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4G using MIMO

4G using MIMO . Presented by: Joel Abraham Anoop Prabha Binaya Parhy. Agenda. 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

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4G using MIMO

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  1. 4G using MIMO Presented by: Joel AbrahamAnoop Prabha Binaya Parhy

  2. Agenda • 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

  3. Why MIMO ? • 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

  4. Different types

  5. MIMO Defined • 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).

  6. How does MIMO work? • 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.

  7. How does MIMO work(cont..) • 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).

  8. 4 x 4 MIMO Configuration • The total number of channel = NTx x NTr

  9. MIMO vs SIMO/MISO

  10. Forms of MIMO

  11. Types of MIMO • 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.

  12. Mimo Increases Throughput(Spatial Multiplexing) Wireless throughput scales as more radio transmissions are added Only baseband complexity, die size/cost and power consumption limits the number of simultaneous transmission

  13. MIMO Increases Range 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

  14. The Working • 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

  15. MIMO channel Matrix

  16. MIMO system model Y = Hx + n H = Channel Matrix n = Noise • Rx1 = h11Tx1 + h21Tx2 + h31Tx3 + n1

  17. Single Radio vs MIMO Performance

  18. General Info & Application • 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

  19. References • 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

  20. Thank you

  21. Presented By Anoop Madhusoodhanan Prabha 36576876

  22. Distribution of Fading channel • 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

  23. Distribution of Fading channel (Contd.) • 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

  24. Distribution of Fading Channel (Contd.) • 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.

  25. Evolution of MIMO • 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.

  26. MIMO Architecture

  27. Spatial Diversity at Receiver

  28. SNR (Receiver Diversity)

  29. Transmitter Diversity

  30. SNR (Transmitter Diversity)

  31. Transmit/Receive Diversity

  32. SNR(Transmitter/Receiver Diversity) • 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

  33. Application on 802.11n • 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.

  34. References • 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

  35. Presented By Binaya Parhy

  36. MIMO Wireless Communication System

  37. Agenda • 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

  38. MIMO Wireless Communication System • 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.

  39. MIMO Capacity cont… • 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=

  40. MIMO Capacity Four Cases Mt=Mr=1 Reduces to SISO Mr=1, Mt>1 Mt=1, Mr>1 Mr>1, Mt>1 MIMO Capacity cont…

  41. MIMO Capacity cont… ρ =10 dB • Case:2(Mr=1, Mt>1) ρ =5 dB ρ =1 dB Capacity Mr

  42. MIMO Capacity cont… • Case:3(Mt=1, Mr>1) ρ =10 dB Capacity ρ =5 dB ρ =1 dB Mt

  43. MIMO Capacity cont… • Case:4(Mt>1, Mr>1) ρ =10 dB ρ =5 dB ρ =1 dB Capacity Mt

  44. MIMO Capacity cont… • 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.

  45. ST code design criteria • 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.

  46. ST code design criteria cont…. • 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 • When r=Mt, the ST code is called to achieve full diversity. The condition T=Mt is a necessary and sufficient condition for achieving full diversity.

  47. ST code design criteria cont… • 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.

  48. Some well known ST signals • Cyclic and Unitary STBC • Orthogonal STBC • Diagonal algebric • BLAST(V-BLAST & D-BLAST) • Differential STBC(Non coherent detection)

  49. Cyclic STBC • Proposed by Hochwald & Sweldens in 2000.

  50. Cyclic STBC cont… • 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.

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