Two-Stage Subspace Constrained Precoding in Massive MIMO Cellular Systems

We propose a subspace constrained precoding scheme that exploits the spatial channel correlation structure in massive MIMO cellular systems to fully unleash the tremendous gain provided by massive antenna array with reduced channel state information (CSI) signaling overhead. The MIMO precoder at each base station (BS) is partitioned into an inner precoder and a Transmit (Tx) subspace control matrix. The inner precoder is adaptive to the local CSI at each BS for spatial multiplexing gain. The Tx subspace control is adaptive to the channel statistics for inter-cell interference mitigation and Quality of Service (QoS) optimization. Specifically, the Tx subspace control is formulated as a QoS optimization problem which involves an SINR chance constraint where the probability of each user's SINR not satisfying a service requirement must not exceed a given outage probability. Such chance constraint cannot be handled by the existing methods due to the two stage precoding structure. To tackle this, we propose a bi-convex approximation approach, which consists of three key ingredients: random matrix theory, chance constrained optimization and semidefinite relaxation. Then we propose an efficient algorithm to find the optimal solution of the resulting bi-convex approximation problem. Simulations show that the proposed design has significant gain over various baselines.Comment: 13 pages, accepted by IEEE Transactions on Wireless Communication

A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead

Physical layer security which safeguards data confidentiality based on the information-theoretic approaches has received significant research interest recently. The key idea behind physical layer security is to utilize the intrinsic randomness of the transmission channel to guarantee the security in physical layer. The evolution towards 5G wireless communications poses new challenges for physical layer security research. This paper provides a latest survey of the physical layer security research on various promising 5G technologies, including physical layer security coding, massive multiple-input multiple-output, millimeter wave communications, heterogeneous networks, non-orthogonal multiple access, full duplex technology, etc. Technical challenges which remain unresolved at the time of writing are summarized and the future trends of physical layer security in 5G and beyond are discussed.Comment: To appear in IEEE Journal on Selected Areas in Communication

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

Large System Analysis of the Energy Consumption Distribution in Multi-User MIMO Systems with Mobility

In this work, we consider the downlink of a single-cell multi-user MIMO system in which the base station (BS) makes use of $N$ antennas to communicate with $K$ single-antenna user equipments (UEs). The UEs move around in the cell according to a random walk mobility model. We aim at determining the energy consumption distribution when different linear precoding techniques are used at the BS to guarantee target rates within a finite time interval $T$. The analysis is conducted in the asymptotic regime where $N$ and $K$ grow large with fixed ratio under the assumption of perfect channel state information (CSI). Both recent and standard results from large system analysis are used to provide concise formulae for the asymptotic transmit powers and beamforming vectors for all considered schemes. These results are eventually used to provide a deterministic approximation of the energy consumption and to study its fluctuations around this value in the form of a central limit theorem. Closed-form expressions for the asymptotic means and variances are given. Numerical results are used to validate the accuracy of the theoretical analysis and to make comparisons. We show how the results can be used to approximate the probability that a battery-powered BS runs out of energy and also to design the cell radius for minimizing the energy consumption per unit area. The imperfect CSI case is also briefly considered.Comment: 8 figures, 2 tables, to appear on IEEE Transactions on Wireless Communication

Optimal Beamforming for Physical Layer Security in MISO Wireless Networks

A wireless network of multiple transmitter-user pairs overheard by an eavesdropper, where the transmitters are equipped with multiple antennas while the users and eavesdropper are equipped with a single antenna, is considered. At different levels of wireless channel knowledge, the problem of interest is beamforming to optimize the users' quality-of-service (QoS) in terms of their secrecy throughputs or maximize the network's energy efficiency under users' QoS. All these problems are seen as very difficult optimization problems with many nonconvex constraints and nonlinear equality constraints in beamforming vectors. The paper develops path-following computational procedures of low-complexity and rapid convergence for the optimal beamforming solution. Their practicability is demonstrated through numerical examples

Robust Linear Precoder Design for Multi-cell Downlink Transmission

Coordinated information processing by the base stations of multi-cell wireless networks enhances the overall quality of communication in the network. Such coordinations for optimizing any desired network-wide quality of service (QoS) necessitate the base stations to acquire and share some channel state information (CSI). With perfect knowledge of channel states, the base stations can adjust their transmissions for achieving a network-wise QoS optimality. In practice, however, the CSI can be obtained only imperfectly. As a result, due to the uncertainties involved, the network is not guaranteed to benefit from a globally optimal QoS. Nevertheless, if the channel estimation perturbations are confined within bounded regions, the QoS measure will also lie within a bounded region. Therefore, by exploiting the notion of robustness in the worst-case sense some worst-case QoS guarantees for the network can be asserted. We adopt a popular model for noisy channel estimates that assumes that estimation noise terms lie within known hyper-spheres. We aim to design linear transceivers that optimize a worst-case QoS measure in downlink transmissions. In particular, we focus on maximizing the worst-case weighted sum-rate of the network and the minimum worst-case rate of the network. For obtaining such transceiver designs, we offer several centralized (fully cooperative) and distributed (limited cooperation) algorithms which entail different levels of complexity and information exchange among the base stations.Comment: 38 Pages, 7 Figures, To appear in the IEEE Transactions on Signal Processin