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MIMO.ppt

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Describes Multiple input Multiple output technolongy

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Page 1: MIMO.ppt

Why MIMO?

• MIMO is all about multi-antenna solutions

• We are aiming for multi-layer transmissions

• If we have multiple antennas, we can transmit several layers, different streams of information all using the same bandwidth and same frequency separated by space

Page 2: MIMO.ppt

Why MIMO?

• MIMO techniques have emerged as a solution to provide higher data rates by exploiting the multipath characteristics of the wireless channel

• If we send a radio pulse towards a receiver, then because of multi paths, it is going to arrive at different times

• If we have 2 signals 90 degrees out of phase => when they arrive, we could get strong additive receive signals and in other places we get a weak composite one. This effect is known as fast-fading

• With MIMO, we can use that to our advantage

Page 3: MIMO.ppt

Smart antennas

• Smart antennas provide the next substantial increase in throughput.

• The peak data rates tend to be proportional to the number of send and receive antennas, so 4X4 MIMO is capable of twice the peak data rates as 2X2 MIMO systems.

• By “smart antennas” we refer to adaptive antennas such as those with electrical tilt, beam width and azimuth control which can follow relatively slow-varying traffic patterns

• Intelligent antennas can – form beams aimed at particular users or – steer nulls to reduce interference and – finally Multiple-Input Multiple Output (MIMO) antenna schemes

Page 4: MIMO.ppt

Shannon-Limit

• 802.16 is an IEEE standard for WiMAX providing a high bit rate solution => cellular technology needs to keep up with other technologies offering high rates

• The problem is that we are faced with what we call shannon-limit:– The max bitrate = BW * Log2(1+SINR)

• Theoretically, we can’t go above that max bitrate but there is a way to cheat

Page 5: MIMO.ppt

Shannon-Limit

At low SINR: approximate

linear increase in rate

Instead, we can have 2 signal streams both at lower SINR & overall capacity can surpass the Shannon limit

If we are just looking to improve SINR, then the gain will be less and less

At high SINR: log increase in rate

Sharing SINR between streams -> linear increase

in rate

Page 6: MIMO.ppt

MIMO & Modes

Single Multiple

Single SISO SIMO (Receive diversity)

Multiple MISO (Transmit diversity) MIMO

Input

Output

Mode 2,7 Mode 3, 4, 5, 6

Mode 1,7

Page 7: MIMO.ppt

7 modes of MIMO on DL

• Mode 1 - single antenna port (port 0)

– Single data stream (=codeword) is transmitted on one antenna and received by either one (=SISO) or more (=SIMO)

• Mode 2: transmit diversity

– Transmission of the same information stream on multiple antennas (2,4)

– The information stream is coded differently on each of the antennas using “Space-Frequency Block Codes”

– Used by common, control and broadcast channels

Page 8: MIMO.ppt

7 modes of MIMO on DL

• Mode 3: open loop spatial multiplexing– 2 information streams (= 2

code words) are transmitted over 2 or more antennas (up to 4)

– No explicit feedback from the UE although a Transmit Rank indication (TRI) transmitted by the UE is used by eNB to select the number of spatial layers

– OL-SM provides better peak throughput than transmit diversity

• Conditions:– No feedback from UE– UE moving fast– eNB cycles through a fixed

pattern of precoders– Due to high mobility, eNB

doesn’t know which precoder is best

Page 9: MIMO.ppt

7 modes of MIMO on DL• Mode 4: closed loop spatial

multiplexing– Two information streams are

transmitted over 2 code words from N antennas (up to 4)

– Pre-coding Matrix Indicator (PMI) is fed back from the UE to the eNB

– The feedback mechanism allows the transmitter to pre-code the data to optimize transmission so that the signals can be easily separated at the receiver side into original streams

– The highest performing mode of MIMO

• Conditions:– UE is stationary– UE suggests to eNB which

precoder matrix to use

Page 10: MIMO.ppt

7 modes of MIMO on DL

• Mode 5: MU-MIMO– This mode is similar to CL-

SM but the information streams are targeted at different UEs

• Multiple UEs share the same resources

– Each UE will experience the same data rate but the overall network data rate is improved

– The number of UEs is limited by the number of spatial layers (1 spatial layer per UE)

Page 11: MIMO.ppt

7 modes of MIMO on DL• Mode 6: closed loop rank 1 with

pre-coding:– A single code word is transmitted

over a single spatial layer– Considered a fall-back scenario of

CL-SM and is associated with beamforming

• Mode 7: single-antenna port (port 5)

– Beamforming mode– A single code word is transmitted

over a single spatial layer– A dedicated reference signal (port

5) forms an additional antenna port and allows transmission from more than 4 antennas

Page 12: MIMO.ppt

Explaining Spatial Mux

• In this example, each transmit antenna transmits a different data stream.

