Kai-Kit Wong

Generalized multiuser orthogonal space-division multiplexing

This paper addresses the problem of performing orthogonal space-division multiplexing (OSDM) for downlink, point-to-multipoint communications when multiple antennas are utilized at the base station (BS) and (optionally) all mobile stations (MS). Based on a closed-form antenna weight solution for single-user multiple-input multiple-output communications in the presence of other receiver points, we devise an iterative algorithm that finds the multiuser antenna weights for OSDM in downlink or broadcast channels. Upon convergence, each mobile user will receive only the desired activated spatial modes with no cochannel interference. Necessary and sufficient conditions for the existence of OSDM among the number of mobile users, the number of transmit antennas at the BS, and the number of receive antennas at the MS, are also derived. The assumption for the proposed method is that the BS knows the channels for all MSs and that the channel dynamics are quasi-stationary.

Robust Cognitive Beamforming With Bounded Channel Uncertainties

This paper studies the robust beamforming design for a multi-antenna cognitive radio (CR) network, which transmits to multiple secondary users (SUs) and coexists with a primary network of multiple users. We aim to maximize the minimum of the received signal-to-interference-plus-noise ratios (SINRs) of the SUs, subject to the constraints of the total SU transmit power and the received interference power at the primary users (PUs) by optimizing the beamforming vectors at the SU transmitter based on imperfect channel state information (CSI). To model the uncertainty in CSI, we consider a bounded region for both cases of channel matrices and channel covariance matrices. As such, the optimization is done while satisfying the interference constraints for all possible CSI error realizations. We shall first derive equivalent conditions for the interference constraints and then convert the problems into the form of semi-definite programming (SDP) with the aid of rank relaxation, which leads to iterative algorithms for obtaining the robust optimal beamforming solution. Results demonstrate the achieved robustness and the performance gain over conventional approaches and that the proposed algorithms can obtain the exact robust optimal solution with high probability.

A joint-channel diagonalization for multiuser MIMO antenna systems

In this paper, we address the problem of improving the performance of multiuser space-division multiplexing (SDM) systems where multiple independent signal streams can be transmitted in the same frequency and time slot. The problem is important in multiuser multiple-input multiple-output systems where communication from one base station to many mobile stations can occur simultaneously. Our objective is to devise a multiuser linear space-time precoder for simultaneous channel diagonalization of the multiuser channels enabling SDM. Our new approach is based on diagonalizing the multiuser channel matrices and we use a variation of successive Jacobi rotations. In addition to the diagonalization, our approach attempts to optimize the resultant channel gains for performance enhancement. Our method is valid for both frequency-flat and frequency-selective fading channels but we assume that the base station knows all the channels and that they are quasi-stationary.

Dual-hop systems with noisy relay and interference-limited destination

In this letter, we analyze the outage performance of a dual-hop relay fading channel in an interference-limited environment. We first derive closed-form expressions for the outage probability of both the amplify-and-forward (AF) and the decode-and-forward (DF) relay channels, based on which, the diversity analysis is conducted. In addition, we show that in terms of the outage probability performance, the worst scenario appears to be the case with equal received-power interferers, for a given total received interference power.

Ergodic Capacity Analysis of Amplify-and-Forward MIMO Dual-Hop Systems

This paper presents an analytical characterization of the ergodic capacity of amplify-and-forward (AF) MIMO dual-hop relay channels, assuming that the channel state information is available at the destination terminal only. In contrast to prior results, our expressions apply for arbitrary numbers of antennas and arbitrary relay configurations. We derive an expression for the exact ergodic capacity, simplified closed-form expressions for the high SNR regime, and tight closed-form upper and lower bounds. These results are made possible by employing recent tools from finite-dimensional random matrix theory, which are used to derive new closed-form expressions for various statistical properties of the equivalent AF MIMO dual-hop relay channel, such as the distribution of an unordered eigenvalue and certain random determinant properties. Based on the analytical capacity expressions, we investigate the impact of the system and channel characteristics, such as the antenna configuration and the relay power gain. We also demonstrate a number of interesting relationships between the dual-hop AF MIMO relay channel and conventional point-to-point MIMO channels in various asymptotic regimes.

