Overview Of Signal Processing For Wireless Communication Computer Science Essay

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In this era of communication, the growing demand of multimedia services and the growth of Internet related contents lead to increasing interest to high speed communications. In wireless communications, spectrum is a scarce resource and hence imposes a high cost on the high data rate transmission. It has been demonstrated that multiple antenna system provides very promising gain in capacity without increasing the use of spectrum, reliability, throughput, power consumption and less sensitivity to fading, hence leading to a breakthrough in the data rate of wireless communication systems.

There are three basic parameters that completely describe the quality and usefulness of any wireless link: speed, range and reliability. Prior to the development of MIMO-OFDM, Speed could be increased only by sacrificing range and reliability. Range could be extended at the expense of speed and reliability. And reliability could be improved by reducing speed and range. MIMO-OFDM has redefined the tradeoffs, clearly demonstrating that it can boost all three parameters simultaneously.

In wireless environment the multipath signals' power drop off due to three effects: path loss, macroscopic fading and microscopic fading. Fading of the signal can be mitigated by different diversity techniques. To obtain diversity, the signal is transmitted through multiple (ideally) independent fading paths e.g. in time, frequency or space and combined constructively at the receiver. MIMO exploits spatial diversity by having several transmit and receive antennas.

So, this proposal explains how the MIMO improve the performance of wireless LAN by taking the advantages of random fading and multipath delay spread. Actually, the ability to turn multipath propagation, which conventionally is considered as a drawback of wireless transmission, into a benefit for the user is the key feature of MIMO systems. So, multiple-input multiple-output (MIMO) system has become one of the major focuses in the research community of wireless communications and information theory.

Finally, this research project will couple the MIMO with a robust and efficient OFDM air interface and hence will lead to a very compelling high-speed data link solution for future wireless systems.

Introduction

A wireless local area network (LAN) is a flexible data communications system enabling multiple computer users to simultaneously share resources in a home or business without additional or intrusive wiring. These resources might include a broadband Internet connection, network printers, data files, and even streaming audio and video. Using radio frequency (RF) technology, wireless LANs transmit and receive data over the air, minimizing the need for wired connections. Thus, wireless LANs combine data connectivity with user mobility.

Because of the mobility, simplicity, flexibility and scalability, Wireless LAN is highly popular than traditional wired networks. Products based on existing wireless LAN standards often fail to meet the range requirements encountered in homes, small businesses, retail stores, and other business locations. Existing wireless LAN standards also lack the throughput levels required by emerging and potentially huge applications such as home entertainment etc. Due to these difficulties with existing wireless LAN, we introduce a new technology to wireless LAN (IEEE802.11n) in which the capacity of a wireless LAN can easily be shared between multiple users and applications. MIMO and OFDM technologies (MIMO-OFDM) may be the foundation of all proposals for the IEEE 802.11n standard.

2.a IEEE Wireless Networking Specifications

802.11 Specifications: The 802.11 specifications were developed specifically for Wireless Local Area Networks (WLANs) by the IEEE, provides 1 or 2 Mbps transmission in the 2.4 GHz band using either frequency hopping spread spectrum (FHSS) or direct sequence spread spectrum (DSSS). Include four subsets of Ethernet-based protocol standards: 802.11a, 802.11b, and 802.11g, 802.11n.

ï‚· 802.11a - an extension to 802.11 that applies to wireless LANs and provides up to 54 Mbps in the 5GHz band. 802.11a uses an orthogonal frequency division multiplexing (OFDM) encoding scheme rather than FHSS or DSSS. The 802.11a specification applies to wireless ATM systems and is used in access hubs.

ï‚· 802.11b ( 802.11 High Rate or Wi-Fi) - an extension to 802.11 that applies to wireless LANS and provides 11 Mbps transmission (with a fallback to 5.5, 2 and 1 Mbps) in the 2.4 GHz band. 802.11b uses only DSSS. 802.11b was ratification to the original 802.11 standard, allowing wireless functionality comparable to Ethernet.

