Random Beam-Based Non-Orthogonal Multiple Access for Low Latency K-User MISO Broadcast Channels

In this paper, we propose random beam-based non-orthogonal multiple access (NOMA) for low latency multiple-input single-output (MISO) broadcast channels, where there is a target signal-to-interference-plus-noise power ratio (SINR) for each user. In our system model, there is a multi-antenna transmitter with its own single antenna users, and the transmitter selects and serves some of them. For low latency, the transmitter exploits random beams, which can reduce the feedback overhead for the channel acquisition, and each beam can support more than a single user with NOMA. In our proposed random beam-based NOMA, each user feeds a selected beam index, the corresponding SINR, and the channel gain, so it feeds one more scalar value compared to the conventional random beamforming. By allocating the same powers across the beams, the transmitter independently selects NOMA users for each beam, so it can also reduce the computational complexity. We optimize our proposed scheme finding the optimal user grouping and the optimal power allocation. The numerical results show that our proposed scheme outperforms the conventional random beamforming by supporting more users for each beam.

Random Beamforming in Mobile mmWave Systems: Performance Evaluation and Parameters Optimization

Random Beamforming (RBF) is considered one of the most promising beamforming techniques especially for Massive MIMO mmWave systems. It has been proven to achieve optimal sumrate capacity for downlink MIMO systems for many applications. In this paper, the RBF is implemented in a mmWave MIMO systems with mobile users and the effect of this mobility is studied. Beside that, some parameters of the system have been optimized for different realistic scenarios. The mathematical derivation of the system model and the simulation using some practical values have been conducted. The resulted degradation in system throughput as a consequence of beamforming outage that results from users mobility is calculated. Many factors that affect the system throughput were considered in the derivation. The second part of the paper is going a further step in optimizing the network parameters for different operation scenarios. These parameters include the frame duration and beam width. Taking in consideration that the outage probability is a Convex optimization problem, the optimal values of these parameters were derived. for the walking and running users cases.

A Pseudo-Random Beamforming Technique for Improving Physical-Layer Security of MIMO Cellular Networks

In this paper, we propose a pseudo-random beamforming (PRBF) technique for improving physical-layer security (PLS) in multiple input multiple output (MIMO) downlink cellular networks consisting of a legitimate base station (BS), multiple legitimate mobile stations (MSs) and potential eavesdroppers. The legitimate BS can obtain available potential eavesdroppers’ channel state information (CSI), which is registered in an adjacent cell. In the proposed PRBF technique, the legitimate BS pseudo-randomly generates multiple candidates of the transmit beamforming (BF) matrix, in which each transmit BF matrix consists of multiple orthonormal BF vectors and shares BF information with legitimate MSs before data transmission. Each legitimate MS generates receive BF vectors to maximize the receive signal-to-interference-plus-noise (SINR) for all pseudo-randomly generated transmit beams and calculates the corresponding SINR. Then, each legitimate MS sends a single beam index and the corresponding SINR value of the BF vector that maximizes the received SINR for each BF matrix since a single spatial stream is sent to each legitimate MS. Based on the feedback information from legitimate MSs and the CSI from the legitimate BS to eavesdroppers, the legitimate BS selects the optimal transmit BF matrix and the legitimate MSs that maximizes secrecy sum-rate. We also propose a codebook-based opportunistic feedback (CO-FB) strategy to reduce feedback overhead at legitimate MSs. Based on extensive computer simulations, the proposed PRBF with the proposed CO-FB significantly outperforms the conventional random beamforming (RBF) with the conventional opportunistic feedback (O-FB) strategies in terms of secrecy sum-rate and required feedback bits.