Outage Analysis of Decode-and-Forward Cognitive Dual-Hop Systems With the Interference Constraint in Nakagami-

This paper studies the outage probability performance of decode-and-forward (DF) cognitive dual-hop systems for Nakagami-m fading channels, with consideration of an interference temperature limit. An exact outage probability expression is derived, and the impact of various key system parameters, such as interference temperature and fading severity, is investigated. Our results show that the interference temperature constraint causes the outage saturation phenomenon, but the outage performance gets better when the channel quality of the secondary transmission links improves. However, how the channel quality of the interfering links affects the outage performance depends on the channel quality of the secondary transmission links, as well as the interference temperature constraint and maximum transmit power.

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The fifth generation (5G) mobile networks are envisioned to support the deluge of data traffic with reduced energy consumption and improved quality of service (QoS) provision. To this end, key enabling technologies, such as heterogeneous networks (HetNets), massive multiple-input multiple-output (MIMO), and millimeter wave (mmWave) techniques, have been identified to bring 5G to fruition. Regardless of the technology adopted, a user association mechanism is needed to determine whether a user is associated with a particular base station (BS) before data transmission commences. User association plays a pivotal role in enhancing the load balancing, the spectrum efficiency, and the energy efficiency of networks. The emerging 5G networks introduce numerous challenges and opportunities for the design of sophisticated user association mechanisms. Hence, substantial research efforts are dedicated to the issues of user association in HetNets, massive MIMO networks, mmWave networks, and energy harvesting networks. We introduce a taxonomy as a framework for systematically studying the existing user association algorithms. Based on the proposed taxonomy, we then proceed to present an extensive overview of the state-of-the-art in user association algorithms conceived for HetNets, massive MIMO, mmWave, and energy harvesting networks. Finally, we summarize the challenges as well as opportunities of user association in 5G and provide design guidelines and potential solutions for sophisticated user association mechanisms.

Fading Channels

This paper describes a new approach to the problem of enhancing the performance of a multiuser multiple-input-multiple-output (MIMO) system for communication from one base station to many mobile stations in both frequency-flat and frequency-selective fading channels. This problem arises in space-division multiplexing systems with multiple users where many independent signal streams can be transmitted in the same frequency and time slot through the exploitation of multiple antennas at both the base and mobile stations. Our new approach is based on maximizing a lower bound for the product of signal-to-interference plus noise ratio (SINR) of a multiuser MIMO system. This provides a closed-form (noniterative) solution for the antenna weights for all the users, under the constraint of fixed transmit power. Our solution is shown by simulation to have better performance than previously proposed iterative or noniterative solutions. In addition, our solution requires significantly reduced complexity over a gradient search-based method that directly optimizes the product SINRs while still maintaining similar performance. Our solution assumes channel state information is present at the base station or transmitter.

User Association in 5G Networks: A Survey and an Outlook

This letter studies the collaborative use of amplify-and-forward (AF) relays to form a virtual multiple-input single-output (MISO) beamforming system with the aid of perfect channel state information (CSI) in a flat-fading channel. In particular, we optimize the relay weights jointly to maximize the received signal-to-noise ratio (SNR) at the destination terminal with both individual and total power constraints at the relays. We show that the optimal collaborative-relay beamforming (CRB) solution achieves the full diversity of a MISO antenna system. Another main contribution of this letter is a distributed algorithm that allows each individual relay to learn its own weight, based on the Karush-Kuhn-Tucker (KKT) analysis.

Performance enhancement of multiuser MIMO wireless communication systems

In this paper, a deterministic equivalent of ergodic sum rate and an algorithm for evaluating the capacity-achieving input covariance matrices for the uplink large-scale multiple-input multiple-output (MIMO) antenna channels are proposed. We consider a large-scale MIMO system consisting of multiple users and one base station with several distributed antenna sets. Each link between a user and an antenna set forms a two-sided spatially correlated MIMO channel with line-of-sight (LOS) components. Our derivations are based on novel techniques from large dimensional random matrix theory (RMT) under the assumption that the numbers of antennas at the terminals approach to infinity with a fixed ratio. The deterministic equivalent results (the deterministic equivalent of ergodic sum rate and the capacity-achieving input covariance matrices) are easy to compute and shown to be accurate for realistic system dimensions. In addition, they are shown to be invariant to several types of fading distribution.