Ideal Scheduler Sample Clauses

Ideal Scheduler. The goal of an ideal scheduler would be to serve as many UEs as possible for a given set of spatial degree of freedom, with the highest possible throughput. This means being able to use a high-rate modulation and coding scheme (MCS), without too high packet error rate. In case of LTE Advanced, the highest modulation scheme is 64QAM. For evaluation of some main scheduling effects, we will below use a 4x2 MIMO system, i.e. each cell has 4 Tx- and each UE 2 Rx-antennas. Otherwise the simulation parameters are as in Table 5.1. Optimization of CoMP scheduling represents – similar as for MU-MIMO scheduling - a multi dimensional non-convex optimization problem. The goal is, in general, to maximize the spectral efficiency while keeping a predefined degree of fairness or, even better, to improve the degree of fairness as this is one of the main ARTIST4G goals. This is equivalent to maximizing the sum rate over all NDS simultaneously served data streams per CA, constrained by the intended degree of fairness. For JP CoMP, the following aspects have to be taken into account: - Setup of cooperation areas that allow a high penetration rate of user-centric served UEs - User grouping that provides a high mutual orthogonality for users who share each subcarrier or physical resource block PRBi. This means, in particular, that different users should have their strongenst channels to different transmit antennas or beams. - Allocation of numbers of streams per UE, per cell and in the end per CA. This is a trade- off because when increasing the number of streams per cooperation area, NDS, the goodput (GP) per stream will typically decrease. (Note that GP counts the throughput of correctly received retransmission blocks and therefore represents the throughput excluding the overhead for hybrid ARQ retransmissions.) - For each potential user group, the optimum cooperation-area wide precoder matrix W and UE individual beamformers or filters Fk  CNUE x 1 – including phase and power - have to be derived, which in general is a non convex optimization problem by itself. - Scheduling of UE sets to PRBs or subcarriers, to maximize overall capacity by exploiting multi- user scheduling gains, while ensuring at least proportional fairness for all UEs. Taking all these scheduling dimensions into account, one can formulate the overall optimization problem for maximum spectral efficiency SEmax as follows: XX  xxx(xxx(  XX(XXxxx,XXxxx ,Xxxx,Xxxx , PRB ) / N ) (5.2.1) max nDS NPRB b 1..K 1.....