1) The document presents a dynamic subcarrier allocation (DSA) scheme called DSA-ESINR that uses estimated signal-to-interference-plus-noise ratio (ESINR) as a metric to allocate subcarriers in a correlated space-division multiple access (SM-OFDMA) system.
2) Simulation results show that DSA-ESINR can minimize the effect of self-interference and improves subcarrier allocation as signal-to-noise ratio increases compared to a baseline DSA scheme.
3) Future work is proposed to study different correlation scenarios, apply adaptive modulation and coding, and analyze self-interference between space-time block coding and spatial multiplexing
3. 3
Correlation in MIMO
Occurs due to: 12
RBS=0.0,RMS=0.0
RBS=0.4,RMS=0.4
10
RBS=0.5,RMS=0.5
RBS=0.0,RMS=0.9
8 RBS=0.9,RMS=0.0
capacity (bps/Hz)
• antenna location/spacing
RBS=0.9,RMS=0.9
6 RBS=1.0,RMS=1.0
• lack of scatterers 4
• angular spread. 2
0
-10 -5 0 5 10 15 20
SNR (dB)
Resulting in self-interference.
Retransmissions and equalisation do not
improve the BER performance.
4. 4
Self-Interference
MIMO only works when the channel is in
low correlation.
In practice:
h’
s0 h’ r0
r0=r1=h’(s0+s1)
BS h’ MS
Scenario: all spatial layers
`
h’ are fully correlated
s1 r1
Mathematically:
If h’ coefficients are correlated, then [H] is
[S] =[H]-1[R] ill-conditioned matrix and difficult to revert
5. 5
SINR Metric
As the performance metric to determine the
subcarrier allocation.
MMSE filter
q= spatial layer Main spatial layer
2
Gk H k qq Es
q
ESINRk 2 2 2
Gk H k qj, j q Es Gk qq
Gk qj, j q
N
Knowledge of
self-interference
k= subcarrier index
6. 6
DSA-SINR
Involves sorting, comparing and simple
arithmetic.
Ranks users from lowest to highest SINR.
Fairness: Allow poor users to have the next
‘best’ subcarriers.
Prevents users from sharing the same
subcarrier with the adjacent layer (interferer).
7. 7
System Model X1 Tx1 Rx1
H1
X1 With Index 1
Transmitter at Base Station OFDM H3
X1
User k Input With Index 2
Data Scrambling/ FEC/ Symbol Serial to Parallel& DSA
H2 Rx2
X1X2 Puncturing/ Interleaving Mapping Spatial Multiplexing mapping X2 Tx2
With Index 3
H4
X2 X2 OFDM
With Index 4
Uplink process Index 1 2 3 4
Downlink process Index 4
ESINR and channel
Index 1 DSA
Index 2
} DSA-ESINR gain feedback from
other users
Scheme
Index 3
Index 2
Index 3 Index 1
Index 4 } DSA-Scheme 1
ESINR1
ESINR2
[ H3 ]
[ H4 ]
ESINR
calculation
Receiver at Mobile Station k [ H1 H3 ] [ H2 H4 ]
S1 Y1 DSA
OFDM
User k Deinterleaving/ S1 S2 Parallel to MMSE [ H1 H3 ] Demapping
Symbol
Output Depuncturing/ Viterbi Serial& De- Linear
Demapping
Data Decoding/ Descrambling Multiplexing Detection Y2 DSA
S2
[ H2 H4 ] Demapping OFDM
8. 8
Simulation Setup
Nsub= 768, NFFT= 1024 for 16 users, 48
subcarriers per user
3GPP-SCM ‘Urban Micro’:
1
Rms delay spread= 251 ns
0.9
0.8
0.7
Normalised power
Excess delay= 1200 ns
0.6
0.5
0.4
0.3
2000 i.i.d Rayleigh
0.2
0.1
200 300 400 500 600 700 800 900 1000
Excess delay (ns)
Six MCS schemes, consists of BPSK,
QPSK, 16-QAM and 64-QAM with ½ or ¾
coding rate
9. 9
Correlation Model
Kronecker product, RMIMO=RMS RBS
‘Default’ = generated by the channel model,
i.e. practical scenario
‘Forced’ = ideal channel environment
Correlation Coefficient
Correlation Modes
RBS RMS
‘Default’ 0.45 0.32
‘Forced’ 0.00 0.00
11. 11
Conclusions
SINR with combination of DSA can minimise
the effect of self-interference.
Allocation improves as SNR increase.
Future works:
Consider different case of correlation scenarios,
e.g. moderate, full correlation
Apply adaptive MCS on the BS Tx antenna
Study the effect of self-interference between STBC
and SM