Please enable JavaScript.
Coggle requires JavaScript to display documents.
Comparision of SCM and Onering channel modelling method - Coggle Diagram
Comparision of SCM and Onering channel modelling method
Section 5: Simulation results and discussion
2 kinds of combination of the spatial channel-coding and signal detection
SFBC-MMSE
Perform better than SFBC-VBLAST-ZF
Fewer SERs in most case of different correlation coefficent
Lower algorithm complexity
O(n^5)
Lower flops in the producers
74 flops with the order of 2x2 anttenas
Requirements of finding inverse matrices
Effection with ORM and SCM channel simulator
Not so much difference when we change coeff
Coeff: 0.1, SNR = 18dB
SCM SERs: 0.0011
ORM SERs: 0.0016
Coeff: 0.9, SNR = 18dB
SCM SERs: 0.077
ORM SERs: 0.0775
SFBC-VBLAST-ZF
Perform worse than SFBC-MMSE
More SERs in most case of different correlation coefficent
Higher algorithm complexity
O(n^7)
Higher flops in the producers
142 flops with the order of 2x2 anttenas
The same calculation complexity
Some discussions
Higher correlation coefficent, the lower the system's performance
Shown in figure
Highly corelated channel
More active users
System degradtion
Uncorelated channel
More active users
More active users
System performance better
Fully exploited by the DCA mechanism
Introduction
SCM Model (PSM)
Onering Model (GBSM)
Both Have Closed - form Correlation Functions
SIMULATION SCENARIOS
Perpendicular Orientation BS Array ⊥ MS - BS
Closely Matched Correlation Results
RECOMMENDATIONS
Onering: Simple
MIMO - OFDMA System over LTE - A Channels
1 more item...
SCM: Better Performance
Other Orientations
Similar Shape but Not Identical
Section 2: Spatial-Temporal Correlation of MIMO Channel
SCM method
Proposed by 3GPP.
MIMO channel using multipath propagation.
Uses angles of arrival and angles of departure with multiple sub-paths.
Analyze spatial & temporal signal correlation across antennas.
Mathematical Formulas: CIR formula, Fourier transform.
OneRing Channel Model Method
Scatterers around MS in a ring.
Signals = reflections from scatterers.
Correlation depends only on MS–BS array geometry.
Special case: 2×2 MIMO (no freq offset): correlation = geometry + Doppler.
Section 3: Performance comparision SCM method to the Onering channel model method
Spatial-temporal correlation properties of the SCM and the Onering channel
simulators
Simulation results (correlation functions vs antenna spacing) show that both models produce similar results, but SCM provides more accurate details, especially in complex antenna arrangements.
Mathematical derivations of spatial correlation functions are given for both methods.
Case studies with different antenna orientations demonstrate that SCM better captures variations, whereas Onering can be sufficient for approximate modeling.
SCM incorporates additional parameters (AoA, AoD) for more precise representation of scattering, while Onering is simpler, with scatterers distributed on a ring around the receiver.
frequency correlation functions (FCF) of MIMO channels obtained from the SCM and Onering channel models.
Consequently, the correlation properties of the two models are considered closely matched under the same conditions.
Simulation results indicate that both models give very similar FCF behavior.
In frequency-selective wideband channels, the FCF is important to evaluate how signals at different frequencies are correlated.
The overall shapes match well, though local maxima and minima differ slightly.
Section 4: Simulated MIMO-OFDMA System (2x2)
Frequency Resource Allocation
BS estimates the channel → computes SNR.
Select subcarriers with maximum SNR and assign them to corresponding users.
Dynamic Channel Allocation (DCA)
System Configuration
2x2 MIMO-OFDMA: 2 transmit antennas (MS), 2 receive antennas (BS)
Q users (MS).
Simulation Assumptions
Perfect time and frequency synchronization (TX & RX).
Multi-user interference is neglected.
Perfect CSI (Channel State Information) at the BS (receiver).
Special antenna arrangement (Figure 3).