ï‚· 802.11g - offers wireless transmission over relatively short distances at 20 - 54 Mbps in the 2.4 GHz band. The 802.11g also uses the OFDM encoding scheme.

ï‚· 802.11n - builds upon previous 802.11 standards by adding MIMO (multiple-input multiple-output). IEEE 802.11n offers high throughput wireless transmission at 100Mbps - 200 Mbps.

MIMO can greatly increase the spectral efficiency (capacity) over a limited bandwidth. Since it has additional dimension to carry information, the capacity gain of MIMO systems over the single input single output (SISO) system is a remedy to the fast increasing demands of higher data rates in wireless communications.

If the channel transfer matrix is fixed and both known to the transmitter/receiver, through some clever joint processing, we can achieve the capacity of this type of channel. In the fading environment, under the assumption of independent fades and noises at the different antennas, the capacity gain of multi-antenna systems over single-antenna systems can be very large.

MIMO systems can be used for different purposes including diversity, spatial multiplexing and interference reduction. It has been demonstrated that multiple antenna system provides very promising gain in capacity without increasing the use of spectrum, reliability, throughput, power consumption and less sensitivity to fading, hence leading to a breakthrough in the data rate of wireless communication systems.

Motivation to MIMO

Existing networks are capacity constrained networks.

Issues related to quality and coverage must handle.

MIMO exploits the space dimension to improve wireless systems capacity, range and reliability.

MIMO-OFDM - the corner stone of future broadband wireless access.

- WiFi - 802.11n

- WiMAX - 802.16e (802.16-2005)

- 3G / 4G

Problem statement

Traditional radio systems either do nothing to combat multipath interference, relying on the primary signal to out-muscle interfering copies, or they employ multipath mitigation techniques. One mitigation technique uses multiple antennas to capture the strongest signal at each moment in time. Another technique adds different delays to received signals to force the peaks and troughs back into alignment. Whatever the mitigation technique, all assume multipath signals are wasteful and/or harmful and strive to limit the damage.

MIMO, in contrast, takes advantage of multipath propagation to increase throughput, range/coverage, and reliability. Rather than combating multipath signals, MIMO puts multipath signals to work carrying more information. This is accomplished by sending and receiving more than one data signal in the same radio channel at the same time. The use of multiple waveforms constitutes a new type of radio communication-communication using multi-dimensional signals-which is the only way known to improve all three basic link performance parameters (range, speed and reliability).

TIPLE-ANTENNA SYSTEMS

4.a MIMO vs. SIMO/MISO (Linear vs. Logarithmic)

Figure 2 Modification of Shannon's Channel Capacity Theorem.

Regarding to above figure 2, if we achieve the linear relationships between channel capacity and SNR, we can significantly improve the speed of wireless communication without compromising on other factors (quality and range). This is possible only with MIMO technology.

Because MIMO transmits multiple signals across the communications channel (rather than the conventional system's single signal), MIMO has the ability to multiply capacity (which is another word for "speed"). A common measure of wireless capacity is spectral efficiency-the number of units of information per unit of time per unit of bandwidth-usually denoted in bits per second per Hertz, or b/s/Hz. Using conventional radio technology, engineers struggle to increase spectral efficiency incrementally (i.e. one b/s/Hz at a time). By transmitting multiple signals containing different information streams over the same frequency channel, MIMO provides a means of doubling or tripling spectral efficiency.

MIMO can also be thought of as a multi-dimensional wireless communications system. Conventional radio systems try to squeeze as much information as possible through a one-dimensional pipe. In order to do that, engineers must adapt their designs to the noise and other limitations of a one-dimensional channel. MIMO empowers engineers to work in multiple dimensions, creating opportunities to work around the limitations of a one-dimensional channel.

Greater spectral efficiency translates into higher data rates, greater range, and an increased number of users, enhanced reliability, or any combination of the preceding factors. By multiplying spectral efficiency, MIMO opens the door to a variety of new applications and enables more cost-effective implementation for existing applications.

