A Hybrid Clustering Approach in Coordinated Multi-Point Transmission System
|
|
- Elisabeth Ross
- 5 years ago
- Views:
Transcription
1 2012 7th International ICST Conference on Communications and Networing in China (CHINACOM) A Hybrid Clustering Approach in Coordinated Multi-Point Transmission System Cui Zeng, Pinyi Ren, Chao Zhang and Gangming Lv School of Electronic and Information Engineering Xi an Jiaotong University, Xi an, China zengcui xjtu@126.com, {pyren, chaozhang and gmlv }@mail.xjtu.edu.cn, Abstract Coordinated Multi-Point transmission technology which can improve cell edge spectral efficiency and meet the demand of high-speed transmission is one of the ey technologies of LTE-Advanced. In this wor, we propose a hybrid cell clustering approach in coordinated multi-point transmission system which is more efficient and practical. First, we divide a cell into three sectors: the intra-cell sector, the intra-cluster sector and the intercluster sector. Users in these three sectors are designed to utilize the non-coordinated approach, the static coordinated approach, and the dynamic coordinated approach, respectively. Second, we propose a method to identify the user s type in order to choose the best coordinated approach. Finally, we give a resource scheduling method to suit the novel clustering approach. Simulations show that, compared with static clustering and dynamic clustering, our proposed hybrid clustering algorithm can achieve the highest cell edge spectral efficiency. Index Terms Coordinated Multi-Point transmission; hybrid cell clustering approach; intra-cell sector; intra-cluster sector; inter-cluster sector. I. INTRODUCTION In order to deal with the conflict between the growing demand and limited frequency resource, full frequency reuse (FFR) has become the consensus of the industry[1]. Based on FFR, the system operates in interference-limited regime. The interference received by mobile terminal mainly comes from the neighboring cells, especially the users located in the edge of the cell. The signal to interference-plus-noise ratio (SINR) of the cell edge users is far lower than that of the central users, which reduces the cell s average spectrum efficiency. In view of this problem, Coordinated Multi-Point (CoMP) transmission technology was proposed[2]. CoMP can improve the cell edge users spectral efficiency and meet the demand for high speed wireless data communications. The core of CoMP technology is that independent cells share data and relevant information with each other. By joint processing or coordinated scheduling, the interference can be reduced or even turned into beneficial factors [3]. Based on the information sharing model and the coupling degree of cells, CoMP can be divided into two categories, namely joint processing and coordinated scheduling[3]. Joint processing requires data sharing among base stations, and channel information interaction between users and base station, which brings a lot of feedbac consumption and greatly increase system overhead [4,5]. Ideal base station coordination is proposed in[6,7]. Full coordination is very difficult to realize, especially for large-scale networs. Therefore, in practical systems, limited number of base stations forming clustering coordination networ should be considered [8]. Popular clustering methods include static clustering, semistatic clustering and dynamic clustering[9,10,11]. Static clustering coordination generally selects adjacent base stations as coordination base stations and does not change with time, so scheduling is low complexity. Users do not need feedbac realtime CSI to base station to cluster. Since it constrains fixed base stations to cooperate, fully distributed macro-diversity cannot be achieved [12]. For dynamic clustering, users adapt to their own environments and need to choose coordinated base station during each time slot [13]. Dynamic clustering meets the real-time needs of the users, and turns the strongest interference into useful signal, which greatly improves the users throughput. Since clusters change dynamically, the complexity of scheduling is high and the feedbac overhead is large [14]. Forming cluster reduce the feedbac overhead of the system, can reduce the complexity of the code design and also reduce the burden of bachaul. On the other hand, however, clustering maes a part of signals to interference rather than useful signal, what s more, unreasonable clustering mechanisms may lead a strong signal into a strong interference. In addition, clustering may cause performance deterioration for the users located in the edge of the cluster, and lead to the unfairness among users. So we need a good clustering strategy to wea these adverse effects and search for an optimal compromise between the design complexity and performance. Our goal is to propose a compromising cooperation approach that maximizes the capability of CoMP and lower the complexity of the system as well. Based on the analysis of the disadvantages of the above strategies, we proposed a hybrid clustering, which has lower scheduling complexity and smaller feedbac overhead but maximizes the capability. First, we divide a cell into three sectors: the intra-cell sector, the intra-cluster sector and the inter-cluster sector. Users in these three sectors are designed to utilize the non-coordinated approach, the static coordinated approach, and the dynamic coordinated approach, respectively. Simulations show that the proposed hybrid clustering approach can approximately get the highest cell edge spectral efficiency. The rest of the paper is organized as follows: In Section II, we give the system model. Section III presents the hybrid clustering approach. Numerical results are presented in Section IV and conclusions are drawn in Section V /12/$ IEEE
