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OutlineIntroduction
PrecodingScheduling (user selection)
Chapter 3: Physical-layer transmission techniques
Section 3.6: Space Division Multiple Access (SDMA)
Instructor: Nguyen Le HungEmail: [email protected]; [email protected]
Department of Electronics & Telecommunications EngineeringDanang University of Technology, University of Danang
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OutlineIntroduction
PrecodingScheduling (user selection)
1 Introduction
SDMA and OFDMMultiuser transmission
2 Precoding
Precoding classificationAn example of linear precodingPower allocation in ZF precodingPossible research problems
3 Scheduling (user selection)Exhaustive selectionGreedy selection
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OutlineIntroduction
PrecodingScheduling (user selection)
SDMA and OFDMMultiuser transmission
SDMA with OFDM
The integration of multi-antenna and OFDM techniques hasprovided remarkable diversity and capacity gains in broadbandwireless communications.In multiuser (MU) transmissions, the use of multiantenna array atthe base station (BS) enables simultaneous transmission of multiple
data streams to multiple users by exploiting spatial separationsamong users.
ABS/eNB
AMS/UE
(a)
IFFT
SU-MIMOprecoder A
BS/eNB
AMS/UE1
(b)
IFFT
MU-MIMOprecoder
AMS/UE2
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OutlineIntroduction
PrecodingScheduling (user selection)
SDMA and OFDMMultiuser transmission
A simple example of multiuser (MU) transmission
1,1h
2,1h
Mh ,1
Base Station
1s
Modulation
Coded bits
of user 1
2s
Modulation
Coded bitsof user 2
1,2h2,2h
Mh ,2
Antenna 1
Antenna M
De-mod
Channel
estimator
User 2
De-mod
Channel
estimator
User 1
1y
2y
1 = 1
=1
1,+2
=1
1,+1, and 2 = 2
=1
2,+1
=1
2,+2
Mobile Communications - Chapter 3: Physical-layer transmissions Section 3.6: Space Division Multiple Access (SDMA) 4
O li P di l ifi i
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OutlineIntroduction
PrecodingScheduling (user selection)
Precoding classificationAn example of linear precodingPower allocation in ZF precodingPossible research problems
Precoding classification
In the so-called space division multiple access (SDMA), multiuserdiversity is the primary factor that increases significantly the systemsum-rate (throughput).
As a result, an appropriate multiuser encoding technique (at the BS)is indispensable to attain the considerable sum-rate gain in SDMA.
It is well-known that dirty paper coding (DPC) is an optimalmultiuser encoding strategy that achieves the capacity limit of MUbroadcast (BC) channels but at the cost of extremely highcomputation burden as the number of users is large.
Recent studies have introduced several suboptimal multiuser
encoding techniques with lower complexity (relative to DPC) thatcan be categorized into:
nonlinear precoding such as: vector perturbation, TomlinsonHarashima techniqueslinear precoding such as: minimum mean squared error (MMSE),zero-forcing.
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O tline Precoding classification
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OutlineIntroduction
PrecodingScheduling (user selection)
Precoding classificationAn example of linear precodingPower allocation in ZF precodingPossible research problems
Multiuser transmission techniques
LTE (4G) system
roa an commun ca ons(high data rate and reliability)
Diversity
Time Freq.SignalSpace
Multi-user
Space
Multipath channelModelin
CSI feedback
Analog Digital
Vectorquantization
Quasi-static Time-variant
BEMs AR
LBG
Grassmannian
Random
Scheduling Precoding
Exhaustivesearch
Greed or iterativesearch
Linearmethods
Non-linearmethods
Codebook-based ones
MMSE BD DPC THP PU2RC
Randomuser selection
VP
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Outline Precoding classification
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OutlineIntroduction
PrecodingScheduling (user selection)
Precoding classificationAn example of linear precodingPower allocation in ZF precodingPossible research problems
An example of linear precoding
1,1h
2,1h
Mh ,1
Base Station
Feedback link of
channel state information (CSI)
1s
X
X
X
1,1w
Modulation
Coded bits
of user 1
2,1w
Mw ,1
2s
X
X
X
1,2w
Modulation
Coded bits
of user 2
2,2w
Mw ,2
1,2h2,2h
Mh ,2
Antenna 1
Antenna M
De-mod
Channel
estimator
User 2
De-mod
Channel
estimator
User 1
1y
2y
1 = 1
=1
1,1,+2
=1
2,1,+1, and2 = 2
=1
2,2,+1
=1
1,2,+2
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OutlineIntroduction
PrecodingScheduling (user selection)
Precoding classificationAn example of linear precodingPower allocation in ZF precodingPossible research problems
Inter-user interference
The received signals at user- can be determined by
=
=1
,, + =1
,, + , , {1, 2},
(1)
where
=1
,, is called as inter-user interferencethat would significantly degrade the performance of the system.Precoding design is to find the weighting coefficients {,}2=1that satisfy the following condition
=1
,, = 0 with ,
{1, 2} (2)to eliminate the inter-user interference
=1 ,,.
