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07-06-2010, 08:27 PM

.docx   MIMO-OFDM-BASED AIR INTERFACE .docx (Size: 178.64 KB / Downloads: 235)




Orthogonal frequency-division multiplexing is a popular method for high-data-rate wireless transmission. OFDM may be combined with multiple antennas at both the access point and mobile terminal to increase diversity gain and/or enhance system capacity on a time-varying multipath fading channel, resulting in a multiple-input multiple-output OFDM system. OFDM has become a popular technique for transmission of signals over wireless channels. It converts a frequency-selective channel into a parallel collection of frequency flat subchannels, which makes the receiver simple. In this paper we gave a brief technical overview of MIMO-OFDM system design. The OFDM systems have high spectral efficiency, low receiver complexity, suitable for high-data-rate transmission over a multipath fading channel, high flexibility in terms of link adaptation, simple implementation by fast Fourier transform. Undoubtedly, OFDM could be a potential air interface candidate for future-generation mobile wireless systems.
Multiple antennas can be used at the transmitter and receiver, now widely termed a MIMO system.A MIMO system takes advantage of the spatial diversity obtained by spatially separated antennas in a dense multipath scattering environment. MIMO-OFDM key techniques influence air interface design, such as time selectivity, frequency selectivity,and spatial selectivity. In this paper MIMO-OFDM key techniques are introduced, MIMO-OFDM system design are also given. Our paper focused on MIMO OFDM-based air interface, including spatial channel modeling, MIMO-OFDM transceiver design, MIMO-OFDM channel estimation, space-time techniques for MIMO-OFDM and error correction code.


The first-generation (1G) radio systems use analog communication techniques to transmit voice over radio, such as Advanced Mobile Phone Services (AMPS) etc. The 2G systems featured the implementation of digital technology, such as Global System for Mobile Communications (GSM), Digital- AMPS (D- AMPS), code-division multiple access (CDMA) etc. Among them GSM is the most successful and widely used 2G system. 3G mobile technologies provide users with high-data-rate mobile access. The three major radio air interface standards for 3G are wideband CDMA (WCDMA), time-division synchronous CDMA (TD-SCDMA), and cdma2000. The transmitted data rate of 3G is up to 144 kb/s for high- mobility traffic, 384 kb/s for low- mobility traffic, and 2 Mb/s in good conditions. However, there are two limitations with 3G. One is the difficult extension to very high data rates such as 100 Mb/s with CDMA due to excessive interference between services. The other is the difficulty of providing a full range of multirate services, all with different quality of service (QoS) and performance requirements, due to the restrictions imposed on the core network by the air interference standard. Therefore, the future mobile communication system with features of highdata- rate transmission and open network architecture, called 4G, is desired to satisfy the increasing demand for broadband wireless access. Hence, 4G refers to a collection of technologies and standards that will find their way into a range of new ubiquitous computing and communication systems. The key objectives of 4G are to provide reliable transmission with high peak data rates ranging from 100 Mb/s for high mobility applications to 1 Gb/s for low-mobility applications, high spectrum efficiency up to 10 b/s/Hz.


OFDM has become a popular technique for transmission of signals over wireless channels.It converts a frequency selected channel into a parallel collection of frequency flat sub-channels, which makes the receiver simple. The time domain waveforms of the subcarriers are orthogonal, yet the signal spectra corresponding to thedifferent subcarriers overlap in frequency. Hence, the available bandwidth is used very efficiently.

Advantages of OFDM systems are:

High spectral efficiency
Simple implementation by fast Fourier transform (FFT)
Low receiver complexity
Suitability for high-data-rate transmission over a multipath fading channel
Low-complexity multiple access schemes such as orthogonal frequency- division multiple access (OFDMA)
Disadvantages of OFDM systems are:
Higher peak-to-average power ratio (PAPR) compared to single-carrier modulation
Sensitivity to time and frequency synchronization errors
Undoubtedly, OFDM could be a potential air interface candidate
for future-generation mobile wireless systems.

