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In this paper, a radio resource allocation and scheduling algorithm for multi-user MISO-OFDMA systems with downlink zero-forcing beamforming is proposed to efficiently support the diverse quality of service (QoS) requirements of heterogeneous services. According to the channel state information (CSI) and the queue state information (QSI), the proposed algorithm dynamically assigns subcarriers and selects the users on the same subcarrier. The goal of the algorithm is to maximize the system throughput by fully exploiting multiuser diversity gain in space, time, and frequency domain while guaranteeing the QoS for real time (NT) services and non-real time (NRT) services with minimum data rate requirement. From the system level simulation, it shows that the proposed algorithm significantly improves the system performances.

To meet the increasing demand of wireless services associated with the scarcity of the radio spectrum and the trend to provide end to end quality of service (QoS), on the one hand advanced technologies that harness the available resource efficiently should be developed, on the other hand the collaboration of different layers such as physical (PHY) layer and medium access control (MAC) layer is needed. In this paper, we propose a joint space-frequency-power scheduling algorithm (JSFP) for real time service in multiuser cellular MIMO-OFDM system which jointly optimizes the subcarrier, bit and power allocation in the PHY layer along with the scheduling in the MAC layer to exploit the multiuser diversity. This algorithm considers both the user equipments (UE)' QoS requirements (such as packet delay and packet loss ratio) and the UEs' channel conditions and includes three parts: packet scheduling, subcarrier allocation and antenna selection, power allocation. Numerical results show that the proposed algorithm achieves significant system performance improvement compared with the conventional methods.

This paper considers zero-forcing beamforming (ZFBF) at the transmitter for a downlink multi-user multiple-input single-output (MU-MISO) system. Transmit beamforming as a simple yet efficient technique can exploit the benefits of multiple transmit antennas provided that the instantaneous channel state information (CSI) is known at both sides of transmission link. In order to have such improvements, the CSI at both link ends must be updated timely. However, the updating process is always subject to non-ideality such as feedback delay and estimation error, which destroy the orthogonality of the parallel channels and cause the mismatch between the actual channel characteristic and the modulation matrices used. By analyzing the effect of feedback delay on the performance of capacity with spectral efficiency and outage probability as benchmarks, we design a cross-layer scheduler combining semi-orthogonal user selection (SUS) algorithm at the medium access control (MAC) layer to reduce the inter-user interferences and an adaptive proportional weighted modulation (APWM) algorithm at the physical (PHY) layer to address the problem of such mismatch, and compare the proposed scheduler (APWM-SUS) with the naive scheduler (the rate modulation matrices designed for the perfect CSI). Finally, simulation and numerical results reveal significant gains and high feasibility.

Multiple input multiple output (MIMO) system has been recognized as a promising candidate for future wireless communication. The adaptive modulation which adjusts the transmitter parameters, such as modulation order, transmit power or coding rate, to time-varying channel conditions has been applied to MIMO system and shown a good average spectral efficiency performance. In this paper, the channel estimation error (CEE)'s effect on the effective spectral efficiency of the MIMO system with zero-forcing receiver is investigated, when the transmitter adopts adaptive modulation. To reduce CEE's negative effect, a dynamic adaptive modulation scheme is proposed. This scheme can dynamically adjust the signal to noise ratio (SNR) thresholds for the different modulation orders according to the feedbacks from the receiver. The numerical results show that the system performance of the proposed scheme is near optimal with acceptable implementation complexity.