2 II. SYSTEM MODEL Consider a cellular MIMO networ consisting of N base stations and K users. Each BS has N t antennas and each user has N r antennas. Each BS chooses only one user of each time-slot t for downlin transmission. The number of data streams to user is L and the data streams are denoted by L 1 vector s, the all networ transmission data streams are denoted by s = [s T 1,...,,s T,...,sT K ]T. In the cluster C of user, there are B (B<N) BSs. The system model of coordinated multi-point transmission system is illustrated in Fig 1. User feedbac CSI to local BS (white), three BSs service the user at the same time (blue), and they share the CSI and the transmission data through the bachaul. Assume user is located in the BS b, we call it local station, the cluster of user is C, the pre-coding matrix is denoted by N t L matrix W b. The received signal of user is given by y =H b Ws b + H i Ws i + H j Wj s +z (1) i C,i b j c, c C where H b is the N r N t channel matrix from BS b to user, z CN(0, I) is additive white Gaussian noise. Superscript denotes BS and subscript denotes user. The first part of (1) denote signal comes from the local BS, the second part denote signal comes from other BSs in the cluster C, and the third part denote signal comes from the other clusters. When non-coordinated, SINR is given by SINR NC = i C,i =b W i Hi 2 + W b Hb 2 j c, c =C, = W j Hj 2 +N o (2) When coordinated, interference coming from cluster becomes useful signal, SINR is given by: W b H b 2 + i C SINR Co =,i b W i H i 2 j c, c C, W j H j 2 (3) + N o Rate of user can be expressed by R =log 2 (1 + SINR Co ) (4) The optimization goal is to maximize the throughput through the clustering: A. Cell division max C SINR Co (5) III. HYBRID CLUSTERING APPROACH The existing researches show that, the networ is in interference-limited when there is full frequency reuse, especially to the edge users, so moderate reducing interference can significantly improve the edge users performance. They introduced coordinated multi-point transmission in LTE-A. As show in Fig 2, the 3 adjacent cells form a static cluster and coordinated. Therefore the main components of interference Fig. 1. System model of coordinated multi-point transmission systems. can be divided into two types: (1) caused by adjacent cells in the static cluster, (2) caused by adjacent clusters. This paper does different treatment of the two types of interference. Based on the above ideas, we divide cell into three sectors, as show in Fig 2 the intra-cell sector (white part), the intracluster sector (blue part) and the inter-cluster sector (red part). In the intra-cell sector, the user has higher SINR. So the users use the traditional transmission directly serviced by the local cell. In the intra-cluster sector, the user has low SINR, and the interference mainly caused by the adjacent cells in the cluster. So we use the static clustering approach. In the intercluster sector, the interference is mainly caused by the adjacent clusters. The user has low SINR and it is hard to improve performance through static clustering approach. So we use the dynamic clustering approach. B. The judgment of the user s type The users have three types: intra-cell users, intra-cluster users, and inter-cluster users. Before transmitting, the system needs to first determine the type of the user, in order to select the best transmission scheme. The type is determined by the users themselves, and then feedbac to the base station. The power received from the local cell i of the user is P local (i) =p i α 2 (, i) (6) ( The power ) received from the coordinated cell j j C static of the user is (j) =p j α 2 (, j) (7) The power received from the cell m in other clusters of the user is (m) =p m α 2 (, m) (8) where p n (n = i, j, m) is the transmission power, α 2 (, n) (n = i, j, m) is the fading factor. The power received from the static cluster cells (including local cell) is = j C static (j) (9) 628
3 h =[h s1 h s2 h s3 ]. Assume ṽ is the right singular vector corresponding to the largest singular value of h. Then the global pre-coding matrix is: [v T s 1 v T s 2 v T s 3 ] T =ṽ (12) Which vs T 1,vT s 2,vT s 3 are the pre-coding matrix of the cell s 1,s 2,s 3 respectively. 3) If the user is an inter-cluster user, uses the dynamic clustering scheme. Details as follows: Fig. 2. The model of the cell division. The power received from the all cells in other clusters is = j B C static When Non-CoMP, SINR is SINR = P local (i) (j) (10) + + N o (11) where N o is noise power. The first step: determination of the cell center/edge user The user is mainly accorded to the received power of the pilot signal to determine the type. If satisfied SINR < SINR edge, the user is a cell edge user; otherwise, the user is an intra-cell user, which SINR edge is the threshold. The second step: determination of the intra-cluster/intercluster user When the user is determined to a cell edge user, continue to be determined. If P co <Pnon co, the user is an intercluster user; otherwise, is an intra-cluster user. Conclusion: if SINR >SINR edge, user is an intra-cell user; if SINR <SINR edge intra-cluster user; if SINR <SINR edge inter-cluster user. and and >, user is an <, user is an C. Hybrid clustering method We propose a hybrid clustering method. Different types of users use different clustering strategy. As follows: Three adjacent cells compose a static cluster, the entire networ is divided into a number of static clusters. First the user calculates the received power of coordinated cells and non- coordinated cells, P co and respectively. 1) According to the above rules of the division, if the user is an intra-cell user, uses the non-coordinated transmission scheme. The user is served by the local cell. 2) If the user is an intra-cluster user, uses the static clustering scheme. The three adjacent cells compose the static cluster. For static clustering scheme, uses the joint processing based the global pre-coding. The cluster of user is C = {s 1,s 2,s 3 }, which s 1 is the local cell, s 2,s 3 are the other coordinated cells. The three cells and the user form a virtual MIMO channel Compute the received power from all cells P j (j B) and sort. Choose the first Y (m) cells with maximum received power to be alternative cells. j =argmaxp j j (13) Choose two cells from the Y (m) cells to coordinate with the local cell. Literate over all the possible clustering combination (total CY 2 () inds), calculate SINR i,j Co of each ind, SINR i,j Co = W b Hb 2 + W i Hi 2 + W j Hj 2 (14) W j Hj 2 +N o j Λ c, Λ c =c, = Choose the maximum one (i,j ) as coordinated cluster. (i,j ) = arg max i,j Y () SINRi,j Co (15) (i,j ) are just the coordinated cells of the inter-cell user. 4) According to the type of the cluster and the coordinated cells, local cell send coordinated request to the coordinated cells. Mae certain the coordination, local cell share the channel information and transmission data to the coordinated cells. D. Scheduling algorithm 1) There are N RBs. And there is a user set {U i } in any RB i. I s (i) is the resource allocation indicator factor of the cell s in RB i. ifi s (i) =1,indicating that the resource i of cell s has been allocated. And if I s (i) = 0, indicating that the resource i of cell s has not been allocated. The maximum rate of user in channel n is r n (i), the historical rate of user is T. Selecting the highest priority user in the resource bloc i, which is determined by: r n (i) =arg max (16) {U } T After a resource bloc been allocated, need to update the historical throughput T = T + r n (i). In order to ensure orthogonal in the cell, each resource bloc can only be assigned to a user in the same cell. 2) The cluster of user is {s 1,s 2,s 3 }, if i {1,2,3} I s i (i) 1, indicates that in the coordination 629
