Qasim Zeeshan Ahmed

On consideration of content preference and sharing willingness in D2D assisted offloading

Device-to-device (D2D) assisted offloading heavily depends on the participation of human users. The content preference and sharing willingness of human users are two crucial factors in the D2D assisted offloading. In this paper, with consideration of these two factors, the optimal content pushing strategy is investigated by formulating an optimization problem to maximize the offloading gain measured by the offloaded traffic. Users are placed into groups according to their content preferences and share content with intergroup and intragroup users at different sharing probabilities. Although the optimization problem is nonconvex, the closed-form optimal solution for a special case is obtained, when the sharing probabilities for intergroup and intragroup users are the same. Furthermore, an alternative group optimization (AGO) algorithm is proposed to solve the general case of the optimization problem. Finally, simulation results are provided to demonstrate the offloading performance achieved by the optimal pushing strategy for the special case and AGO algorithm. An interesting conclusion drawn is that the group with the largest number of interested users is not necessarily given the highest pushing probability. It is more important to give high pushing probability to users with high sharing willingness.

Network-Assisted D2D Discovery Method by Using Efficient Power Control Strategy

Neighbour discovery is an important process in device-to-device (D2D) communications. In cellular networks, D2D discovery signals are multiplexed with cellular signals causing in-band emission interference (IEI). IEI degrades D2D user equipments (DUEs) discovery range and cellular user equipments (CUEs) throughput. In this paper, a new discovery method is proposed by applying power control strategy. In this method, DUEs are arranged into two groups depending on whether the received power of a reference signal sent from the based station (BS) to DUEs is larger than a given threshold. A high received reference signal at a DUE indicates strong IEI which may be caused by the DUE to the BS. Then, Group-1 contains DUEs which cause low IEI while Group-2 contains DUEs which cause severe IEI. A new strategy to mitigate IEI is proposed for Group-2. Firstly, CUEs send scheduling information in predefined blocks. Secondly, DUEs estimate the symbols which are orthogonal to CUE. This will assist DUEs to boost their discovery transmission power, reduce IEI and improve the discovery performance.

Capacity Maximisation for Hybrid Digital-to-Analog Beamforming mm-Wave Systems

Millimetre waves (mm-Waves) with massive multiple input and multiple output (MIMO) have the potential to fulfill fifth generation (5G) traffic demands. In this paper, a hybrid digital-to-analog (D-A) precoding system is investigated and a particle swarm optimisation (PSO) based joint D-A precoding optimisation algorithm is proposed. This algorithm maximises the capacity of the hybrid D-A mm-Wave massive MIMO system. The proposed algorithm is compared with three known hybrid D-A precoding algorithms. The analytical and simulation results show that the proposed algorithm achieves higher capacity than the existing hybrid D-A precoding algorithms.

Hybrid digital-to-analog precoding design for mm-wave systems

Hybrid digital-to-analog (D-A) precoding is a promising technology to reduce the number of radio frequency (RF) chains in a millimetre-wave (mm-Wave) multiple-input multiple-output (MIMO) system. To reap the full scale benefits of the hybrid D-A precoding, in this paper, two algorithms are proposed to maximise the capacity of the hybrid D-A mm-Wave MIMO system. The first algorithm is based on the principle of manifold optimisation (MO). The second algorithm operates on particle swarm optimisation (PSO). These two algorithms are compared with three existing hybrid D-A precoding algorithms in the literature. The simulation results show that the proposed algorithms achieve higher capacity than the existing hybrid D-A precoding algorithms with lower computational complexity.

Hybrid Digital-to-Analog Beamforming for Millimeter-Wave Systems with High User Density

Millimeter-wave (mm-Wave) systems with

Hybrid Digital-to-Analog Beamforming Approaches to Maximise the Capacity of mm-Wave Systems

\mbox{hybrid digital-to-analog beamforming (D-A BF)}

Video Content Delivery Using Multiple Devices to Single Device Communications

have the potential to fulfill 5G traffic demands. The capacity of mm-Wave systems is severely limited as each radio frequency (RF) transceiver chain in current base station (BS) architectures support only a particular user. In order to overcome this problem when high density of users are present, a new algorithm is proposed in this paper. This algorithm operates on the principle of selection combining (SC). This algorithm is compared with the state of the art

Transmit antenna selection for massive MIMO: A knapsack problem formulation

\mbox{hybrid D-A BF}

Content Offloading via D2D Communications with the Impact of User Preferences and Selfishness

. The simulation results show that our proposed

Measurement, simulation and optimization of wideband log-periodic antennas

\mbox{hybrid D-A BF}