Multiple antennas can be used at the transmitter and receiver, now widely termed a MIMO system. A MIMO system takes advantage of the spatial diversity obtained by spatially separated antennas in a dense multipath scattering environment. MIMO systems may be implemented in a number of different ways to obtain either a diversity gain to combat signal fading or to obtain a capacity gain. There are three categories of MIMO techniques. The first one aims to improve the power efficiency by maximizing spatial diversity. The second type uses a layered approach to increase capacity The third type exploits knowledge of the channel at the transmitter. It decomposes the channel matrix usingsingular value decomposition (SVD) and uses these decomposed unitary matrices as pre- and post-filters at the transmitter and receiver to achieve capacity gain. MIMO may be implemented in the high-speed downlink packet access (HSDPA) channel, which is a part of the Universal Mobile Telecommunications System (UMTS) standard.


MIMO is known to boost capacity. For highdata-rate transmission, the multipath characteristic of the environment causes the MIMO channel to be frequency-selective. OFDM can transform such a frequency-selective MIMO channel into a set of parallel frequency- flat MIMO channels, and therefore decrease receiver complexity. The combination of the two powerful techniques, MIMO and OFDM, is very attractive, and has become a most promising broadband wireless access scheme.


This section briefly describes the key channel characteristics that influence air interface design, such as time selectivity, frequency selectivity, and spatial selectivity. Time Selectivity A signal experiences slow or time- nonselective fading if its symbol period is much smaller than the channel coherence time, and fast or time- selective fading if its symbol period is more than the coherence time. Frequency Selectivity A signal experiences flat or frequency- nonselective fading if its bandwidth is much smaller than the channel coherence bandwidth, and frequency-selective fading if its bandwidth is more than the channel coherence bandwidth. Spatial Selectivity ” When using multiple-element antennas, the coherence distance represents the minimum distance in space separating two antenna elements such that they experience independent fading. Due to scattering environments, the channel exhibits independent or spatially selective fading.
K-Factor T he ratio of the line-ofsight (LOS) component power to the diffraction component power is defined as the Ricean k- factor.The worst case fading occurs when the power of the LOS component is zero.
Transmitter ” Figure shows a simplified block diagram of a MIMO -OFDM transmitter. The source bitstream is encoded by a forward error correction (FEC) encoder. After that, the coded bitstream is mapped to a constellation by the digital modulator, and encoded by a MIMO encoder. Then each of the parallel output symbol streams corresponding to a certain transmit antenna follows the same transmission process. First, pilot symbols are inserted according to the pilot patterns. Then the symbol sequence in frequency is modulated by inverse FFT (IFFT) to an OFDM symbol sequence. A cycle prefix (CP) is attached to every OFDM symbol to mitigate the effect of channel delay spread, and a preamble is inserted in every slot for timing. Finally, the constructed data frame is transferred to IF/RF components for transmission.
Receiver Figure shows a simplified block diagram of a MIMO-OFDM receiver. The received symbol stream from IF/RF components over the receive antennas are first synchronized, including coarse frequency synchronization and timing aided by the preamble. After that, the preambles and CP are extracted from the received symbol stream, and the remaining OFDM symbol is demodulated by The refined frequency pilots from all the receive antennas are used for channel estimation (CE). The estimated channel matrix aids the MIMO decoder in decoding the refinedOFDM symbols. The estimated transmit symbols are then demodulated and decoded. Finally, the decoded source bitstreams are transmitted to the sink.
Frame Structure ” Figure 3 shows an example for the frame format of the MIMO-OFDM system. In the time domain, a frame is a minimum transmission unit that includes 10 slots. Each slot consists of one slot preamble and eight OFDM symbols. The preamble is used for time synchronization. Each OFDM in a slot is attached to a CP that is used to reduce ISI, and therefore the design of channel equalizer is simplified.