4 TABLE I SYSTEM-LEVEL SIMULATION PARAMETER SETTINGS Parameter Setting Channel model SCM Simulation scene Urban macro-cell Number of cells 57 Number of MSs per cell 10 bandwidth 10MHz Carrier frequency 2.5GHz Sub-carriers interval 15Hz BS antenna structure N t =4 MS antenna structure N r =2 MIMO mode SU-MIMO ( single stream) Channel estimation error Ideal estimation Receiving mode MMSE Lin to system mapping MIESM Service type Full buffer CDF(%) Static CoMP Dynamic CoMP 10 Performance of Proposed cell edge user Normalized Cell Average Spectrum Efficiency(bps) cluster cells, some cell resource have been allocated. The user scheduling failed, then update the user set{u i } {U i } = {U i } (17) 3) If the scheduling of user is successful, let I si (i) = 1,i {1, 2, 3}, {U i } = {U i } 4) Follow by cycle, until all users are scheduled, that is {U i } =. 5) If {U i } =, update the resource bloc. Followed by cycle, until all resource blocs are scheduled. IV. SIMULATION RESULTS In this section, we give the simulation results of the proposed algorithm. As comparison, two other algorithms are considered: Static-CoMP The local cell and the adjacent two cells compose the coordinated cells. And use the joint processing technology of the global pre-coding. Dynamic-CoMP The coordinated user selects the optimal two cells in all cells to compose the coordinated cells. And use the joint processing technology of the global pre-coding. Simulation settings follow the ITU M.2135 standard. The simulation system was consisted of 57 cells, each cell contains 10 users and users are distributed in the cell with a uniform random distribution. Wraparound technology was used to eliminate the edge effect. The threshold which to determine the cell intra or edge users is determined based on the proportion of the coordinated users. We assumed the proportion of the coordinated user is 20%. The related simulation parameter settings are shown in table 1. A. The performance of different coordinated solutions Fig 3 gives the CDF of normalized cell average spectrum efficiency in urban macro cell scenario. And table 2 gives the performance of different coordinated solutions. It can be seen from the figure and the table that the performance of the proposed scheme is the best, the dynamic CoMP is second Fig. 3. CDF of normalized cell average spectrum efficiency. TABLE II THE PERFORMANCE OF DIFFERENT COORDINATED SOLUTIONS The type of Cell average Gain Cell edge Gain transmission spectral user spectral efficiency efficiency (bps/hz) (bps/hz) Static- CoMP % % Dynamic- CoMP % % Proposed % % and the static CoMP is the worst. The performance of the dynamic CoMP and the proposed scheme are very similar. But regardless of the cell average spectrum efficiency or the cell edge spectral efficiency, the performance of the proposed scheme is better than the dynamic CoMP. Figure 4 and figure 5 show the cell average spectral efficiency histogram and the cell edge user spectral efficiency histogram in the different coordinated scheme, respectively. We can see from that when static CoMP, cell average spectral efficiency is 1.87 bps/hz, and cell edge spectral efficiency is bps/hz. Compared to static CoMP, dynamic CoMP not only improve 8% of the cell average spectral efficiency but also 34.5% of the cell edge spectral efficiency. The performance of the proposed scheme is the best. It gets the cell average spectral efficiency gain of 13% and the cell edge spectral efficiency gain of 35%. The proposed scheme is outperformed from the two other schemes due to users selecting the best transmission scheme. B. The influence of different threshold According the threshold SINR edge, divided users into intracell user and cell edge user. When SINR >SINR edge, the user is an intra-cell user, and uses Non-CoMP scheme. When SINR <SINR edge, the user is a cell edge user, and uses CoMP scheme. Threshold will affect the number of the coordinated users and will also affect the cell performance. 630
5 Fig. 4. Cell average spectral efficiency histogram. Fig. 5. Cell edge user spectrum efficiency histogram. Fig 6 shows the cell average spectrum efficiency of the proposed scheme in different thresholds. The threshold is smaller, the cell average spectrum efficiency is greater. This is because the threshold is larger, more resources are assigned to the coordinated users, less resources are assigned to the non-coordinated user, so the cell average spectrum efficiency will reduce. The threshold is smaller, the cell edge spectrum efficiency is greater. This is because the threshold is larger, coordinated users are more. And the chance to be scheduled is smaller. So increase the threshold will not improve the throughput of the cell edge users. V. CONCLUSION We propose a hybrid clustering approach in coordinated multi-point transmission system. For the proposed approach, the users location information is taen into consideration, and users with different locations utilize different coordinated schemes.three schemes, namely Non-comp, static-comp, and dynamic-comp, are applied to intra-cell users, intra-cluster users, and inter-cell users, respectively. Simulations show that, that our scheme cam improve both the cell average spectral efficiency and the cell edge spectral efficiency. ACKNOWLEDGMENT This wor was supported in part by the National Natural Science Foundation of China ( ),the Nation- CDF(%) %coordinated user 10 20%coordinated user 30%coordinated user Normalized Cell Average Spectrum Efficiency(bps) Fig. 6. Cell average spectrum efficiency in different threshold. al Science and Technology Major Project(2012ZX ), and the National High-Tech Development Program (2011AA01A105). REFERENCES [1] TR v1.0.0, Further Advancement of E-UTRA, Physical layer aspects, 3GPP Technical Report. [2] M. Karaayali, G. Foschini and R. Valenzuela, Networ Coordination for spectrally efficient Communications in Cellular Systems, in proc.of IEEE Wireless Communications, Volume:13, Issue:4, pp.56-61, Aug [3] 3GPP TR , Further Advancements for E-UTRA Physical Layer Aspects(Release 9), v.1.5.2, January Sep [4] G. J. Foschini, K. Karaayali, and R. Valenzuela, Coordinating multiple antenna cellular networs to achieve enormous spectral efficiency, in proc.of IEEE Communications, Vol. 153, Issue:4, pp , August [5] Stefan Bruec, Lu Zhao, Jochen Giese and M. Awais Amin, Centralized Scheduling for Joint Transmission Coordinated Multi-Point in LTE- Advanced, in proc.of IEEE WSA, Bremen,pp , Feb [6] Someh, O. Simeone, Y. Bar Ness, A. M. Haimovich. Distributed multicell zero-forcing beamforming in cellular downlin channels, in proc.of IEEE Global Telecommunications Conference, vol.27, Dec 2006, pp.1-6. [7] Jing Shen, N. C. Tse David, B. Soriaga Joseph, Hou Jilei, E. Smee John, Padovani Roberto. Downlin macro-diversity in cellular networs, in proc.of IEEE International Symposium on Information Theory, pp.1-5, [8] Linan Sun, Zhongzhao Zhang, Xuejun Sha, and Weilin Jiang. Improved static clustering base station coordination, in proc.of CCWMC, shanghai, China, pp , Dec [9] 3GPP TR R , Clustering for CoMP Transmission, Jan. 12-Jan [10] 3GPP TR R , Setuo of CoMP Cooperation areas, January [11] 3GPP TR R , Cell Clustering for CoMP Transmission/Reception, Feb. 9-Feb [12] Fan Huang, Yafeng Wang, Jian Geng, Mei Wu, Dacheng Yang, Clustering Approach in Coordinated Multi point Transmission/Reception System, in proc.of IEEE VTCF, pp.1-5, [13] Shanghui Xiao, Zhongpei Zhang, Qinmin Wang, Zhiping Shi, Coordinated Multi-point Transmission Systems with Dynamical Cell Clustering Strategies, in proc.of IEEE CHINACOM, pp.1-5, [14] Papadogiannis.A,Gesbert.D,Hardouin.E, R D Div, A Dynamic Clustering Approach in Wireless Networs with Multi-Cell Cooperative Processing, in proc.of IEEE ICC, pp ,
