- 235 Views
- Uploaded on
- Presentation posted in: General

4G using MIMO

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

4G using MIMO

Presented by:

Joel AbrahamAnoop Prabha

Binaya Parhy

- Why MIMO
- Different Arrangements of Antennas
- Working
- MIMO vs SIMO/MISO
- Types of MIMO
- Diversity
- Spatial Multiplexing
- Uplink Collaborative MIMO Link

- Actual Working
- Channel Matrix
- System Model
- Advantages and Application

- MIMO is an acronym that stands for Multiple Input Multiple Output.
- Motivation: current wireless systems
- Capacity constrained networks
- Signal Fading, Multi-path, increasing interference, limited spectrum.

- 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 (a.k.a 802.16-2005)
- – 3G / 4G

- In short - Two or more data signals transmitted in the same radio channel at the same time
- It is an antenna technology that is used both in transmission and receiver equipment for wireless radio communication.
- MIMO uses multiple antennas to send multiple parallel signals (from transmitter).

- 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.
- They are called “multi-dimensional” signals
- There can be various MIMO configurations. For example, a 4x4 MIMO configuration is 4 antennas to transmit signals (from base station) and 4 antennas to receive signals (mobile terminal).

- The total number of channel = NTx x NTr

- MIMO involves Space Time Transmit Diversity (STTD), Spatial Multiplexing (SM) and Uplink Collaborative MIMO.
- Space Time Transmit Diversity (STTD) - The same data is
coded and transmitted through different antennas, which effectively

doubles the power in the channel. This improves Signal Noise Ratio

(SNR) for cell edge performance.

- Spatial Multiplexing (SM) - the “Secret Sauce” of MIMO. SM
delivers parallel streams of data to CPE by exploiting multi-path. It

can double (2x2 MIMO) or quadruple (4x4) capacity and throughput.

SM gives higher capacity when RF conditions are favorable and

users are closer to the BTS.

- Uplink Collaborative MIMO Link - Leverages conventional single
Power Amplifier (PA) at device. Two devices can collaboratively

transmit on the same sub-channel which can also double uplink

capacity.

Wireless throughput scales as more radio transmissions are added

Only baseband complexity, die size/cost and power consumption limits the number of simultaneous transmission

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

- Consider a simple BPSK bit sequence 1,-1,1,1,-1
- We code 1 as C1 and -1 as C2
- C1 = c2 =
1 -1

- Dimension of C is determined by the Number of Tx and Rx

Y = Hx + n

H = Channel Matrix

n = Noise

- Rx1 = h11Tx1 + h21Tx2
+ h31Tx3 + n1

- Using the space dimension (MIMO) to boost data rates up to 600 Mbps through multiple antennas and signal processing.
- Target applications include: large files backup, HD streams, online interactive gaming, home entertainment, etc.
- Backwards compatible with 802.11a/b/g
- Application
- WLAN – WiFi 802.11n
- Mesh Networks (e.g., MuniWireless)
- WMAN – WiMAX 802.16e
- 4G
- RFID
- Digital Home

- http://en.wikipedia.org/wiki/4G
- http://en.wikipedia.org/wiki/MIMO#MIMO_literature
- http://www.wirelessnetdesignline.com/howto/wlan/185300393;jsessionid=3R20PO41AV3Y1QE1GHRSKHWATMY32JVN?pgno=1
- www.ieeeexplore.com
- http://www.ece.ualberta.ca/~HCDC/mimohistory.html
- http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.13.4732&rep=rep1&type=pdf

Thank you

Presented By

Anoop Madhusoodhanan Prabha

36576876

- Rayleigh Model
- Statistical Modeling of wireless channels.
- Magnitude of signal varies randomly as it propagates in the medium.
- Best fit for tropospheric and ionospheric signal propagation.
- Fits fine for Urban environments too.
- Highlight – No dominant light of sight communication between transmitter and receiver.
- Rate of channel fade – Studied by Doppler shift. 10Hz to 100 Hz is the shift considered in GSM phones modeling for an operating frequency of 1800 MHz and speed between 6km/h to 60 km/h

- Racian Fading
- Comes into picture when there is a dominant component present (especially line of sight way)
- v(t) = Ccoswct + ∑Nn=1rncos (wct + fn)
- Examples
- Vehicle to vehicle communication
- Satellite channels
- Indoor communication

- Nakagami fading
- Reason for modeling – Empirical results matched with short wave ionospheric propagation.
- If amplitude – Nakagami distributed, power – gamma distributed and ‘m’ is the shape factor in this distribution.
- For m=1, its Rayleigh fading (amplitude distribution) and corresponding power distribution is exponential.
- These days many recent papers recommend this model as an approx. to Rician model.

