Motivated by the emerging standards for indoor pico-cellular wireless systems, such as the Bluetooth, we propose and study the scheduling policies for master driven time division duplex (TDD) wireless networks. In these networks, the frequency band is divided into time slots, and each end (i.e., master or slave) takes turns in using the time slots. In Bluetooth, a slave transmits packets in the reverse slot only after the master polls the slave in a forward slot (by sending data to it). The conventional scheduling policies such as round robin do not perform well in these systems as they are not suited to the tight coupling of the uplink-downlink. We propose new scheduling policies, (i) the priority scheme, and, (ii) the K-fairness scheme that utilize the state at the master and slaves to schedule the TDD slots effectively. Active slaves are differentiated based upon the binary information (i.e., the presence or absence of packets in a slave queue) about the master-slave queue pairs. The priority scheme achieves high throughput as compared to the packet-by-packet generalized processor sharing (PGPS) based policies while guaranteeing a minimal service to each active slave while the K-fairness policy is characterized by a tight fairness bound as well as high system throughput. We then extend these policies for scheduling variable size data in the presence of voice. Further, since Bluetooth supports variable size data packets (1, 3 or 5 slots) on the same connections, the segmentation and reassembly (SAR) can significantly impact scheduling of data packets by varying packet size distribution. We propose an intelligent SAR policy (ISAR) and compare it with the naive random-SAR in which the data packet sizes (i.e., 1, 3 or 5) are assigned probabilistically. ISAR adapts MAC packet size at the master and slave queues depending on the data arrival rates at both the queues.