The Potential of Restricted PHY Cooperation for the Downlink of LTE-Advanced
The Potential of Restricted PHY Cooperation for the Downlin of LTE-Advanced Marc Kuhn, Raphael Rolny, and Armin Wittneben, ETH Zurich, Switzerland Michael Kuhn, University of Applied Sciences, Darmstadt,
More informationSystem Performance of Cooperative Massive MIMO Downlink 5G Cellular Systems
IEEE WAMICON 2016 April 11-13, 2016 Clearwater Beach, FL System Performance of Massive MIMO Downlink 5G Cellular Systems Chao He and Richard D. Gitlin Department of Electrical Engineering University of
More informationA Graph-Theory Approach to Joint Radio Resource Allocation for Base Station Cooperation
A Graph-Theory Approach to Joint Radio Resource Allocation for Base Station Cooperation Geng Su Laurie Cuthbert Lin Xiao Queen Mary University of London School of Electronic Engineering and Computer Science
More informationA Practical Resource Allocation Approach for Interference Management in LTE Uplink Transmission
JOURNAL OF COMMUNICATIONS, VOL. 6, NO., JULY A Practical Resource Allocation Approach for Interference Management in LTE Uplink Transmission Liying Li, Gang Wu, Hongbing Xu, Geoffrey Ye Li, and Xin Feng
More informationResource Allocation Strategies Based on the Signal-to-Leakage-plus-Noise Ratio in LTE-A CoMP Systems
Resource Allocation Strategies Based on the Signal-to-Leakage-plus-Noise Ratio in LTE-A CoMP Systems Rana A. Abdelaal Mahmoud H. Ismail Khaled Elsayed Cairo University, Egypt 4G++ Project 1 Agenda Motivation
More informationA Decentralized Optimization Approach to Backhaul-Constrained Distributed Antenna Systems
A Decentralized Optimization Approach to Bachaul-Constrained Distributed Antenna Systems Patric Marsch, Gerhard Fettweis Vodafone Chair Mobile Communications Systems Technische Universität Dresden, Germany
More informationOn the Value of Coherent and Coordinated Multi-point Transmission
On the Value of Coherent and Coordinated Multi-point Transmission Antti Tölli, Harri Pennanen and Petri Komulainen atolli@ee.oulu.fi Centre for Wireless Communications University of Oulu December 4, 2008
More informationMassive MIMO a overview. Chandrasekaran CEWiT
Massive MIMO a overview Chandrasekaran CEWiT Outline Introduction Ways to Achieve higher spectral efficiency Massive MIMO basics Challenges and expectations from Massive MIMO Network MIMO features Summary
More informationAnalysis of RF requirements for Active Antenna System
212 7th International ICST Conference on Communications and Networking in China (CHINACOM) Analysis of RF requirements for Active Antenna System Rong Zhou Department of Wireless Research Huawei Technology
More informationPerformance Analysis of CoMP Using Scheduling and Precoding Techniques in the Heterogeneous Network
International Journal of Information and Electronics Engineering, Vol. 6, No. 3, May 6 Performance Analysis of CoMP Using Scheduling and Precoding Techniques in the Heterogeneous Network Myeonghun Chu,
More informationEasyChair Preprint. A User-Centric Cluster Resource Allocation Scheme for Ultra-Dense Network
EasyChair Preprint 78 A User-Centric Cluster Resource Allocation Scheme for Ultra-Dense Network Yuzhou Liu and Wuwen Lai EasyChair preprints are intended for rapid dissemination of research results and
More informationAadptive Subcarrier Allocation for Multiple Cognitive Users over Fading Channels
Proceedings of the nd International Conference On Systems Engineering and Modeling (ICSEM-3) Aadptive Subcarrier Allocation for Multiple Cognitive Users over Fading Channels XU Xiaorong a HUAG Aiping b
More informationSurvey of Power Control Schemes for LTE Uplink E Tejaswi, Suresh B
Survey of Power Control Schemes for LTE Uplink E Tejaswi, Suresh B Department of Electronics and Communication Engineering K L University, Guntur, India Abstract In multi user environment number of users
More informationDistributed Coordinated Multi-Point Downlink Transmission with Over-the-Air Communication
Distributed Coordinated Multi-Point Downlink Transmission with Over-the-Air Communication Shengqian Han, Qian Zhang and Chenyang Yang School of Electronics and Information Engineering, Beihang University,
More informationCoordinated Multi-Point MIMO Processing for 4G
Progress In Electromagnetics Research Symposium Proceedings, Guangzhou, China, Aug. 25 28, 24 225 Coordinated Multi-Point MIMO Processing for 4G C. Reis, A. Correia, 2, N. Souto, 2, and M. Marques da Silva
More informationSystem-Level Performance of Downlink Non-orthogonal Multiple Access (NOMA) Under Various Environments
System-Level Permance of Downlink n-orthogonal Multiple Access (N) Under Various Environments Yuya Saito, Anass Benjebbour, Yoshihisa Kishiyama, and Takehiro Nakamura 5G Radio Access Network Research Group,
More informationCombating Interference: MU-MIMO, CoMP, and HetNet
MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Combating Interference: MU-MIMO, CoMP, and HetNet Liu, L.; Zhang, J.; Yi, Y.; Li, H.; Zhang, J. TR2012-027 September 2012 Abstract Combating
More informationREMOTE CONTROL OF TRANSMIT BEAMFORMING IN TDD/MIMO SYSTEMS
The 7th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 6) REMOTE CONTROL OF TRANSMIT BEAMFORMING IN TDD/MIMO SYSTEMS Yoshitaa Hara Kazuyoshi Oshima Mitsubishi
More informationMulti-user Space Time Scheduling for Wireless Systems with Multiple Antenna
Multi-user Space Time Scheduling for Wireless Systems with Multiple Antenna Vincent Lau Associate Prof., University of Hong Kong Senior Manager, ASTRI Agenda Bacground Lin Level vs System Level Performance
More informationStudy of Handover Techniques for 4G Network MIMO Systems
Study of Handover Techniques for 4G Network MIMO Systems 1 Jian-Sing Wang, 2 Jeng-Shin Sheu 1 National Yunlin University of Science and Technology Department of CSIE E-mail: M10017008@yuntech.edu.tw 2
