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Jaypee Institute of Information Technology, Noida - JIIT

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Minor report on MIMO-ODFM - multiple input multiple output- orthogonal frequency division multiplexing

ABSTRACT


In this new information age, high data rate and strong reliability features in wire-less communication systems are the dominant factor for a successful deployment of commercial networks. MIMO-OFDM (multiple input multiple output- orthogonal frequency division multiplexing), a new wireless broadband technology, has gained great popularity for its capability of high rate transmission and its robust-ness against multi-path fading and other channel impairments.


A major challenge to MIMO-OFDM systems is how to obtain the channel state information accurately and promptly for coherent detection of information symbols and channel synchronization.The multiuser MIMO-OFDM system has great potential of providing enormous capacity due to its integrated space-frequency diversity and multiuser diversity.


This project report is based on a novel method to enable concurrent communications in MIMO networks. This method enables an 802.11n MIMO-OFDM receiver to decode independent data streams from two independent 802.11n transmitters concurrently. The method I have discussed in this report, namely the MATRIX OPERATION, enables a single 802.11n based MIMOOFDM receiver to decode data streams from two independent 802.11n based transmitters simultaneously with a very slight modification on the existing PHY layer of 802.11n testbeds.


It has been well studied that independent data streams can be sent from a multi-antenna transmitter and decoded by multi-antenna receiver using spatial multiplexing techniques. This idea is adopted in the 802.11n standard to increase the single link throughput.

Similarly, independent data streams that are transmitted from independent transmitters can also be decoded simultaneously at the multi-antenna receiver, since this situation is essentially equivalent to the former case. However, the latter process has two major practical challenges if it is desired to be implemented on 802.11n nodes; timing and the carrier synchronization between the independent transmitters.


INTRODUCTION


MIMO


MIMO stands for Multiple-Input Multiple-Output. In communication systems, this usually means that several transmitting and receiving antennas are employed at both the transmitter and receiver to improve communication performance. It is one of several forms of
smart antenna
technology.


 Antenna Arrays


A special case of MIMO systems are antenna arrays that have been in use for a long time

·        Several antennas can be used with a specific phase and amplitude setting to transmit the same signal. This setup produces a higher gain in a certain direction and is called beamforming.

·        It also increases the diversity of the channel. If there is negative interference of the signal transmitted from one of the antennas at the receiver, then there is a high probability that at least one signal transmitted from another antenna of the array is decodable.Using antenna arrays does neither increase the used bandwidth nor does it decrease the throughput of data .                                                                            


                                                                                        


 MIMO CHANNEL MODEL


Wireless channels limitations


Wireless transmission introduces following factors-


·        Fading: multiple paths with different phases add up at the receiver, giving a random (Rayleigh/Ricean) amplitude signal.


·        ISI: multiple paths come with various delays, causing intersymbol Interference.

·        CCI: Co-channel users create interference to the target user

·        Noise: electronics suffer from thermal noise, limiting the SNR.

FORMS OF MIMO

SISO/SIMO/MISO is
degenerate
cases of MIMO

·       Multiple-input and single-output (MISO) is a degenerate case when the receiver has a single antenna.

·       Single-input and multiple-output (SIMO) is a degenerate case when the transmit.....[read full text]

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Wireless systems do not provide the option of just adding an additional cable as in wire or fibre optics based systems. Therefore, the spectral efficiency needs to be increased in order to enable a higher throughput. But customers do not only want fast data access - this access also needs to be reliable (QOS - quality of service)

MIMO systems seem to be able to solve that problem at least temporarily. Instead of just transmitting one single signal over the “air” from the transmitter to the receiver, several independent signals are sent over the common channel “air” by using multiple antennas for transmitting and receiving.

The idea seems fairly trivial but sending signals in the same frequency band over a common channel is generally not possible. This is because the signals interfere with each other and cannot be easily decoded at the receiver.


In most applications, every signal sent from a transmitting antenna reaches the receiving antenna over multiple paths. This phenomenon called multipath propagation is produced by electromagnetic waves that are reflected off walls and other objects. The signal arriving at the receiver is therefore generally a superposition of scaled and delayed versions of the original signal.


Instead of seeing multipath propagation as a factor that decreases the system performance; clever approaches use it as an advantage in MIMO systems. One can imagine the following setup:


• Transmitter using antennas T1 and T2

• Receiver using antennas R1 and R2

• T1 and T2 transmit different signals

• Both are placed inside a building - assuming no LOS for simplicity


A signal sent from T1 and received at R1 follows a different path compared to the signal sent from T2 and received at R2. The same is true for the signals from T1 to R2 and from T2 to R1. If one assumes that the different paths are known at the receiver, clever calculations can remove the effect of the superposition and decode both streams. In that case, the data rate would have been doubled without using additional spectrum.

Due to the spatial distribution of the antennas, the reliability of the link should be increased at the same time. The major concern is how to obtain the channel matrix .This is generally done in a training phase where known signals are sent by the transmitter.

This does of course decrease the overall throughput as no real information is transmitted during that phase. This loss is generally smaller than the additional capacity gained by using a second stream. This procedure is called spatial multiplexing.

Ø  Spatial multiplexing has been generally used to increase the capacity of a MIMO link by transmitting independent data streams in the same time slot and frequency band simultaneously from each transmit antenna, and differentiating multiple data streams at the receiver using channel information about each propagation path.


Ø  Benefits

·         It does not require any additional power.

·         No additional bandwidth requirement.

Ø  WORKING

In the above figure it has been shown that when we have M= 3 number of antennas in the transmitting side and have K (a1, a2, a3, a4, a5, a6) = 6 bits for sending. At first divide the bits into M=3 sub streams of data {(a1, a3), (a2, a4), (a3, a6)} and then multiply each sub stream of data with three carrier frequency in order to transmit them via three separate antennas.

