User Grouping Sample Clauses

User Grouping. Enlarged cooperation areas have been introduced above to obtain sufficiently large penetration rates. Furthermore, the tortoise concept has helped to decouple adjacent CAs. Therefore, the analysis of the user grouping can be restricted here to a single CA comprising 9 cells - i.e. 3 sites a’ 3 cells - for an exemplary 4x2 MIMO system according to [3GPPTR1]. The maximum number of servable data streams per physical resource block NDS,max, is NDS,max ≤ min(Ntx,MNrx), where M is the number of UEs, so each cell might serve up to 4 data streams. This corresponds to 4*9=36 potential UEs (or UE antennas) per CA simultaneously served on each PRB. Eigenvalues in [dB] for 4 Tx eNBs and 1 Rx UE; Tx power adapted 20  [dB]0 -40 -60 -80 Mk, # of UEs in resource block Figure 5.7: Singular values of a channel matrix of dimension 36 x Mk, with 36 transmitters with fixed beams, as a function of the number of UEs Mk, that are randomly selected to co-exist in one resource block. Under these conditions, Figure 5.7 illustrates the typical singular value distribution of the total channel matrix from all 36 transmitters to M users, as being observed for an increasingly loaded system with M increasing. Serving more than k=13...18 UEs seems to be quite unreasonable due to the very high spread of singular values, with some singular values being extremely small. Additionally, the variation over frequency is small as indicated by the differently colored lines. SVD-based joint transmit- and receive beamforming would be the best transmission strategy (although it can not be implemented for the here considered non-cooperative multi-receiver case). Its performance would be severely limited by a large singularvalue spread of the total channel matrix. Beamformer design would be sensitive and difficult and only a minority of the singular values could contribute meaningfully to the sum throughput. Given these results, it could be concluded that attainable gains for JP CoMP indeed seems to have a fundamental limit. However, there is already a useful hint in Figure 5.7. Serving at most 2 instead of 3, or at most 3 instead of 4 UEs per cell would be accompanied by about 10-20dB lower spread of singular values. The number of served users per 9 cells would then drop from above 18 to max 18 and from above 27 to max 27 UEs. This would result in large reductions of the singular value spreads of the channel matrices. The conclusion is that loading one single extra UE into one single cell might already...