More informationCoordinated Multi-Point (CoMP) Transmission in Downlink Multi-cell NOMA Systems: Models and Spectral Efficiency Performance
1 Coordinated Multi-Point (CoMP) Transmission in Downlink Multi-cell NOMA Systems: Models and Spectral Efficiency Performance Md Shipon Ali, Ekram Hossain, and Dong In Kim arxiv:1703.09255v1 [cs.ni] 27
More informationDynamic Grouping and Frequency Reuse Scheme for Dense Small Cell Network
GRD Journals Global Research and Development Journal for Engineering International Conference on Innovations in Engineering and Technology (ICIET) - 2016 July 2016 e-issn: 2455-5703 Dynamic Grouping and
More informationPerformance Evaluation of Uplink Closed Loop Power Control for LTE System
Performance Evaluation of Uplink Closed Loop Power Control for LTE System Bilal Muhammad and Abbas Mohammed Department of Signal Processing, School of Engineering Blekinge Institute of Technology, Ronneby,
More informationAdaptive Co-primary Shared Access Between Co-located Radio Access Networks
Adaptive Co-primary Shared Access Between Co-located Radio Access Networks Sofonias Hailu, Alexis A. Dowhuszko and Olav Tirkkonen Department of Communications and Networking, Aalto University, P.O. Box
More informationDATA ALLOCATION WITH MULTI-CELL SC-FDMA FOR MIMO SYSTEMS
DATA ALLOCATION WITH MULTI-CELL SC-FDMA FOR MIMO SYSTEMS Rajeshwari.M 1, Rasiga.M 2, Vijayalakshmi.G 3 1 Student, Electronics and communication Engineering, Prince Shri Venkateshwara Padmavathy Engineering
More informationFractional Frequency Reuse Schemes and Performance Evaluation for OFDMA Multi-hop Cellular Networks
Fractional Frequency Reuse Schemes and Performance Evaluation for OFDMA Multi-hop Cellular Networks Yue Zhao, Xuming Fang, Xiaopeng Hu, Zhengguang Zhao, Yan Long Provincial Key Lab of Information Coding
More informationPerformance of the LTE Uplink with Intra-Site Joint Detection and Joint Link Adaptation
Performance of the LTE Uplink with Intra-Site Joint Detection and Joint Link Adaptation Andreas Müller, Philipp Frank and Joachim Speidel Institute of Telecommunications, University of Stuttgart, Germany
More informationBlock Error Rate and UE Throughput Performance Evaluation using LLS and SLS in 3GPP LTE Downlink
Block Error Rate and UE Throughput Performance Evaluation using LLS and SLS in 3GPP LTE Downlink Ishtiaq Ahmad, Zeeshan Kaleem, and KyungHi Chang Electronic Engineering Department, Inha University Ishtiaq001@gmail.com,
More informationRadio Resource Allocation Scheme for Device-to-Device Communication in Cellular Networks Using Fractional Frequency Reuse
2011 17th Asia-Pacific Conference on Communications (APCC) 2nd 5th October 2011 Sutera Harbour Resort, Kota Kinabalu, Sabah, Malaysia Radio Resource Allocation Scheme for Device-to-Device Communication
More informationJoint User Selection and Beamforming Schemes for Inter-Operator Spectrum Sharing
Joint User Selection and Beamforming Schemes for Inter-Operator Spectrum Sharing Johannes Lindblom, Erik G. Larsson and Eleftherios Karipidis Linköping University Post Print N.B.: When citing this work,
More informationA Hybrid Signalling Scheme for Cellular Mobile Networks over Flat Fading
A Hybrid Signalling Scheme for Cellular Mobile Networs over Flat Fading Hassan A. Abou Saleh and Steven D. Blostein Dept. of Electrical and Computer Eng. Queen s University, Kingston, K7L 3N6 Canada hassan.abousaleh@gmail.com
More informationCoordinated Multi-Point Transmission for Interference Mitigation in Cellular Distributed Antenna Systems
Coordinated Multi-Point Transmission for Interference Mitigation in Cellular Distributed Antenna Systems M.A.Sc. Thesis Defence Talha Ahmad, B.Eng. Supervisor: Professor Halim Yanıkömeroḡlu July 20, 2011
More informationResearch Article Intercell Interference Coordination through Limited Feedback
Digital Multimedia Broadcasting Volume 21, Article ID 134919, 7 pages doi:1.1155/21/134919 Research Article Intercell Interference Coordination through Limited Feedback Lingjia Liu, 1 Jianzhong (Charlie)
More informationSmart M2M Uplink Scheduling Algorithm over LTE
http://dx.doi.org/1.5755/j1.eee.19.1.5457 ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 19, NO. 1, 213 Smart M2M Uplin Scheduling Algorithm over LTE Jinghua Ding 1, Abhishe Roy 2, Navrati Saxena
More informationLTE-Advanced research in 3GPP
LTE-Advanced research in 3GPP GIGA seminar 8 4.12.28 Tommi Koivisto tommi.koivisto@nokia.com Outline Background and LTE-Advanced schedule LTE-Advanced requirements set by 3GPP Technologies under investigation
More informationDynamic Fair Channel Allocation for Wideband Systems
Outlines Introduction and Motivation Dynamic Fair Channel Allocation for Wideband Systems Department of Mobile Communications Eurecom Institute Sophia Antipolis 19/10/2006 Outline of Part I Outlines Introduction
More informationMulti cell Coordination via Scheduling, Beamforming and Power control in MIMO-OFDMA
Multi cell Coordination via Scheduling, Beamforming and Power control in MIMO-OFDMA G.Rajeswari 1, D.LalithaKumari 2 1 PG Scholar, Department of ECE, JNTUACE Anantapuramu, Andhra Pradesh, India 2 Assistant
More informationNovel Transmission Schemes for Multicell Downlink MC/DS-CDMA Systems Employing Time- and Frequency-Domain Spreading
Novel Transmission Schemes for Multicell Downlink MC/DS-CDMA Systems Employing Time- and Frequency-Domain Spreading Jia Shi and Lie-Liang Yang School of ECS, University of Southampton, SO7 BJ, United Kingdom
More informationEnergy-Efficient Configuration of Frequency Resources in Multi-Cell MIMO-OFDM Networks
0 IEEE 3rd International Symposium on Personal, Indoor and Mobile Radio Communications - PIMRC) Energy-Efficient Configuration of Frequency Resources in Multi-Cell MIMO-OFDM Networks Changyang She, Zhikun
More informationTHE fifth-generation (5G) wireless system is expected to. Sparse Beamforming and User-Centric Clustering for Downlink Cloud Radio Access Network
1 Sparse Beamforming and User-Centric Clustering for Downlin Cloud Radio Access Networ Binbin Dai, Student Member, IEEE and Wei Yu, Fellow, IEEE arxiv:1410.500v1 [cs.it] 19 Oct 014 Abstract This paper
More informationQoS Optimization For MIMO-OFDM Mobile Multimedia Communication Systems
QoS Optimization For MIMO-OFDM Mobile Multimedia Communication Systems M.SHASHIDHAR Associate Professor (ECE) Vaagdevi College of Engineering V.MOUNIKA M-Tech (WMC) Vaagdevi College of Engineering Abstract:
More informationOn the Complementary Benefits of Massive MIMO, Small Cells, and TDD
On the Complementary Benefits of Massive MIMO, Small Cells, and TDD Jakob Hoydis (joint work with K. Hosseini, S. ten Brink, M. Debbah) Bell Laboratories, Alcatel-Lucent, Germany Alcatel-Lucent Chair on
More informationUniversity of Bristol - Explore Bristol Research. Peer reviewed version. Link to published version (if available): /PIMRC.2009.