- The fading and shadowing effects are overcome by spatial diversity i.e. my installing multiple antennas.
- Antennas separated by 4 – 10 times the wavelength to ensure unique propagation paths.
- As a part 4G, one of important emphasis is on throughput improvement.
- This stressed on better modulation techniques and coding practices.

MIMO Architecture

- For transmit/receive beamforming we have a diversity order of MN, referred to as full diversity.
M – Number of transmitting antennas

N – Number of receiving antennas

v – beamforming vector for receiver

u – beamforming vector for transmitter

- The design goal of 802.11n was “HT”, High throughput.
- Speed – 600 Mbps unlike the 802.11g (54Mbps)
- The achievement of this speed is as follows:
- More Subcarriers (OFDM) – from 48 (802.11g) to 52 thus speed increased to 58.5Mbps
- FEC squeezing to a coding rate of 5/6 instead of ¾ boosted the link rate to 65Mbps.
- Guard interval of 800ns in 802.11g was reduced to 400ns thus increasing the throughput to 72.2Mbps.
- MIMO with a max of 4X4 architecture which means 72.2X4 = 288.9Mbps
- Channel width of 802.11g was 20Mhz each which was increased to 40MHz which eventually resulted in 600MHz throughput.

- http://www.wirelesscommunication.nl/
- Wikipedia
- http://www.intel.com/technology/itj/2006/volume10issue02/art07_mimo_architecture/p04_mimo_systems_reliability.htm
- http://www.wirevolution.com

Presented By

Binaya Parhy

- MIMO Wireless Communications
- Capacity of MIMO

- Well known STBC codes
- Criteria to be a good ST BC code.
- Cyclic and Unitary STBC
- Orthogonal STBC
- Diagonal algebric
- BLAST(V-BLAST & D-BLAST)
- Differential STBC(Non coherent detection)

- Summarize

- SISO Capacity
- Capacity of any communication system is given by the most famous equation

- ρ:SNR, h: Channel gain
- Note: Since channel is assumed to be N(0,1), this reduces to just
- MIMO Capacity Equation
- It is similar but when it is MIMO we have MtxMr channel coefficients.

- Block Diagram Of a MIMO communication system

1

H1,1

1

h1,2

H2,1

h2,2

2

2

H2,Mr

H1,Mr

hMt,1

hMt,2

Mr

Mt

hMt,Mr

Channel Matrix H=

MIMO Capacity

Four Cases

Mt=Mr=1 Reduces to SISO

Mr=1, Mt>1

Mt=1, Mr>1

Mr>1, Mt>1

ρ =10 dB

- Case:2(Mr=1, Mt>1)

ρ =5 dB

ρ =1 dB

Capacity

Mr

- Case:3(Mt=1, Mr>1)

ρ =10 dB

Capacity

ρ =5 dB

ρ =1 dB

Mt

- Case:4(Mt>1, Mr>1)

ρ =10 dB

ρ =5 dB

ρ =1 dB

Capacity

Mt

- Conclusion:
- M=min(Mt,Mr)
- The capacity of the MIMO system increases linearly with
the minimum of transmitter and receiver antenna.

- To achieve the potential huge capacity, new coding and modulation called Space Time coding or ST-modulation is developed since 1998.

- The maximum probability of error (also called PEP- Piece wise error probability) of a MIMO system is given by
- r-> rank of and λi’s are the eigen valus of
- Based on the PEP code design criteria were proposed by Tarokh in 1998.
- Rank criterion or Diversity criterion
The minimum rank of difference of any 2 code word over all possible pairs should be should be as large as possible. If there are L signals then there are L(L-1)/2 pairs.

- Product criterion or Coding gain criterion
The minimum value of the product over all pairs of distinct code word difference should be as large as possible.

- Rank criterion or Diversity criterion

- Q: Among these two criteria which one is more important?
- A: Diversity is the more important one.
- Accordingly lets define two terms that define the wellness of a ST code
- Diversity order = rxMr
- Normalized coding gain
Where T=Mt and 0<γ<1

- MIMO Tran receiver can be modeled as
- C is the ST code is one among the signal constellation.
- So we will conclude that
- Square size i.e. T=Mt
- ||Cl||2=Mt2 (This is for normalization to have a fair comparison)
- The difference matrix between any two distinct code Cl and Cl’should be full rank.
- The coding gain γshould be as large as possible. γ is a measure of the minimum Euclidian distance between two codes.