CE MIMO-OFDM is a promising scheme for achieving high data rates and large system capacity over wireless links. To obtain the promised increase in data rate, accurate channel state information is required in the receiver. However, for OFDM systems with multiple transmit antennas, different signals are transmitted from different antennas simultaneously,and consequently, the received signal is the superposition of these signals, which gives rise to challenges for CE. CE algorithms for MIMO-OFDM system, based on scattered pilots is discussed below.
Pilot Pattern ” The scattered pilot pattern of transmit antennas is designed as follows. Pilot spacing in the frequency domain should be designed such that the following inequality is satisfied, which is required by the MIMO-OFDM CE algorithm described here:
(FFT Size)/(PSF.M)>(Maximum Delay) where PSF denotes the pilot spacing in the frequency domain, and Maximum Delay is the maximum excess delay of the multipath channels between transmitter and receiver in units of sampling time.


Current space-time processing techniques forMIMO typically fall into two categories, data rate maximization and diversity maximization schemes. Spatial Multiplexing ” Spatial multiplexing multiplexes multiple spatial channels to send as many independent data as we can over different antennas for a specific error rate. There are four spatial multiplexing schemes: diagonal BLAST, horizontal BLAST, V-BLAST, and turbo BLAST. Of them, V-BLAST is the most promising for its implementation simplicity.
The method to detect the transmitted signals consists of three main steps:
1). Estimate the channel matrix. This is often done through training sequence
2). Determinate the optimal detecting order and the nulling vectors
3). Detect the received signals based on the optimal detecting order and successive interference cancellation.
Zero-forced (ZF) or minimum mean square error (MMSE) nulling: ZF or MMSE estimation of the strongest transmit signal is obtained via nulling out the weaker transmit signals.
Detecting: The actual value of the strongest signal is detected by slicing to the nearest value in the signal constellations.
Symbol interference cancellation: The effect of the strongest transmitted signal on the other weaker transmitted signal to be detected is removed from the vector of the received signals. Since the spatial multiplexing detector uses some form of channel matrix inversion, a unique solution is only possible if the number of receive antennas is greater than or equal to the number of independent transmit signals. Moreover, spatial multiplexing has poor detection performance over a spatially correlated channel.

Space-Time Coding Space-time coding jointly encodes the data streams over different antennas, and therefore aims to maximize diversity gain. Two main space-time coding schemes, STBC andSTTC . STBC based on orthogonal design obtains full diversity gain with low decoding complexity, and therefore has been widely used. Between SFBC and STBC, one is selected based on the selectivity of the channel in the time or frequency domain. Whatever the delay spread of the channel, STBC is chosen only if the channel is slowly varying in the time domain when theterminal moves slowly. SFBC is chosen only if the channel is slowly varying in the frequency domain when the delay spread of the channel is small.
Comparisons of STC and Spatial Multiplexing Data rate: SFBC/STBC is only suitable for low-data-rate service. Here, low data rate is just relative to the very high data rate achieved by spatial multiplexing. Thus, in order to achieve very high bandwidth efficiency up to the future 10 b/s/Hz, spatial multiplexing is a better choice. Diversity gain: If a system is designed to achieve better QoS for average data rate, STBC/SFBC is a better choice.
Spatially correlated channel: Over a weak spatially correlated channel, both SFBC/STBC and spatial multiplexing can work well. Over a spatially correlated channel, STBC/SFBC is preferred because spatial correlation leads to much less performance degradation for STBC/SFBC than spatial multiplexing. Frequency-selective channel: Spatial multiplexing and STBC can work well in a frequencyselective channel at low mobility. At high mobility, only MIMO spatial multiplexing or SFBC can work well. Fading channel: Both spatial multiplexing and SFBC can work well in a fast fading channel only if the channel is not frequency-selective. Over a frequency-selective channel, spatial multiplexing is better.
Channel estimation technique: SFBC/STBC is not as sensitive to channel estimation error as spatial multiplexing.
Antenna configuration: For a configuration with more than two transmit antennas, either two of the transmit antennas are chosen for SFBC/STBC, or spatial multiplexing is used.