Beh, K. C., Doufexi, A., & Armour, S. M. D. (2009). On the performance of SU-MIMO and MU-MIMO in 3GPP LTE downlink. In IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications,
More informationLTE in Unlicensed Spectrum
LTE in Unlicensed Spectrum Prof. Geoffrey Ye Li School of ECE, Georgia Tech. Email: liye@ece.gatech.edu Website: http://users.ece.gatech.edu/liye/ Contributors: Q.-M. Chen, G.-D. Yu, and A. Maaref Outline
More informationPartial Co-channel based Overlap Resource Power Control for Interference Mitigation in an LTE-Advanced Network with Device-to-Device Communication
CTRQ 2013 : The Sixth International Conference on Communication Theory Reliability and Quality of Service Partial Co-channel based Overlap Resource Power Control for Interference Mitigation in an LTE-Advanced
More informationHype, Myths, Fundamental Limits and New Directions in Wireless Systems
Hype, Myths, Fundamental Limits and New Directions in Wireless Systems Reinaldo A. Valenzuela, Director, Wireless Communications Research Dept., Bell Laboratories Rutgers, December, 2007 Need to greatly
More informationA REVIEW OF RESOURCE ALLOCATION TECHNIQUES FOR THROUGHPUT MAXIMIZATION IN DOWNLINK LTE
A REVIEW OF RESOURCE ALLOCATION TECHNIQUES FOR THROUGHPUT MAXIMIZATION IN DOWNLINK LTE 1 M.A. GADAM, 2 L. MAIJAMA A, 3 I.H. USMAN Department of Electrical/Electronic Engineering, Federal Polytechnic Bauchi,
More informationAnalysis and Improvements of Linear Multi-user user MIMO Precoding Techniques
1 Analysis and Improvements of Linear Multi-user user MIMO Precoding Techniques Bin Song and Martin Haardt Outline 2 Multi-user user MIMO System (main topic in phase I and phase II) critical problem Downlink
More informationScheduling Algorithm for Coordinated Beamforming in Heterogeneous Macro / Pico LTE-Advanced Networks
Scheduling Algorithm for Coordinated Beamforming in Heterogeneous Macro / Pico LTE-Advanced Networks Jakob Belschner, Daniel de Abreu, Joachim Habermann Veselin Rakocevic School of Engineering and Mathematical
More informationDecentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks
Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 1 Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks Antti Tölli with Praneeth Jayasinghe,
More informationGSM FREQUENCY PLANNING
GSM FREQUENCY PLANNING PROJECT NUMBER: PRJ070 BY NAME: MUTONGA JACKSON WAMBUA REG NO.: F17/2098/2004 SUPERVISOR: DR. CYRUS WEKESA EXAMINER: DR. MAURICE MANG OLI Introduction GSM is a cellular mobile network
More informationPerformance Studies on LTE Advanced in the Easy-C Project Andreas Weber, Alcatel Lucent Bell Labs
Performance Studies on LTE Advanced in the Easy-C Project 19.06.2008 Andreas Weber, Alcatel Lucent Bell Labs All Rights Reserved Alcatel-Lucent 2007 Agenda 1. Introduction 2. EASY C 3. LTE System Simulator
More informationOpen-Loop and Closed-Loop Uplink Power Control for LTE System
Open-Loop and Closed-Loop Uplink Power Control for LTE System by Huang Jing ID:5100309404 2013/06/22 Abstract-Uplink power control in Long Term Evolution consists of an open-loop scheme handled by the
More informationENERGY EFFICIENT WATER-FILLING ALGORITHM FOR MIMO- OFDMA CELLULAR SYSTEM
ENERGY EFFICIENT WATER-FILLING ALGORITHM FOR MIMO- OFDMA CELLULAR SYSTEM Hailu Belay Kassa, Dereje H.Mariam Addis Ababa University, Ethiopia Farzad Moazzami, Yacob Astatke Morgan State University Baltimore,
More informationOn the Optimum Power Allocation in the One-Side Interference Channel with Relay
2012 IEEE Wireless Communications and etworking Conference: Mobile and Wireless etworks On the Optimum Power Allocation in the One-Side Interference Channel with Relay Song Zhao, Zhimin Zeng, Tiankui Zhang
More informationClosed-loop MIMO performance with 8 Tx antennas
Closed-loop MIMO performance with 8 Tx antennas Document Number: IEEE C802.16m-08/623 Date Submitted: 2008-07-14 Source: Jerry Pi, Jay Tsai Voice: +1-972-761-7944, +1-972-761-7424 Samsung Telecommunications
More informationInterference Model for Cognitive Coexistence in Cellular Systems
Interference Model for Cognitive Coexistence in Cellular Systems Theodoros Kamakaris, Didem Kivanc-Tureli and Uf Tureli Wireless Network Security Center Stevens Institute of Technology Hoboken, NJ, USA
More informationDynamic Subcarrier, Bit and Power Allocation in OFDMA-Based Relay Networks
Dynamic Subcarrier, Bit and Power Allocation in OFDMA-Based Relay Networs Christian Müller*, Anja Klein*, Fran Wegner**, Martin Kuipers**, Bernhard Raaf** *Communications Engineering Lab, Technische Universität
More informationDownlink Erlang Capacity of Cellular OFDMA
Downlink Erlang Capacity of Cellular OFDMA Gauri Joshi, Harshad Maral, Abhay Karandikar Department of Electrical Engineering Indian Institute of Technology Bombay Powai, Mumbai, India 400076. Email: gaurijoshi@iitb.ac.in,
More informationDownlink Performance of Cell Edge User Using Cooperation Scheme in Wireless Cellular Network
Quest Journals Journal of Software Engineering and Simulation Volume1 ~ Issue1 (2013) pp: 07-12 ISSN(Online) :2321-3795 ISSN (Print):2321-3809 www.questjournals.org Research Paper Downlink Performance
More informationLTE System Level Performance in the Presence of CQI Feedback Uplink Delay and Mobility
LTE System Level Performance in the Presence of CQI Feedback Uplink Delay and Mobility Kamran Arshad Mobile and Wireless Communications Research Laboratory Department of Engineering Systems University
More informationThroughput Improvement for Cell-Edge Users Using Selective Cooperation in Cellular Networks