- Cyclic and Unitary STBC
- Orthogonal STBC
- Diagonal algebric
- BLAST(V-BLAST & D-BLAST)
- Differential STBC(Non coherent detection)

- Proposed by Hochwald & Sweldens in 2000.

- Why Cyclic?
- Cl=CL+li.e. the code regenerates itself.
- Sqrt(M) is to satisfy the energy criterion ||Cl||2=Mt2.
- Achieves full diversity.
- To maximize coding gain ui’s should be chosen carefully.
- Exhaustive search methodology is used to find ui’s.
- For Mt=2, L=4, [u1 u2]=[1 1], coding gain=.707
- For Mt=2, L=16, [u1 u2]=[1 7]
- For Mt=4, L=16, [u1 u2 u3 u4]=[1 3 5 7], coding gain=.4095
- As Clis a diagonal matrix, at a time slot only one Tx transmits.
- Why Unitary?
- An unitary matrix satisfies AHA=I (Identity Matrix).
- Cyclic ST is an unitary code.

- Cyclic ST code is not the optimum unitary code. There are others which can give lesser coding gain for e.g. Mt=2, L=4
- The coding gain for above ST code is 0.8165. The upper bound is given by
- For L=8, the optimal code is not yet discovered.
- No new ST coding techniques has to be explored.

- Orthogonal STBC achieve full diversity and offer fast ML decoding. Proposed by Alamouti in 1998 for two Tx.
- X1, X2 are any two complex symbols.
- Fast ML decoding means for ML X1, X2 can be minimized separately therefore decreasing the complexity of the minimization problem.
- For more transmitters, Orthogonal design can be used.

- Orthogonal design with k variables X1, X2,…… Xk is a pxn matrix such that
- The entries of G are 0,+/- X1, +/- X2 ,……., +/- Xk or their conjugates.
- The columns are orthogonal to each other. i.e.
- n is related to the number of transmitter antenna and p to the time delay.
- The rate of orthogonal design is k/p i.e a code word of time delay p carries k information symbols.

- In general n=2l an orthogonal design of size n by n can be given as
- Rate is given by l+1/2l
- With increase in l the rate decreases, so 2x2 Alemouti is normally used.

- Vandermonde transformation is used.
- S1,S2…Sk are the k information symbols. |θk|=1. The code word is formed as diag[X1,X2,…Xk].
- Θk=exp(j(4k-3)/2K) k=1,2..K
- Achieves full diversity.

- The first MIMO system proposed by Tuschini from Bell Lab to verify the potential MIMO capacity.
- V-Blast Systme
- Each data stream layer for each Tx.
- No coding across different layer. Decoding by nulling and cancellation method. Ymr is used to obtain Ymr-1 and so on.
- Disadvantage- error propagation.

1

..a3,a2,a1,a0

2

..b3,b2,b1,b0

Mr

Mt

- The first MIMO system proposed by Tuschini from Bell Lab to verify the potential MIMO capacity.
- V-Blast Systme
- Each data stream layer for each Tx.
- No coding across different layer. Decoding by nulling and cancellation method. Ymr is used to obtain Ymr-1 and so on.
- Disadvantage- error propagation.

1

..a3,a2,a1,a0

2

..b3,b2,b1,b0

Mt

Mr

- Coding is done with in each data stream but no coding across different streams.
- At the 1st time slot only 1 transmitted sends other send nothing. At 2nd only 1st and 2nd Tx sends and so on. After Mt time slots all Tx starts sending.
- Achieves full diversity.
- Better performance than V-BlAST.
- Decoding is same as V-BLAST.

- There are 3 scenarios.
- CSI is not available at Tx but available at Rx---ST coding
- CSI is not available at both Tx and Rx--- Differential Coding
- CSI is available at both Tx and Rx--- Beam forming or Smart Antenna
- Differential Encoding/Decoding
- Proposed by Hughes, Hochwald and Swelden in 2000.
- Non coherent detection ideal for slow fading channels.
- So at first a dump (identity matrix is sent)

- For stability unitary ST coding is used.
- ML Detection-:
- Performance of Non-coherent detection is 3 dB below then coherent case dute to noise.
- The received vector at the previous slot is used for detection of present information symbol.

<------------Coherent----------

<--NonCoherent->