• This is the basic case for spatial multiplexing.

Page 13: MIMO.ppt

Explaining Beamforming

• This is an example of beamforming

• We have 2 antennas and 1 receiver

• We are trying to maximize the receive signal at the antenna

• We do that by adjusting the phase and amplitude of the signal going to each antenna

• This is achieved by using “precoding”

Page 14: MIMO.ppt

Explaining Precoding• The precoder is a complex matrix W• Rows correspond to complex antenna

weights• Columns correspond to layers• a1 and a2 are antennas. s1 and s2 are 2

separate streams of data• Both antennas are going to use to the same

frequency (=reusing the bandwidth)• We need to adjust the amplitude and phase

of the different layers going to the different antennas

• We need to make sure that the radio load that comes out is separate enough so that the receiver can pick out 2 completely different streams: this is done by weighing

• The number of rows corresponds to the number of antennas

• The number of columns corresponds to the number of layers

• The values in the matrix are the weights for antenna port 1 and port 2 (row wise)

Page 15: MIMO.ppt

Matrix Algebra

• a refers to the signal• h is the transfer

function (channel estimate) and is changing the amplitude and the phase of the signal

• y is what is received (probably affected by h)

• With this MIMO example, we have 2 sending/receiving antennas and 2 different signals and 4 h functions

• We have to estimate the channel response at pilot bits

• For example, if I send at a known time a ‘1’ bit and receive a ‘1’, then I know that the channel isn’t corrupting that bit. If I receive ‘-1’, then I know the data is inverted and I can correct it accordingly and so on.

Page 16: MIMO.ppt

Precoding patterns

• This is an example with 2 precoders

• 2 separate layers treated differently

• Example: for layer 2, 2 lobes at 90° and 270 ° => the UE needs to be positioned there

Page 17: MIMO.ppt

SU-MIMO

• This is an example of SU-MIMO

• L1 and L2 are transferred from those lobes in the eNB and received at different angles by the UE

• UE and eNB are both using precoder 1

• Note: For a MU-MIMO, each of the layers would be targeted to a different UE

Page 18: MIMO.ppt

When to use CL-SM or OL-SM?

• The benefits of open and closed loop SM schemes are achieved when the received signal quality (as measured by SINR) is at its highest:15 dB and higher.

• At the cell edge, a weak signal and low SINR reduce the benefits of SM modes– CL rank 1 or transmit diversity become more

attractive

• Transmit diversity is also more attractive in environments where signal scattering is low (e.g. rural areas)

Page 19: MIMO.ppt

UE reporting• In order for MIMO schemes to work properly, each UE has to report

information about the mobile radio channel to the base station. • A lot of different reporting modes and formats are available which

are selected according to MIMO mode of operation and network choice.

• The reporting may be periodic or aperiodic and is configured by the radio network.

• Aperiodic reporting is triggered by a CQI request contained in the uplink scheduling grant. The UE would send the report on PUSCH.

• In case of periodic reporting, PUCCH is used in case no PUSCH is• available.

Page 20: MIMO.ppt

CQI• CQI (channel quality indicator) is an indication of the downlink

mobile radio channel quality as experienced by this UE. • The UE is proposing to the eNodeB an optimum modulation scheme

and coding rate to use for a given radio link quality, so that the resulting transport block error rate would not exceed 10%.

• 16 combinations of modulation scheme and coding rate are specified as possible CQI values.

• The UE may report different types of CQI.• A so-called “wideband CQI” refers to the complete system

bandwidth. • Alternatively, the UE may evaluate a “sub-band CQI” value per sub-

band of a certain number of resource blocks which is configured by higher layers.

• The full set of sub-bands would cover the entire system bandwidth.• In case of spatial multiplexing, a CQI per code word needs to be

reported.

Page 21: MIMO.ppt

PMI

• PMI (precoding matrix indicator) is an indication of the optimum precoding matrix to be used in the base station for a given radio condition.

• The PMI value refers to the codebook table.• The network configures the number of resource

blocks that are represented by a PMI report. • Thus to cover the full bandwidth, multiple PMI

reports may be needed. • PMI reports are needed for closed loop spatial

multiplexing, multi-user MIMO and closed-loop rank 1 precoding MIMO modes.

Page 22: MIMO.ppt

RI

• RI (rank indication) is the number of useful transmission layers when spatial multiplexing is used.

• In case of transmit diversity, rank is equal to 1.

Page 23: MIMO.ppt