VIET NAM NATIONAL UNIVERSITY, HA NOI UNIVERSITY OF ENGINEERING AND TECHNOLOGY PERFORMANCE ANALYSIS OF NETWORK-MIMO SYSTEMS A THESIS SUBMITTED IN FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF EECTRICAL ENGINEERING DUC-TUYEN TA 2010 Supervisor: Dr. Trinh Anh Vu i LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com ACKNOWLEDGMENTS First and foremost, I would like to express my gratitude to Dr. Trinh Anh Vu for being a great mentor and for numerous technical discussions and suggestions that have found their way into this thesis. I also very thank to all my colleagues at University of Engineering and Technology, VNU who have contributed greatly to provide a supportive and collaborative research atmosphere.
Many thanks to Phd. Tran Duc Tan and Dinh Van Phong, with whom I have had opportunities to collaborate on various subjects. I would like to sincerely thank my parents for their support, encouragement, and love throughout my life. This thesis is dedicated to them.
ii LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com ABSTRACT Network MIMO is a means of coordinating and processing the information gathered from multiple- input multiple- output (MIMO) communication systems to increase spectral efficiency, robustness, and data rates. These properties make it a topic of great interest in the near future as the number of wireless users continues to grow and their individual demands on bandwidth climb. Systems employing network MIMO capitalize on the fact that inter-cell interference, a major problem for dense wireless systems, is a superposition of signals. With careful coordination between receivers (and transmitters), these super-positions can be decoupled and the information they contain can be utilized.
The goal of this thesis is to investigate the ability of network MIMO techniques to increase data rates in multi-user indoor wireless networks of various sizes with various channel schemes. The simulation results also show that Network MIMO systems can be increase data rates and good through put than non- networked MIMO systems. iii LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com AUTHOR’S DECLARATION I declare that the work in this thesis was carried out in accordance with the Regulations of the University of Engineering and Technology, VNU. The work is original except where indicated by special reference in the text and no part of the thesis has been submitted for any other degree.
Any views expressed in the dissertation are those of the author and do not necessarily represent those of the University of Engineering, VNU. The thesis has not been presented to any other university for examination either in Viet Nam or overseas. Duc-Tuyen Ta 15 October 2010 iv LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com TABLE OF CONTENTS Page LIST OF TABLES. vii LIST OF FIGURES.
xi CHAPTER 1: INTRODUCTION .3 Network-MIMO systems. 5 CHAPTER 2: BASIC MIMO THEORY .1 MIMO systems Model .2 Theoretical MIMO Capacity Gains .3 Types of MIMO .3 Multi-user Communications .1 Limitations of Single-User view .2 Multi-User MIMO (MU-MIMO) .4 Multi-cell Communications .1 Limitations of Single-Cell View .2 Multi-Cell MIMO .1 Inter-cell Interference .2 Theory behind Network MIMO .3 Network-MIMO systems Model. 28 v LUAN VAN CHAT LUONG download : add luanvanchat@agmail. 30 CHAPTER 4: SIMULATION AND RESULTS.
46 vi LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com LIST OF TABLES Page Table 1 Power Delay Profile. 35 Table 2 Simulation parameters. 39 vii LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com LIST OF FIGURES Page Figure 1 MIMO communication from SISO to IA-MIMO (Source: www. 4 Figure 2 MIMO channel with M transmit and N receive antennas.
The sketched path, from transmitter and receiver, represent the channel which h11 is the channel between transmit antenna 1 and receive antenna 1. The transmit and receive signal are often presented by “black boxes”. 9 Figure 3 From single- to multiuser communications, where all the users in the coverage area are simultaneously considered in the optimization. The base station may choose to transmit data to a single or multiple user terminals at once.
14 Figure 4 Illustration of MU-MIMO: Downlink and Uplink. 15 Figure 5 MU-MIMO systems: MIMO Broadcast (Source: www. 16 Figure 6 MU-MIMO systems: MIMO MAC (Source: www. 17 Figure 7 Frequency reused in cellular network with the reuse factor is 3 and 7.
Cells of same color are used with same frequency. 18 Figure 8 From multi-user to multi cell communication, where all the cells and all the users in the network are simultaneously considered in optimization. The solid line marks the useful signals, where the interfering is dashed. 20 Figure 9 Coordination or Cooperation between all base stations in the wireless communication network under fast backhaul.
The central unit played an central network controller for control the coodination/cooperation between all the BS. 20 Figure 10 Illustration of typical interference between users and access points in a cell-based wireless system. The left image shows interference in down link and the right image shows interference in uplink. 22 viii LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Figure 11 Illustration of traditional interference control between users and access points in a cell-based wireless system.
The left image shows down link and the right image shows uplink. 23 Figure 12 Illustration of MIMO interference control between users and access points in a cell-based wireless system. The left image shows down link and the right image shows uplink. 24 Figure 13 Example of a small wireless communication with terminals, AP and the Central Network Controller.
25 Figure 14 Network MIMO solution where all the signals are useful, i., interference is removed. 25 Figure 15 Conventional vs. Network MIMO average SINR and data rate improvements. 26 Figure 16 Wireless network with two transmit and two receive antennas communicating through independent channels.
27 Figure 17 Network-MIMO uplink channel: from m-th cell to all of base station. 29 Figure 18 Network-MIMO downlink channel: from all base station to k-th user in the m-th cell. 31 Figure 19 Block Diagram showing key functions that are to be implemented in MATLAB simulation. 37 Figure 20 Simulation environment with 9 cell, each cell include 1 access point and 1 end-user with randomly place.