If all the sub-streams had to be transmitted by one carrier then the bandwidth consumptions would be three time greater-this is one of the great advantage .....

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In case of impulse noise or other short period noise with high energy, it is likely that a symbol gets distorted to such a high extent that it cannot be recovered. The shorter the period in which the symbol is available, the higher is the probability that the symbol is fully destroyed by bursts of noise.


Frequency Division Multiplexing


To solve this problem, one can use frequency division multiplexing (FDM). Instead of using a single carrier that occupies the whole available frequency band, several subcarriers are employed within the available frequency band.

The data stream is distributed over all available subcarriers. This increases the symbol period and therefore decreases susceptibility to noise bursts. It also adds additional immunity to narrow banded noise; as such noise only affects several of the subcarriers and not the entire signal.

FDM comes at the cost of a lower data rate as a guard interval has to be inserted between the different subcarriers and therefore a part of the available frequency spectrum is wasted. FDM also adds some complexity to the hardware by using several streams. At the same time it also removes some of the complexity by slowing down the bit rate of each subcarrier.


Ø Orthogonal FDM (OFDM)

If one can choose a set of subcarriers that are orthogonal to each other, then there is

No need to use a guard interval to separate the subcarriers. This would increase the spectral efficiency of the system.


Two signals u(t) and v(t) are said to be ort.....

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Using a cyclic prefix leads to a significant simplification of the receiver: Instead of having to remove a convolution in time (between the signal and the channel), it is only necessary to remove a multiplication in frequency domain.




NOISE CONSIDERATIONS


The most common noise source in a wireless system is thermal noise - usually manifesting itself as Additive White Gaussian Noise (AWGN). As the noise spectrum is uniform in the frequency domain, this kind of noise has the same impairment on the overall system as it has in a single carrier system.

Another common type of noise is impulse noise. This type of broadband noise is generally only present during a short period. As described before, the OFDM system performs better under impulse noise than a single carrier system. Colored noise is difficult to handle as it doesn’t have a constant spectrum as AWGN. A simple solution for high noise environments is to lower the data rate.

 

CHANNEL MODELS

 

If there are other systems present, carrier interference can occur. An OFDM system can handle that by disabling the affected subcarriers. Another type of imperfection emerges from the local oscillator. There are two effects that have to be considered: Phase noise (sometimes called phase jitter) and the frequency offset.

Phase noise originates from the fact that the oscillator frequency changes randomly within a small range. The same argument in the frequency domain is that the oscillator does not produce a single peak but rather a “smeared out” peak. Phase noise affects every subcarrier. As the spectral width of a subcarrier is smaller than in a single carrier system, phase noise affects OFDM systems more severely tha.....

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To simplify the notation for a MIMO system with T transmitting and R receiving Antennas, it is assumed that T = R = 4. Such a general setup is shown below in the figure. It is straight forward to change the number of transmitting or receiving antennas.




A standard approach for a MIMO system with 4 transmitting and 4 receiving antennas


Ø MIMO-OFDM Channel Model


As can be seen from the SISO OFDM channel model, the different OFDM sub channels can be treated separately. This allows formulating a simple model for a MIMO-OFDM system: The whole system can be seen as a stack of C different MIMO systems. A graphic showing such a system is presented in figure shown below.


A channel model for MIMO-OFDM SYSTEM


WORKING OF MIMO-OFDM

Like any other communication system MIMO-OFDM system also has transmitter and receiver but the antennas are more than one both at transmit and receive end. MIMO system can be implemented in various ways, if we need to take the diversity advantage to combat fading then we need to send the same signals through various MIMO antennas and at the receiving end all the signals received by MIMO antennas will receive the same signals traveled through various path.

In this case the entire received signal must pass through un-correlated channels. If we are inserted to use MIMO for capacity increase then we can send different set of data (not the same set of data like diversity MIMO) via a number of antennas and the same number of antennas will receive the signals in the receiving end. For MIMO to be efficient antenna spacing need to be done very carefully- at least half the wave length of the transmitting signal.

.....

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The multiple antennas available on a MIMO enabled node could also be used to provide immunity to interference. Interference can be avoided at the multi-antenna transmitter side using pre-coding and beamforming, and/or cancelled at the receiver side by weighing and linearly combining the received signals from each antenna.

The idea of achieving concurrent communications with MIMO enabled nodes has been adopted by some MAC protocols with the purpose of increasing the aggregate throughput of the network.


MATRIX OPERATION

The matrix operation is defined as synchronous, independent data transmission from two 802.11n based MIMO-OFDM transmitters to a single 802.11n based MIMO-OFDM receiver. The two transmit nodes (clients) are equipped with 2 antennas each while the receive node (base station) is equipped with 4 antennas.

This scenario is illustrated in Fig. 1. Assuming two client nodes are sending independent data streams, the objective of the matrix operation is to simultaneously decode independent data streams from these two independent transmitters. Theoretically, this situation is equivalent to a single 4 × 4 MIMO link where the transmitter has two pair of antennas each located at different locations.


FIG 1: MATRIX OPERATION SYSTEM MODEL


IMPLEMENTATION CHALLENGES


·         Timing synchronization: Two client nodes need to coordinate the onset of their transmissions.


·         Carrier synchronization: Relative frequency offset between two client nodes should be eliminated.


SYNC PACKET OPERATION


·         In order to solve the timing and frequency synchronization problems between two client nodes, we first send synchronization (SYNC) packet from the base station to client nodes before the actual data transmission starts.  At the client node side, upon receiving the SYNC packet each client node first estimates the carrier frequency offset between itself and the base station.

Then, it waits for a pre-programmed fixed silence peri.....

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