Time-varying wireless channel conditions and therefore time- varying system capacity are two important features of wireless and mobile communication systems. Accordingly, future systems should have a high degree of adaptivity on many levels in order to achieve desired performance.Examples of such adaptivity are information rate adaption, power control, code adaptation, bandwidth adaptation, antenna adaptation The principle of AMC is to change the modulation and coding format in accordance with instantaneous fluctuation in channel conditions, subject to system restrictions. Channel conditions should be estimated based on feedback from the receiver. For a system with AMC, users close to the cell site are typically assigned higher- order modulation with higher code rates. On the other hand, users close to the cell boundary are assigned lower-order modulation with lower code rates. The implementation of AMC offers several challenges. First, AMC is sensitive to channel measurement error and delay. In order to select appropriate modulation schemes, the scheduler must be aware of the channel quality. Errors in the channel estimate will cause the scheduler to select the wrong data rate, and transmit at either too high power, wasting system capacity, or too low power, raising the block error rate. Delay in reporting channel measurements also reduces the reliability of the channel quality estimate.
Furthermore, changes in interference also increase measurement errors. One objective of AMC is to greatly improve the MIMO channel capacity with the help of turbo-like codes.


For a traditional OFDM communication system,the frequency offset caused by oscillator inaccuracies results in ICI that degrades the BER performance of the system greatly. Although frequency synchronization is used, the residential frequency offset causes a number of impairments including attenuationand rotation of each of the subcarriers and ICI between subcarriers. Similarly, MIMO-OFDM is also sensitive to carrier frequency offset that destroy orthogonality of subcarriers and give rise to ICI. PAPR The main limitation of OFDM-based transmission systems is the high PAPR of the transmitted signals, and large peaks will occasionally reach the amplifier saturation region and result in signal distortion.


In this paper, MIMO-OFDM key techniques are introduced. Some of our considerations in MIMO-OFDM system design are also given, focusing on frame structure, CE, and comparisons of STC and spatial multiplexing. The proposed frame structure with scattered pilots is especially suited for high-data-rate transmission at high mobility. Based on comparisons of STC nd spatial multiplexing, qualitative criteria in terms of data rate, application environment, and antenna configuration are proposed to chooseSTC or spatial multiplexing. The high bandwidth efficiency obtained shows that MIMO-OFDM is a potential candidate for future broadband wireless access.


[1] V. Tarokh, H. Jafarkhani, and A. R. Calderbank, Space-Time
Block Codes from Orthogonal Designs, IEEE Trans. Info.
Theory, vol. 45, no. 5, Jul 1999, pp. 1456“67.
[2] Y. Li, Simplified Channel Estimation for OFDM Systems
with Multiple Transmit Antennas, IEEE Trans. Wireless
Commun., vol. 1, no. 1, Jan. 2002, pp. 67“75.
[3]Some Other IEEE Journals


MIMO-OFDM Key Techniques
The Spatial Channel Model
Time Selectivity
Frequency Selectivity
Spatial Selectivity
MIMO-OFDM System Model
Frame Structure
Space Time Processing Techniques for MIMO
Spatial Multiplexing
Space-Time Coding
Comparisons of STC and Spatial Multiplexing
Adaptive Modulation and Coding
Intercarrier Interference Cancellation
Peak to Average Power Ratio (PAPR)

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28-09-2010, 10:04 AM

plz send me the full report asap....
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30-12-2011, 09:13 AM

plz send ppt on mimo-ofdm-based air interface
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30-03-2012, 05:22 PM

i need ppt for multiple input multiple output(MIMO) a future wireless communication technology
seminar paper
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31-03-2012, 10:50 AM

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