nly be used once). Out of the remainder potential allocations between TRP and UE (across all remainder repeater path options) find the one that gives the next (next) highest possible throughput. Assign time/frequency resources to this UE and remove the TRP and repeater path to this UE from further consideration (each allocation can only be used once). Continue this process until no more UE can be served by an available TRP/repeater path. This greedy scheme is often used in real applications even though it is intuitively under- stood not to necessarily give the best possible solution. Linear programming can be used to find a mathematically optimum solution to the problem. Software optimization techniques Theoretically speaking, the base station can provide time, frequency, and spatial access to a new set of users every possible scheduling instant (TTI, slot, ...). This means that the steps outlined in section "Architectural framework for the base station wireless scheduler algo- rithm" need to be implemented in (quasi) real time. In addition, as the number of (active) users in the base station increases and the number of scheduled users increases, the com- plexity of the scheduling algorithm goes up. As a result, software optimization of algorithmic schedulers becomes important. Note that the algorithms we described earlier include specific math-centric: PF scheduling. Using the fact that the actual value of the UE priority metric to be sorted to is not important to the arg(max) function, rather than only the relative value of the metric compared to other evaluated UEs, this function can be simplified for real-time computation 258 Open Radio Access Network (O-RAN) Systems Architecture and Design as follows: j = log (AaBBCY) = log (Ad)+log(BB)+log(Cy) = = a log (A) + B log (B) + r log (C). This implementation is regular and highly parallelizable by performing calculations on A, B, C, in parallel using vectorized operations. Assuming the input parameters are structured in a single instruction multiple data (SIMD)-fr