Throughput Improvement for Cell-Edge Users Using Selective Cooperation in Cellular Networks M. R. Ramesh Kumar S. Bhashyam D. Jalihal Sasken Communication Technologies,India. Department of Electrical Engineering,
More informationUL/DL Mode Selection and Transceiver Design for Dynamic TDD Systems
UL/DL Mode Selection and Transceiver Design for Dynamic TDD Systems 1 UL/DL Mode Selection and Transceiver Design for Dynamic TDD Systems Antti Tölli with Ganesh Venkatraman, Jarkko Kaleva and David Gesbert
More informationLTE-Advanced and Release 10
LTE-Advanced and Release 10 1. Carrier Aggregation 2. Enhanced Downlink MIMO 3. Enhanced Uplink MIMO 4. Relays 5. Release 11 and Beyond Release 10 enhances the capabilities of LTE, to make the technology
More informationDynamic Frequency Hopping in Cellular Fixed Relay Networks
Dynamic Frequency Hopping in Cellular Fixed Relay Networks Omer Mubarek, Halim Yanikomeroglu Broadband Communications & Wireless Systems Centre Carleton University, Ottawa, Canada {mubarek, halim}@sce.carleton.ca
More informationHybrid Compression and Message-Sharing Strategy for the Downlink Cloud Radio-Access Network
Hybrid Compression and Message-Sharing Strategy for the Downlink Cloud Radio-Access Network Pratik Patil and Wei Yu Department of Electrical and Computer Engineering University of Toronto, Toronto, Ontario
More informationOptimum Rate Allocation for Two-Class Services in CDMA Smart Antenna Systems
810 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 51, NO. 5, MAY 2003 Optimum Rate Allocation for Two-Class Services in CDMA Smart Antenna Systems Il-Min Kim, Member, IEEE, Hyung-Myung Kim, Senior Member,
More informationEvaluation of Adaptive and Non Adaptive LTE Fractional Frequency Reuse Mechanisms
Evaluation of Adaptive and Non Adaptive LTE Fractional Frequency Reuse Mechanisms Uttara Sawant Department of Computer Science and Engineering University of North Texas Denton, Texas 76207 Email:uttarasawant@my.unt.edu
More informationUniversity of Bristol - Explore Bristol Research. Peer reviewed version. Link to published version (if available): /VETECF.2010.
Han, C., Beh, K. C., Nicolaou, M., Armour, S. M. D., & Doufexi, A. (2010). Power efficient dynamic resource scheduling algorithms for LTE. In IEEE 72nd Vehicular Technology Conference Fall 2010 (VTC 2010-Fall),
More informationNew Cross-layer QoS-based Scheduling Algorithm in LTE System
New Cross-layer QoS-based Scheduling Algorithm in LTE System MOHAMED A. ABD EL- MOHAMED S. EL- MOHSEN M. TATAWY GAWAD MAHALLAWY Network Planning Dep. Network Planning Dep. Comm. & Electronics Dep. National
More informationLow complexity interference aware distributed resource allocation for multi-cell OFDMA cooperative relay networks
University of Wollongong Research Online Faculty of Informatics - Papers (Archive) Faculty of Engineering and Information Sciences 2010 Low complexity interference aware distributed resource allocation
More informationOptimal Resource Allocation in Multihop Relay-enhanced WiMAX Networks
Optimal Resource Allocation in Multihop Relay-enhanced WiMAX Networks Yongchul Kim and Mihail L. Sichitiu Department of Electrical and Computer Engineering North Carolina State University Email: yckim2@ncsu.edu
More informationBeamforming and Binary Power Based Resource Allocation Strategies for Cognitive Radio Networks
1 Beamforming and Binary Power Based Resource Allocation Strategies for Cognitive Radio Networks UWB Walter project Workshop, ETSI October 6th 2009, Sophia Antipolis A. Hayar EURÉCOM Institute, Mobile
More informationLoad Balancing for Centralized Wireless Networks
Load Balancing for Centralized Wireless Networks Hong Bong Kim and Adam Wolisz Telecommunication Networks Group Technische Universität Berlin Sekr FT5 Einsteinufer 5 0587 Berlin Germany Email: {hbkim,
More informationUser Grouping and Scheduling for Joint Spatial Division and Multiplexing in FDD Massive MIMO System
Int. J. Communications, Networ and System Sciences, 2017, 10, 176-185 http://www.scirp.org/journal/ijcns ISSN Online: 1913-3723 ISSN Print: 1913-3715 User rouping and Scheduling for Joint Spatial Division
More information(R1) each RRU. R3 each
26 Telfor Journal, Vol. 4, No. 1, 212. LTE Network Radio Planning Igor R. Maravićć and Aleksandar M. Nešković Abstract In this paper different ways of planning radio resources within an LTE network are
More informationInter-Cell Interference Coordination in Wireless Networks
Inter-Cell Interference Coordination in Wireless Networks PhD Defense, IRISA, Rennes, 2015 Mohamad Yassin University of Rennes 1, IRISA, France Saint Joseph University of Beirut, ESIB, Lebanon Institut
More informationBeamforming algorithm for physical layer security of multi user large scale antenna network
, pp.35-40 http://dx.doi.org/10.14257/astl.2016.134.06 Beamforming algorithm for physical layer security of multi user large scale antenna network Zhou Wen-gang, Li Jing, Guo Hui-ling (School of computer
More informationFull-Band CQI Feedback by Huffman Compression in 3GPP LTE Systems Onkar Dandekar
Full-and CQI Feedback by Huffman Compression in 3GPP LTE Systems Onkar Dandekar M. Tech (E&C) ASTRACT 3GPP LTE system exhibits a vital feature of Frequency Selective Scheduling(FSS). Frequency scheduling
More informationCell Load Based User Association For Tetra Trunk Systems
Cell Load Based User Association For Tetra Trunk Systems Azad Karataş 1, Berna Özbek 1, Erinç Deniz Bardak 2, İlker Sönmez 2 1 Izmir Institute of Technology, Electrical and Electronics Engineering Dept.,
More informationField Test of Uplink CoMP Joint Processing with C-RAN Testbed
