approximations. Then, aiming for improving the system sum rates, a pair of $K^*$-based low-complexity user selection methods are proposed, namely the $K^*$-based random user selection ($K^*$-RUS) and the $K^*$-based location-dependant user selection ($K^*$-LUS). For $K^*$-RUS, $K^*$ UEs are randomly selected for simultaneous data transmissions at each time slot. The system sum rates are improved with an appropriate configuration of $K^*$. Meanwhile, the fairness among UEs is guaranteed as a result of the random selection. For the $K^*$-LUS scheme, $K^*$ UEs nearest to the BS are selected for data transmission, which may achieve higher sum rate performance than $K^*$-RUS.

Notably, our schemes exhibit two fundamental differences as compared with the conventional user selection schemes. First, unlike the conventional SUS that requires the instantaneous CSI of small-scale fading (SSF), our schemes only need long-term CSI. Second, rather than emphasizing which UEs should be selected for improving system performance, the proposed user selection schemes mainly focus on how many UEs should be selected for simultaneous transmissions. Thanks to these differences, we bypass the complicated online computations regarding the sum rates and the selection metric, which are often inevitable in the conventional schemes. Therefore, the online computational complexity of the proposed two schemes is 