Spectral, Energy and Computation Efficiency in Future 5G Wireless Networks

Wireless technology has revolutionized the way people communicate. From first generation, or 1G, in the 1980s to current, largely deployed 4G in the 2010s, we have witnessed not only a technological leap, but also the reformation of associated applications. It is expected that 5G will become commercially available in 2020. 5G is driven by ever-increasing demands for high mobile traffic, low transmission delay, and massive numbers of connected devices. Today, with the popularity of smart phones, intelligent appliances, autonomous cars, and tablets, communication demands are higher than ever, especially when it comes to low-cost and easy-access solutions. Existing communication architecture cannot fulfill 5G’s needs. For example, 5G requires connection speeds up to 1,000 times faster than current technology can provide. Also, from transmitter side to receiver side, 5G delays should be less than 1ms, while 4G targets a 5ms delay speed. To meet these requirements, 5G will apply several disruptive techniques. We focus on two of them: new radio and new scheme. As for the former, we study the non-orthogonal multiple access (NOMA) and as for the latter, we use mobile edge computing (MEC). Traditional communication systems allow users to communicate alternatively, which clearly avoids inter-user interference, but also caps the connection speed. NOMA, on the other hand, allows multiple users to transmit simultaneously. While NOMA will inevitably cause excessive interference, we prove such interference can be mitigated by an advanced receiver side technique. NOMA has existed on the research frontier since 2013. Since that time, both academics and industry professionals have extensively studied its performance. In this dissertation, our contribution is to incorporate NOMA with several potential schemes, such as relay, IoT, and cognitive radio networks. Furthermore, we reviewed various limitations on NOMA and proposed a more practical model. In the second part, MEC is considered. MEC is a transformation from the previous cloud computing system. In particular, MEC leverages powerful devices nearby and instead of sending information to distant cloud servers, the transmission occurs in closer range, which can effectively reduce communication delay. In this work, we have proposed a new evaluation metric for MEC which can more effectively leverage the trade-off between the amount of computation and the energy consumed thereby. A practical communication system for wearable devices is proposed in the last part, which combines all the techniques discussed above. The challenges for wearable communication are inherent in its diverse needs, as some devices may require low speed but high reliability (factory sensors), while others may need low delay (medical devices). We have addressed these challenges and validated our findings through simulations

Energy Efficient SWIPT: From Fully-Digital to Hybrid Analog-Digital Beamforming

CCBY Simultaneous wireless information and power transfer (SWIPT) enables the transmission of information symbols and energy simultaneously. In this paper, we study the MIMO SWIPT systems with limited RF chains at the base station. We focus on the scenario where there is one information decoder with a target SINR and several separate energy harvesting receivers with harvested energy thresholds. To motivate our energy-efficient hybrid analog-digital beamforming strategy, the fully-digital power minimization problem is firstly analyzed, where we mathematically show that the optimal beamformer consists of only the information beamformer, and derive closed-form beamformers for a number of special cases. Based on this result, we further consider hybrid beamforming and propose an iterative scheme where the analog and digital beamformers are alternately updated. For the proposed scheme, in each iteration we design the analog beamformer by minimizing the difference between the fully-digital beamformer and the hybrid beamformer. Based on our above analysis for fully-digital case, the optimal solution for analog beamformer can be obtained via a geometrical interpretation. We further design the robust beamformers for the proposed schemes, when only imperfect channel state information (CSI) is available. The numerical results show that the proposed iterative designs achieve a close-to-optimal performance with significant gains in the total power consumption over fully-digital SWIPT

Interference Exploitation Based Secure Transmission for Distributed Antenna Systems

Distributed antenna (DA) is considered as a strong alternative to conventional centralized multiple-input multiple-output (MIMO), to provide a greener and user-centric network structure. However, physical layer (PHY) security becomes more challenging in DA systems because of the proximity to the transmitters. In this paper, we jointly optimize DA activation/deactivation and secure precoding to minimize the total power consumption, subjected to legitimate user's (LU) quality-of-service (QoS) and PHY security constraints against potential eavesdroppers (Eves). A practical scenario is considered, where channel state information (CSI) of all the nodes can only be imperfectly obtained. In the presence of infinite probabilities of CSI uncertainties, a deterministic robust based algorithm is designed to always satisfy LU's QoS requirement and address PHY security constraints against Eves. Moreover, essentially different from existing artificial noise (AN)-aided secure transmission schemes, where AN' leakage effect at LU needs to be suppressed, we utilize AN as a beneficial element at LU end while keeping it destructive at potential Eves. Simulation results verify that, the proposed algorithm incurs much lower power consumption compared to its benchmarks, thanks to the additional degrees of freedom of antenna selection and utilizing constructive AN. Last but not least, by adaptively facilitating DA activation/deactivation, the proposed algorithm addresses a user-centric network structure, which is more flexible over the conventional centralized MIMO systems