40 Figure 21 OFDM Pilot symbol to estimate the channel state information at both transmitter (AP/user) and receiver (user/AP) side with 3 users. 41 Figure 22 Compare between real channel and the estimated channel by using pilot symbol. 42 ix LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Figure 23 Channel estimation between 4-th AP and 1-st User (in the different cell) and the channel between 1-st AP and 1-st cell (in the same cell). 43 Figure 24 Comparison between performance of Network-MIMO and non Network-MIMO communication system with the ranger of Signal-to-Noise Ratio (SNR) is 10 to 20 dB.
43 x LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com ABBREVIATIONS 1G, 2G, 3G, 4G 1st to 4th generations of wireless (phone) networks BER Bit Error Rate CSCG Circularly Symmetric Complex Gaussian CSI Channel State Information CSIR Channel State Information at the Receiver CSIT Channel State Information at the Transmitter DPC Dirty Paper Coding GSM Global System for Mobile(originally: Groupe Spéciale Mobile) IEEE Institute of Electrical and Electronics Engineers LOS Line of Sight MIMO Multiple-Input Multiple-Output MISO Multiple-Input Single-Output MMSE Minimum Mean Square Error MU-MIMO Multiuser MIMO NLOS Non Line of Sight OFDM Orthogonal Frequency Division Multiplexing OSTBC Orthogonal Space Time Block Code PEP Pairwise Error Probability RF Radio Frequency SDMA Space Division Multiple Access SER Symbol Error Rate SIMO Single-Input Multiple-Output SINR Signal to Interference and Noise Ratio SNR Signal to Noise Ratio STBC Space Time Block Code xi LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com STC Space Time Code SU-MIMO Single-User MIMO WiMAX Worldwide Interoperability for Microwave Access WLAN Wireless Local Area Network ZF Zero-Forcing MSE Mean Square Error xii LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com CHAPTER 1: INTRODUCTION Modern wireless networks tend to be interference limited, mainly caused by their own base stations and mobile terminals. Suppressing interference would thus result in significant improvements in data rates, capacity, and coverage. Our studies determined the feasibility of achieving significant performance Network MIMO (Multiple-Input/Multiple-Output) gains. This led to a proposed solution to suppress inter-cell interference via phase- coherent coordination and joint spatial filtering between the base stations.1 Wireless Communication Wireless communication services are basic features of global civilization, soon available everywhere and adopted by everyone.
The development has been especially rapid in the last few decades, in which time wireless communications has taken a leap from being a niche technology towards achieving a status as an independent growth industry and diverse research area [1]. The history of wireless communication technologies can be traced back over 140 years, to Maxwell’s theories on electromagnetic waves and Hertz’ later demonstration of their existence [2]. Marconi’s 1896 invention of wireless telegraphy supplied the first useful application, enabling transatlantic communication services. Then followed radiotelephony, and commercial car phone services were spreading slowly from the late 1920s [3].
First generation (1G) personal mobile phone systems came in the early 1980s, with user terminals that were expensive and of questionable portability. However, the introduction of a cellular structure, for base station location and 1 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com frequency reuse, helped control the interference and made the networks more easily scalable, and the wireless revolution was ignited. The analog 1G networks were followed by the digital second generation (2G) systems, among which the GSM, first introduced for regular service in Finland in 1991, is one successful example. Third generation (3G) standards were released from 2000, aiming for unified global roaming, more users and higher data rates.
However, the actual deployment of networks was long delayed by enormous spectrum licensing fees and a lack of industry incentive. The fourth generation (4G) of wireless networks, also known as Beyond 3G, notably include implementations of the WiMAX and the Long-Term Evolution (LTE) standards [4]. For years, there is an on-going shift in end-user mobile communications service. The future of wireless communication is multimedia, which includes image, video, and local area network applications; with the data transmission rate more than 1000 times faster than that of the present systems.
However, the physical limits imposed by the mobile radio channel cause performance degradation and make it very difficult to achieve high bit rate at low error rate over the time dispersive wireless channels. Another key limitation is co-channel interference (CCI) which can also significantly decrease the capacity of wireless and personal communications systems.2 MIMO Techniques As presented in Section 1, future wireless communication networks will need to support extremely high data rates in order to meet the rapidly growing demand for broadband applications. Existing wireless communication technologies cannot 2 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com efficiently support broadband data rates, due to their sensitivity to fading. Multiple antennas have recently emerged as a key technology in wireless communication systems for increasing both data rates and system performance.
The benefits of exploiting Multiple-Input-Multiple-Output (MIMO) may be categorized by the following [6]: Array gain Array gain refers to the average increase in the SNR at the receiver that arises from the coherent combining effect of multiple antennas at the receiver or transmitter or both. The average increase in signal power at the receiver is proportional to the number of receive antennas. Diversity gain Signal power in a wireless channel fluctuates. When the signal power drops significantly, the channel is said to be in a fade.
Diversity is used in wireless channels to combat fading. Utilization of diversity in MIMO channels requires antenna diversity at both receive and transmit side. The diversity order is equal to the product of the number of transmit and receive antennas, if the channel between each transmit-receive antenna pair fades independently. Spatial multiplexing (SM) SM offers a linear (in the number of transmit-receive antenna pairs or min (Mt, Mr) increase in the transmission rate for the same bandwidth and with no additional power consumption.
Interference reduction Co-channel interference arises due to frequency reuse in wireless channels.