Performance Analysis of Network-MIMO Systems Tạ Đức Tuyển Trường Đại học Công nghệ Luận văn ThS ngành: Kỹ thuật Điện tử - Viễn thông; Mã số: 60 52 70 Người hướng dẫn: TS. Trịnh Anh Vũ Năm bảo vệ: 2010
Performance Analysis of Network-MIMO Systems Tạ Đức Tuyển Trường Đại học Công nghệ Luận văn ThS ngành: Kỹ thuật Điện tử - Viễn thông; Mã số: 60 52 70 Người hướng dẫn: TS Trịnh Anh Vũ Năm bảo vệ: 2010 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 nonnetworked MIMO systems Keywords: Kỹ thuật điện tử; Mạng Mimo; Xử lý thông tin; Mạng truyền thông Content 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 1.1 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 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 1.2 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 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 (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 When multiple antennas are used, the difference between the spatial signatures of the desired signal and co-channel signals can be exploited to reduce the interference This operation is done at the receiver side Figure MIMO communication from SISO to IA-MIMO (Source: www.wikipedia.org) In addition, we will increase system performance or reduce cost by apply some enhancement techniques to MIMO communication systems These can be categorized into two groups: evolutionary and revolutionary approaches Evolutionary approaches: Use an existing techniques with enhanced PHY capabilities, perhaps a 16×16 array configuration Use new MIMO algorithms such as pre-coding or multi-user scheduling at the transmitter Revolutionary approaches: developing the fundamentally of new MIMO concepts Based on the literature, we summarize a number of advanced MIMO techniques that leverage multiple users as seen in Fig 1: Cross-layer MIMO: Scheduling, etc Advanced decoding MIMO: Multi-user detection such as MLD Beamforming and SDMA: widely known multi-user MIMO (MU-MIMO) scheme Infrared/Non-infrared network optimization Network MIMO (Net-MIMO) Cognitive MIMO based on intelligent techniques Cooperative/competitive MIMO Cooperation: DPC, Wyner-Ziv, etc Competitive: Game theory, autonomous packets, implicit MAC fairness etc 1.3 Network-MIMO systems Network MIMO is a MIMO communication scheme, which falls within the family of techniques that use cooperation in a MIMO systems to increase system performance More specifically, network MIMO is a family of techniques whereby each end user in a wireless access network is served not just by multiple antennas but also by multiple access points [8] This allows users similar performance increases to those seen in other MIMO processing methods but achieves it by taking advantage of the already existing infrastructure in any multi-point access network For example, an indoor wireless system for a small business would have several access points (AP) These access points would all be connected through a wired grid to a central router and then to the internet via an ISP Taking advantage of the fact, these access points are all connected, network MIMO could be used to coordinate the transmission and reception of data without needing to add additional antennas to local access points 1.4 Thesis’s Structure In general terms, this thesis focuses on performance analysis of network MIMO systems Because Network-MIMO is an enhancement model of the original MIMO systems, we first analysis the theoretical of MIMO techniques in Chapter That is the basic knowledge to work with Network-MIMO in the next chapters In Chapter 3, we consider a Network-MIMO systems where two or more AP served each end-user to achieve high system performance while also reduces the system interference Chapter presented the simulation model and simulation results of a Network MIMO systems using Matlab The model simulates an indoor wireless access system with multiple Access Point (AP) and multiple End-User For simplicity, we assumed that the MIMO link is created only by the way of multiple wireless access The simulation results show that Network MIMO systems can be archive high system performance than the non Network-MIMO systems Finally, we have some conclusion and discussion about Network-MIMO systems in Chapter CHAPTER 2: BASIC MIMO THEORY Future wireless communication networks will need to support extremely high data rates in order to meet the rapidly growing demand for broadband applications such as high quality audio and video Existing wireless communication technologies cannot efficiently support broadband data rates, due to their sensitivity to fading Multiple-input multiple-output (MIMO) is a key technique for increasing both data rates and system performance It can increase data throughput and link range without bandwidth or transmit power expansion 2.1 Wireless Background A simple wireless communication system consists of a transmitter and a receiver, both equipped with a single antenna, transmitting information-carrying electromagnetic waves over space The transmit antenna provides the input to the wireless channel, and the output is picked up by the receive antenna, thus, forming a Single-Input Single-Output (SISO) system In this thesis, communications is assumed to take place between a stationary access point (AP) or base station (BS) and a mobile user terminal (MS) The BS transmits data to the user terminal on the downlink, while the reverse direction is the uplink With a multiple base stations network, these are often assumed to be connected by a wired or wireless backbone network, offering highrate inter-base communications The wireless communications medium is space, and so a system’s characteristics are highly dependent on the local propagation environments formed by natural and manmade structures, such as mountains, foliage, buildings, and large vehicles Flat and rural areas offer free space conditions, under which a transmitted signal will reach the destination only via the direct Line-Of-Sight (LOS) path Non Line-Of-Sight (NLOS) conditions occur when the direct path is blocked, which is common in cities and suburban areas, but which may also be caused by a countryside hill Propagation over space is additive in nature, which makes wireless communications susceptible to crosstalk between same-frequency signals, so called co-channel interference (CCI) If the desired and the interfering signal are received with comparable powers, the desired signal may well be impossible to retrieve from the new, sum signal 2.2 MIMO Communications In wireless communication, multiple input multiple output (MIMO) technology is the use of multiple antennas in both transmitter and receiver It has attracted attention in modern wireless communications, because it offers significant increases in data throughput and link range without additional bandwidth or transmit power by higher spectral efficiency (more bits per second per hertz of bandwidth) and link reliability or diversity (reduced fading) Because of these properties, MIMO is an important part of modern wireless communication standards such as IEEE 802.11n, 3GPP Long Term Evolution (LTE), 4G, and WiMax Figure 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 and receive antenna The transmit and receive signal are often presented by “black boxes” 2.2.1 MIMO systems Model We consider a MIMO systems with a transmit array of MT antennas and a receive array of MR antennas The block diagram of such a system is shown in the Fig The transmitted matrix is an [M, 1] column matrix S where Si is the 𝑖 𝑡 component, transmitted from antenna i, and of the form: 𝑇 𝑆 = 𝑆1 , 𝑆2 , … , 𝑆𝑀 Where ( ) T denotes the transpose matrix For simplicity, we consider the channel is a Gaussian channel such that the elements of S are considered to independent identically distributed (i.i.d) variables Assume that the channel state information (CSI) is known at receiver but unknown at the transmitter side and the signals transmitted from each antenna have equal powers of Es/M with Es is the power of transmitted signal The channel matrix can be given by: 11 12 𝐻 = 21 22 ⋮ 1𝑀 𝑀2 … ⋯ ⋱ ⋯ 1𝑁 2𝑁 ⋮ 𝑀𝑁 The noise at the receiver is another column matrix of size [N, 1], denoted by w: 𝑤 = 𝑤1 , 𝑤2 , … , 𝑤𝑁 𝑇 So the receiver vector is [N, 1] vector that satisfied: 𝑅 [𝑚] = 𝐻 𝑆[𝑚] + 𝑤[𝑚] Where m is a real number from to N [2-1] ... thesis focuses on performance analysis of network MIMO systems Because Network-MIMO is an enhancement model of the original MIMO systems, we first analysis the theoretical of MIMO techniques... signal are often presented by “black boxes” 2.2.1 MIMO systems Model We consider a MIMO systems with a transmit array of MT antennas and a receive array of MR antennas The block diagram of such... reasons for this performance gap include the presence of co-channel interference (CCI), diminishing the effect of MIMO communications, and the limited number of degrees of freedom offered for inter-cell