An interesting sidelight: Guglielmo Marconi demonstrated the first non line-of-sight (NLOS) wireless communications system in 1896 by communicating over a hill. From that day forward, engineers viewed multipath signals as an annoyance at best and serious problem at worst. The first paper describing wireless MIMO's capacity multiplying capability was published 100 years later in the 1996 Global Communications Conference proceedings.

On the downlink, MIMO exploits multiple antennas at both the base station transmitter and the user terminal receiver. In the transmitter, the high speed data stream intended for the user is encoded in time and space across multiple transmit antennas. In doing so, the same carrier (or spectral resource) is reused at each antenna. Signal processing is then used to decode the composite signals received at the mobile user's terminal. The spatial antenna processing at the terminal is able to unravel the effects of complex multipath scattering, and fundamentally provides access to parallel independent propagation paths between the base station and the user. Thus, instead of having access to a single data pipe, as with conventional wireless system design, a wireless system exploiting MIMO technology is able to capitalize on the presence of multiple parallel pipes, improving both the data rate and system capacity. MIMO has now reached a certain maturity, and is being investigated in the Third Generation Partnership Projects (3GPP and 3GPP2) for the evolution of the Universal Mobile Telecommunications System (UMTS) and cdma2000 systems, respectively.

Figure 3 MIMO uses multiple transmitters, receivers and antennas to send multiple signals over the same channel, multiplying spectral efficiency.

4. b How MIMO Works?

MIMO takes advantage of multi-path.

• MIMO uses multiple antennas to send multiple parallel signals (from transmitter).

• In an urban environment, these signals will bounce off trees, buildings, etc. and continue on their way to their destination (the receiver) but in different directions.

• "Multi-path" occurs when the different signals arrive at the receiver at various times.

• With MIMO, the receiving end uses an algorithm or special signal processing to sort out the multiple signals to produce one signal that has the originally transmitted data.

Multiple data streams transmitted in a single channel at the same time, multiple radios collect multipath signals and delivers simultaneous speed, coverage, and reliability improvements.

Each multipath route is treated as a separate channel, creating many "virtual wires" over which to transmit signals. Traditional radios are confused by this multipath, while MIMO takes advantage of these "echoes" to increase range and Throughput.

4. c MIMO Channel Matrix

Figure 4 the block diagram of MIMO system.

Example for 3 X 3 systems:

If { x1, x2 , x3} be the streams of transmitted signals from the transmitter antennas and{ b1, b2, b3} be the corresponding received signals by the receiver antennas, then the received signals can be expressed as

Where, hij are complex numbers.

The matrix H is called the Channel matrix and the matrix elements are complex numbers comprising of the amplitude, phase and frequencies. And the noise I consider here is Raleigh fading and AWGN Channels, others may also be considering while simulating in MATLAB. By taking the Fourier Transform of the transmitted and received signals streams, we can plot the PSD of MIMO signals using MATLAB.

So if the Channel Matrix (H) is invertible, we can approximate the transmitted signals by taking H-1 as shown below.

What next when the matrix H is singular and ill condition will occur?

In the case of LOS (Line of Side) Communication, the channel matrix will be non invertible

The system is near rank one (non invertible), and hence the spatial multiplexing requires multipath to work i.e. in MIMO the multipath is necessary.

4. d OFDM (Orthogonal Frequency Division Multiplexing)

OFDM is becoming a very popular multi-carrier modulation technique for transmission of signals over wireless channels. It converts a frequency-selective fading channel into a collection of parallel at fading sub channels, which greatly simplifies the structure of the receiver. The time domain waveform of the subcarriers are orthogonal (sub channel and subcarrier will be used interchangeably hereinafter), yet the signal spectral corresponding to different subcarriers overlap in frequency domain. Hence, the available bandwidth is utilized very efficiently in OFDM systems without causing the ICI (inter-carrier interference). By combining multiple low-data-rate subcarriers, OFDM systems can provide a composite high-data-rate with a long symbol

duration. That helps to eliminate the ISI (inter-symbol interference), which often occurs along with signals of a short symbol duration in a multipath channel. Simply speaking, we can list its pros and cons as follows.