The above technique is called as zero-forcing (ZF) precoding.
The problem of finding the weighting coefficients {,}2=1 can beeasily solved by expressing received signals in a vector form.
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OutlineIntroduction
PrecodingScheduling (user selection)
Precoding classificationAn example of linear precodingPower allocation in ZF precodingPossible research problems
Zero forcing (ZF) precoding formulation
In the presence of two users, the previous equations become12
=
1,1 . . . 1,2,1 . . . 2,
1,1 2,1...
...1, 2,
12
+
12
.
In the presence of users, the received signal can be expressed by:
y = HWs+ z, (3)
where y =
1..
.
, H =
1,1 . . . 1,..
.
..
.
..
.,1 . . . ,
, s =
1..
.
W =
1,1 . . . ,1... . . .
...1, . . . ,
= [w1, . . . ,w] with
w = [,1
, . . . , ,]
, and z = [1
, . . . , ]
.Mobile Communications - Chapter 3: Physical-layer transmissions Section 3.6: Space Division Multiple Access (SDMA) 9
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IntroductionPrecoding
Scheduling (user selection)
gAn example of linear precodingPower allocation in ZF precodingPossible research problems
Zero-forcing precoding formulation (cont.)
To eliminate inter-user interference, precoding matrix W can bedetermined by
W = H(HH
)1H (4)
so thaty = HWs+ z = s+ z. (5)
With precoding, the received signal can be written by
y = Hx+ z, (6)
where x = [1, . . . , ]
= Ws are the transmitted signals in a
vector form at antennas in the base station.Under the power constraint of max at the BS, one has
=12
=
[ x 2
] max, (7)
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IntroductionPrecoding
Scheduling (user selection)
gAn example of linear precodingPower allocation in ZF precodingPossible research problems
Power allocation in ZF precoding
The power constraint (7) is equivalent to=1
max. (8)
where =(HH
)1, and =
After ZF precoding, the received signals at users are given by
y =
1...
=
11
...
+
1...
(9)Hence, the resultant sum-rate of the multiuser system is
= max:
=1 max
=1log2 (1 + ) (bps/Hz) (10)
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OutlineI d i
Precoding classificationA l f li di
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IntroductionPrecoding
Scheduling (user selection)
An example of linear precodingPower allocation in ZF precodingPossible research problems
Power allocation in ZF precoding (cont.)
The optimal power allocation [, {1,...,}] in (10) can beeasily determined by the following waterfilling process
= (/ 1)+ (11)
where + denotes max(, 0), and the water level is chosen to
satisfy=1
( )+ = max. (12)
Given a set of selected users = {1,...,}, the above precodingprocess attempts to eliminate the inter-user interference andmaximize the system sum-rate.
The problem of how to perform user selection (finding the set = {1,...,}) with a reasonable complexity for maximizing thesystem sum-rate will be addressed in the next section.
Mobile Communications - Chapter 3: Physical-layer transmissions Section 3.6: Space Division Multiple Access (SDMA) 12
OutlineI t d ti
Precoding classificationA l f li di
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IntroductionPrecoding
Scheduling (user selection)
An example of linear precodingPower allocation in ZF precodingPossible research problems
Precoding in LTE downlink transmissions
Data bits
ofuser 1
Channel
encoderInterleaver Layer
mapper
MQAM
mapper
MQAMmapper
Precoding
OFDMA
modulator
OFDMA
modulator
Precoding matrix
generator
Recovered data bits Channel decoder
Channel
Estimator
OFDMA
Demodulator
BER evaluator
ofuser 1
OFDMA
Demodulator
Channel State
Information (CSI)
MIMO
demapper
Limited feedback
link
User 1
Base Station (BS)
Data bits
ofuser N
Channel
encoderInterleaver Layer
mapper
MQAM
mapper
MQAM
mapper
WX
Y= W*X
BER evaluator
ofuser N
Multipath fading
channel
User N
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OutlineIntroduction Exhaustive selection
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IntroductionPrecoding
Scheduling (user selection)
Exhaustive selectionGreedy selection
Exhaustive selection
Given a precoding technique, scheduling (user selection) is to find aset of users among all active users to maximize the system sum-rate.
Obviously, the simple optimal method for user selection is exhaustivesearch but its complexity is impractically high as the number of usersis large.
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OutlineIntroduction Exhaustive selection
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IntroductionPrecoding
Scheduling (user selection)
Exhaustive selectionGreedy selection
Greedy selection
Greedy user selection algorithm1 Initialization: 0 = {1, 2,...,} is the set of all available users
indices0 = {} is the set of selected users initially assigned to a null set. = 0 stands for the number of selected users, initially set to zero.
0 = 0 is the system sum-rate of selected users, initially set to zero.2 Repetition: Assuming that selecting user in the set
maximizes the resulting sum-rate of the system called max.
= + 1If max < 1 or > or > go to Step 3 otherwise do:
= max = 1
{} (select one more user)
= 1{} (ignore user- in later consideration)
Go to Step 2.
3 Stop the user selection process and compute the ZF weightingvectors based on the composite channel matrix of selected users.
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