MANGEL T, KOSCH T, HARTENSTEIN H. A comparison of UMTS and LTE for vehicular safety communication at intersections [C]// 2010 IEEE Vehicular Networking Conference. [S.l.]: IEEE, 2010: 293?300.

[8] GERLA M, KLEINROCK L. Vehicular networks and the future of the mobile internet [J]. Computer Networks, 2011, 55(2): 457?469.

[9] CAPOZZI F, PIRO G, GRIECO L, et al. Downlink packet scheduling in lte cellular networks: Key design issues and a survey [J]. IEEE Communications Surveys & Tutorials, 2013, 15(2): 678?700.

[10] KELA P, PUTTONEN J, KOLEHMAINEN N, et al. Dyna?mic packet scheduling performance in UTRA long term evolution downlink [C]// 2008 3rd International Symposium on Wireless Pervasive Computing. [S.l.]: IEEE, 2008: 308?313.

[11] BASUKALA R, MOHDRAMLI H A, SANDRASEGARAN K. Performance analysis of EXP/PF and M?LWDF in downlink 3GPP LTE system [C]// 2009 First Asian Himalayas International Conference on Internet. [S.l.]: IEEE, 2009: 1?5.

[12] CHOI J G, BAHK S. Cell?throughput analysis of the proportional fair scheduler in the single?cell environment [J]. IEEE Transactions on Vehicular Technology, 2007, 56(2): 766?778.

[13] PIRO G, GRIECO L A, BOGGIA G, et al. Simulating LTE cellular systems: an open?source framework [J]. IEEE Tran?sactions on Vehicular Technology, 2011, 60(2): 498?513.

[14] CAMP T, BOLENG J, DAVIES V. A survey of mobility mo?dels for ad hoc network research [J]. Wireless Communications and Mobile Computing, 2002, 2(5): 483?502.

[15] Arizona State University. Video trace library [EB/OL]. [2011?05?20]. http://trace.eas.asu.edu/yuv/index.html.

參考文獻

[1] AMANNA A. Overview of intellidrive/vehicle infrastructure integration (VII) [R]. USA: Virginia Tech Transportation Institute, 2009.

[2] TOULMINET G, BOUSSUGE J, LAURGEAU C. Comparative synthesis of the 3 main European projects dealing with cooperative systems (CVIS, SAFESPOT and COOPERS) and description of COOPERS demonstration site 4 [C]// 2008 11th International IEEE Conference on Intelligent Transportation Systems. [S.l.]: IEEE, 2008: 809?814.

[3] FUJIMOTO A, SAKAI K, OGAWA M, et al. Toward realization of smartway in Japan [C]//15th World Congress on Intelligent Transport Systems and ITS America's 2008 Annual Mee?ting. New York, NY: [s.n.], 2008: 23?31.

[4] CAMPOLO C, VINEL A, MOLINARO A, et al. Modeling broadcasting in IEEE 802.11 p/WAVE vehicular networks [J]. IEEE Communications Letters, 2011, 15(2): 199?201.

[5] WEWETZER C, CALISKAN M, MEIER K, et al. Experimental evaluation of UMTS and wireless LAN for inter?vehicle communication [C]// 2007 7th International Conference on ITS Telecommunications. [S.l.]: IEEE, 2007: 1?6.

[6] WELLENS M, WESTPHAL B, MAHONEN P. Performance evaluation of IEEE 802.11?based WLANs in vehicular scena?rios [C]// IEEE 65th Vehicular Technology Conference. [S.l.]: IEEE, 2007: 1167?1171.

[7] MANGEL T, KOSCH T, HARTENSTEIN H. A comparison of UMTS and LTE for vehicular safety communication at intersections [C]// 2010 IEEE Vehicular Networking Conference. [S.l.]: IEEE, 2010: 293?300.

[8] GERLA M, KLEINROCK L. Vehicular networks and the future of the mobile internet [J]. Computer Networks, 2011, 55(2): 457?469.

[9] CAPOZZI F, PIRO G, GRIECO L, et al. Downlink packet scheduling in lte cellular networks: Key design issues and a survey [J]. IEEE Communications Surveys & Tutorials, 2013, 15(2): 678?700.

[10] KELA P, PUTTONEN J, KOLEHMAINEN N, et al. Dyna?mic packet scheduling performance in UTRA long term evolution downlink [C]// 2008 3rd International Symposium on Wireless Pervasive Computing. [S.l.]: IEEE, 2008: 308?313.

[11] BASUKALA R, MOHDRAMLI H A, SANDRASEGARAN K. Performance analysis of EXP/PF and M?LWDF in downlink 3GPP LTE system [C]// 2009 First Asian Himalayas International Conference on Internet. [S.l.]: IEEE, 2009: 1?5.

[12] CHOI J G, BAHK S. Cell?throughput analysis of the proportional fair scheduler in the single?cell environment [J]. IEEE Transactions on Vehicular Technology, 2007, 56(2): 766?778.

[13] PIRO G, GRIECO L A, BOGGIA G, et al. Simulating LTE cellular systems: an open?source framework [J]. IEEE Tran?sactions on Vehicular Technology, 2011, 60(2): 498?513.

[14] CAMP T, BOLENG J, DAVIES V. A survey of mobility mo?dels for ad hoc network research [J]. Wireless Communications and Mobile Computing, 2002, 2(5): 483?502.

[15] Arizona State University. Video trace library [EB/OL]. [2011?05?20]. http://trace.eas.asu.edu/yuv/index.html.

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