The EDF is optimal in many queuing models [25; 27; 28; 29; 30; 31]; however, in the presence of prioritized packets, it can be sub-optimal [32]. At the same time, applications differ in terms of their importance. Application priority normally reflects their importance. The priority is attached to the application's packet. Priority becomes a reward upon successful delivery of a packet. The reward is considered to benefit the network if the packet is delivered on time [33]. Scheduling mechanisms that consider both rewards and deadlines were presented in [34]. Another scheduling policy is based on the \(c\mu_{k}/\theta_{k}\)-rule presented in [35; 36; 37]. The \(c\mu_{k}/\theta_{k}\)-rule is based on having a finite number of queues, each queue presenting a possible packet's priority. The policy selects the queue to be served. The decision aims to reduce the summation of \(c\mu_{k}/\theta_{k}\) over the queues. In \(c\mu_{k}/\theta_{k}\), \(c\) presents a cost function of the queue, which is similar to a reward summation, \(\mu_{k}\) presents the \(k^{\text{th}}\) queue packets arrival rate, and \(\theta_{k}\) presents the abandon rate from the queue. The policy selection process takes into consideration the queue rewards, the arrival rate expectation, the abandon rate expectation, and the queue length. A similar approach to prioritization can be found in WLAN standard 802.11e [38], which implements a queue per priority and assigns different idle time bounds according to the queue priority. Recently, the authors developed a significantly improved solution for managing queues with both priorities and deadlines [32]. The above queuing theoretic papers discuss queue management policies independent of the underlying physical layer, assuming a single server with a deterministic or random service rate. In contrast, managing queues of packets aimed at independent users with different communication channels requires a cross-layer approach, as priorities and deadlines need to be measured against the effect of each user on other users grouped together. A simplified approach was presented in [39] where packets with priorities and deadlines were scheduled to static beams. It is the goal of this paper to propose a cross-layer approach for scheduling and beamforming. A typical application of the proposed approach would be for WLAN networks; for example, WLAN equipment supporting the IEEE 802.11 ac standard planned for a maximum throughput of at least 500 Mb/s for a single user and at least 1 Gb/s for multiple users [40; 41]. The IEEE 802.11 ac Multiple Access Control (MAC) layer extended the IEEE 802.11n standard to accommodate an MU-MIMO [42]. In order to increase the capacity, new bands were allocated, such that the IEEE 802.11 ac standard aims for a WLAN working at multi-user transmission at 60 GHz. This standard was defined to increase the throughput of next-generation WLANs via both analog and digital beamforming [43; 44; 45]. The 802.11 standard indeed contains a priority mechanism at the medium control level; however, these are insufficient to support delay-critical applications. In this paper, we use a scheduling policy combined with the ZF beamforming technique to improve systems with traffic under a hard real-time environment, as well as priorities. The remainder of this paper is organized as follows. Section 2 introduces the system model. Section 3 describes the RPS algorithm. Section 4 presents simulation results, and conclusions are drawn in Section 5.