Advantage of OFDM systems are:

High spectral efficiency;

Simple implementation by FFT Algorithms;

Low receiver complexity;

Robustability for high-data-rate transmission over multipath fading channel and

High flexibility in terms of link adaptation;

This is due to the fact that the transmit power of the mobile station is concentrated in a small portion of the channel bandwidth and the signal-to-noise ratio (SNR) at the receiver input is increased. Cell range extension is also achievable on the downlink (from base station to mobile stations) by allocating more power to carrier groups assigned to distant users. Another interesting feature of OFDMA is that it eases the deployment of networks with a frequency reuse factor of 1, thus eliminating the need for frequency planning.

The Wireless World Research Forum (WWRF) considers OFDM the most important technology for a future public cellular radio access technology [3]. Several wireless networking (e.g., IEEE 802.11 and 802.16) and wireless broadcasting systems (e.g. DVB-T, DAB) have already been developed using OFDM technology and are now available in mature commercial products.

Since data is multiplexed on many narrowband subcarriers, OFDM is very robust to typical multipath fading (i.e., frequency-selective) channels. Furthermore, the subcarriers can easily be generated at the transmitter and recovered at the receiver, using highly efficient digital signal processing based on fast Fourier transform (FFT).

Why MIMO-OFDM?

OFDM is also a wideband system, but unlike CDMA which spreads the signal continuously over the entire channel, OFDM employs multiple, discrete, lower data rate sub channels.

MIMO can be used with any modulation or access technique. However, research shows that implementation is much simpler-particularly at high data rates-for MIMO-OFDM. Specifically, MIMO-OFDM signals can be processed using relatively straightforward matrix algebra.

Previous Studied

The concept of MIMO was begun in the late 19's. The earliest ideas in this field go back to work by A.R. Kaye and D.A. George (1970) and W. van Etten (1975, 1976). Jack Winters and Jack Salz at Bell Laboratories published several papers on beamforming related applications in 1984 and 1986. After that revolutionary concept in Wireless communication, various scientists were involved in this field. Arogyaswami Paulraj and Thomas Kailath proposed the concept of spatial multiplexing (SM) using MIMO in 1993. Their US Patent No. 5,345,599 issued 1994 on Spatial Multiplexing emphasized applications to wireless broadcast.

In 1996, Greg Raleigh and Gerard J. Foschini refine new approaches to MIMO technology, which considers configurations where multiple transmit antennas are co-located at one transmitter to improve the link throughput effectively. Bell Labs was the first to demonstrate a laboratory prototype of spatial multiplexing in 1998, where spatial multiplexing is a principal technology to improve the performance of MIMO communication systems.

"USING MIMO-OFDM TECHNOLOGY TO BOOST WIRELESS LAN PERFORMANCE TODAY" DATACOMM RESEARCH COMPANY 9220, Old Bonhomme Rd. St. Louis, Missouri 63132 USA. (http://www.datacommresearch.com)

This paper defines the MIMO, compares the MIMO with other existing access techniques (MISO, SIMO) only in theoretical perspectives. To understand MIMO-OFDM and its working principle mathematical and simulation explanations is required, which cannot given by this paper.

Future research related to this field

After successful completion of MIMO-OFDM capacity analysis, the following further project works may be done to enhance the MIMO techniques for 4G technology.

Integrated DWDM and MIMO-OFDM System for 4G High Capacity Mobile Communication.

Capacity Analysis on Downlink MIMO OFDMA Systems.

An Analysis of MIMO Techniques for Mobile WiMAX Systems.

The MIMO Wireless Switch: Relaying Can Increase the Multiplexing Gain.

Throughput and Capacity of MIMO WiMAX.

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