212 7th International ICST Conference on Communications and Networking in China (CHINACOM) Field Test of Uplink CoMP Joint Processing with C-RAN Testbed Lei Li, Jinhua Liu, Kaihang Xiong, Peter Butovitsch
More informationMassive MIMO for the New Radio Overview and Performance
Massive MIMO for the New Radio Overview and Performance Dr. Amitabha Ghosh Nokia Bell Labs IEEE 5G Summit June 5 th, 2017 What is Massive MIMO ANTENNA ARRAYS large number (>>8) of controllable antennas
More informationDistributed Power Control in Cellular and Wireless Networks - A Comparative Study
Distributed Power Control in Cellular and Wireless Networks - A Comparative Study Vijay Raman, ECE, UIUC 1 Why power control? Interference in communication systems restrains system capacity In cellular
More informationCollege of Engineering
WiFi and WCDMA Network Design Robert Akl, D.Sc. College of Engineering Department of Computer Science and Engineering Outline WiFi Access point selection Traffic balancing Multi-Cell WCDMA with Multiple
More informationPerformance of CSI-based Multi-User MIMO for the LTE Downlink
Performance of CSI-based Multi-User MIMO for the LTE Downlink ABSTRACT Philipp Frank Deutsche Telekom Laboratories Ernst-Reuter-Platz 7 1587 Berlin, Germany philipp.frank@telekom.de We consider the application
More informationTransactions on Wireless Communication, Aug 2013
Transactions on Wireless Communication, Aug 2013 Mishfad S V Indian Institute of Science, Bangalore mishfad@gmail.com 7/9/2013 Mishfad S V (IISc) TWC, Aug 2013 7/9/2013 1 / 21 Downlink Base Station Cooperative
More informationEnergy Efficient Multiple Access Scheme for Multi-User System with Improved Gain
Volume 2, Issue 11, November-2015, pp. 739-743 ISSN (O): 2349-7084 International Journal of Computer Engineering In Research Trends Available online at: www.ijcert.org Energy Efficient Multiple Access
More informationModeling and Analysis of User-Centric and Disjoint Cooperation in Network MIMO Systems. Caiyi Zhu
Modeling and Analysis of User-Centric and Disjoint Cooperation in Network MIMO Systems by Caiyi Zhu A thesis submitted in conformity with the requirements for the degree of Master of Applied Science Graduate
More informationDownlink Scheduling in Long Term Evolution
From the SelectedWorks of Innovative Research Publications IRP India Summer June 1, 2015 Downlink Scheduling in Long Term Evolution Innovative Research Publications, IRP India, Innovative Research Publications
More informationCommon Feedback Channel for Multicast and Broadcast Services
Common Feedback Channel for Multicast and Broadcast Services Ray-Guang Cheng, Senior Member, IEEE, Yao-Yuan Liu, Wen-Yen Cheng, and Da-Rui Liu Department of Electronic Engineering National Taiwan University
More informationTechnical Aspects of LTE Part I: OFDM
Technical Aspects of LTE Part I: OFDM By Mohammad Movahhedian, Ph.D., MIET, MIEEE m.movahhedian@mci.ir ITU regional workshop on Long-Term Evolution 9-11 Dec. 2013 Outline Motivation for LTE LTE Network
More informationMillimeter-Wave Communication and Mobile Relaying in 5G Cellular Networks
Lectio praecursoria Millimeter-Wave Communication and Mobile Relaying in 5G Cellular Networks Author: Junquan Deng Supervisor: Prof. Olav Tirkkonen Department of Communications and Networking Opponent:
More informationISSN: (Online) Volume 2, Issue 6, June 2014 International Journal of Advance Research in Computer Science and Management Studies
ISSN: 2321-7782 (Online) Volume 2, Issue 6, June 2014 International Journal of Advance Research in Computer Science and Management Studies Research Article / Survey Paper / Case Study Available online
More informationThe final publication is available at IEEE via:
2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising
More informationCombined shared/dedicated resource allocation for Device-to-Device Communication
Combined shared/dedicated resource allocation for Device-to-Device Communication Pavel Mach, Zdene Becvar Dpt. of Telecommunication Eng., Faculty of Electrical Engineering, Czech Technical University in
More informationInvestigation on Multiple Antenna Transmission Techniques in Evolved UTRA. OFDM-Based Radio Access in Downlink. Features of Evolved UTRA and UTRAN
Evolved UTRA and UTRAN Investigation on Multiple Antenna Transmission Techniques in Evolved UTRA Evolved UTRA (E-UTRA) and UTRAN represent long-term evolution (LTE) of technology to maintain continuous
More informationOn Channel-Aware Frequency-Domain Scheduling With QoS Support for Uplink Transmission in LTE Systems
On Channel-Aware Frequency-Domain Scheduling With QoS Support for Uplink Transmission in LTE Systems Lung-Han Hsu and Hsi-Lu Chao Department of Computer Science National Chiao Tung University, Hsinchu,
More informationDYNAMIC POWER ALLOCATION SCHEME USING LOAD MATRIX TO CONTROL INTERFERENCE IN 4G MOBILE COMMUNICATION SYSTEMS
DYNAMIC POWER ALLOCATION SCHEME USING LOAD MATRIX TO CONTROL INTERFERENCE IN 4G MOBILE COMMUNICATION SYSTEMS Srinivas karedla 1, Dr. Ch. Santhi Rani 2 1 Assistant Professor, Department of Electronics and
More informationWINNER+ IMT-Advanced Evaluation Group
IEEE L802.16-10/0064 WINNER+ IMT-Advanced Evaluation Group Werner Mohr, Nokia-Siemens Networks Coordinator of WINNER+ project on behalf of WINNER+ http://projects.celtic-initiative.org/winner+/winner+
More informationAnalytical Evaluation of the Cell Spectral Efficiency of a Beamforming Enhanced IEEE m System
Analytical Evaluation of the Cell Spectral Efficiency of a Beamforming Enhanced IEEE 802.16m System Benedikt Wolz, Afroditi Kyrligkitsi Communication Networks (ComNets) Research Group Prof. Dr.-Ing. Bernhard
More information