Teng Joon Lim

Wireless communications with unmanned aerial vehicles: opportunities and challenges

Wireless communication systems that include unmanned aerial vehicles promise to provide cost-effective wireless connectivity for devices without infrastructure coverage. Compared to terrestrial communications or those based on high-altitude platforms, on-demand wireless systems with low-altitude UAVs are in general faster to deploy, more flexibly reconfigured, and likely to have better communication channels due to the presence of short-range line-of-sight links. However, the utilization of highly mobile and energy-constrained UAVs for wireless communications also introduces many new challenges. In this article, we provide an overview of UAV-aided wireless communications, by introducing the basic networking architecture and main channel characteristics, highlighting the key design considerations as well as the new opportunities to be exploited.

A matrix-algebraic approach to linear parallel interference cancellation in CDMA

Linear parallel interference cancellation (PIC) schemes are described and analyzed using matrix algebra. It is shown that the linear PIC, whether conventional or weighted, can be seen as a linear matrix filter applied directly to the chip-matched filtered received signal vector. An expression for the exact bit-error rate (BER) is obtained, and conditions on the eigenvalues of the code correlation matrix and the weighting factors to ensure convergence are derived. The close relationship between the linear multistage PIC and the steepest descent method (SDM) for minimizing the mean squared error (MSE) is demonstrated. A modified weighted PIC structure that resembles the SDM is suggested which approaches the minimum MSE (MMSE) detector rather than the decorrelator. It is shown that for a K-user system, only K PIC stages are required for the equivalent matrix filter to be identical to the the MMSE filter. For fewer stages, techniques are devised for optimizing the choice of weights with respect to the MSE. One unique optimal choice of weights is found, which will lead to the minimum achievable MSE at the final stage. Simulation results show that a few stages are sufficient for near-MMSE performance.

Optimal Save-Then-Transmit Protocol for Energy Harvesting Wireless Transmitters

In this paper, the design of a wireless communication device relying exclusively on energy harvesting is considered. Due to the inability of rechargeable energy sources to charge and discharge at the same time, a constraint we term the energy half-duplex constraint, two rechargeable energy storage devices (ESDs) are assumed so that at any given time, there is always one ESD being recharged. The energy harvesting rate is assumed to be a random variable that is constant over the time interval of interest. A save-then-transmit (ST) protocol is introduced, in which a fraction of time ρ (dubbed the save-ratio) is devoted exclusively to energy harvesting, with the remaining fraction 1-ρ used for data transmission. The ratio of the energy obtainable from an ESD to the energy harvested is termed the energy storage efficiency, η. We address the practical case of the secondary ESD being a battery with η <; 1, and the main ESD being a super-capacitor with η = 1. Important properties of the optimal save-ratio that minimizes outage probability are derived, from which useful design guidelines are drawn. In addition, we compare the outage performance of random power supply to that of constant power supply over the Rayleigh fading channel. The diversity order with random power is shown to be the same as that of constant power, but the performance gap can be large. Finally, we extend the proposed ST protocol to wireless networks with multiple transmitters. It is shown that the system-level outage performance is critically dependent on the number of transmitters and the optimal save-ratio for single-channel outage minimization.

Downlink and Uplink Energy Minimization Through User Association and Beamforming in C-RAN

The cloud radio access network (C-RAN) concept, in which densely deployed access points (APs) are empowered by cloud computing to cooperatively support mobile users (MUs), to improve mobile data rates, has been recently proposed. However, the high density of active APs results in severe interference and also inefficient energy consumption. Moreover, the growing popularity of highly interactive applications with stringent uplink (UL) requirements, e.g., network gaming and real-time broadcasting by wireless users, means that the UL transmission is becoming more crucial and requires special attention. Therefore in this paper, we propose a joint downlink (DL) and UL MU-AP association and beamforming design to coordinate interference in the C-RAN for energy minimization, a problem which is shown to be NP hard. Due to the new consideration of UL transmission, it is shown that the two state-of-the-art approaches for finding computationally efficient solutions of joint MU-AP association and beamforming considering only the DL, i.e., group-sparse optimization and relaxed-integer programming, cannot be modified in a straightforward way to solve our problem. Leveraging on the celebrated UL-DL duality result, we show that by establishing a virtual DL transmission for the original UL transmission, the joint DL and UL optimization problem can be converted to an equivalent DL problem in C-RAN with two inter-related subproblems for the original and virtual DL transmissions, respectively. Based on this transformation, two efficient algorithms for joint DL and UL MU-AP association and beamforming design are proposed, whose performances are evaluated and compared with other benchmarking schemes through extensive simulations.

Linear parallel interference cancellation in long-code CDMA multiuser detection

Parallel interference cancellation (PIC) is a promising detection technique for code division multiple access (CDMA) systems. It has previously been shown that the weighted multistage PIC can be seen as an implementation of the steepest descent algorithm used to minimize the mean squared error (MSE). Following this interpretation, a unique set of weights, based on the eigenvalues of the correlation matrix, was found to lead to the minimum achievable MSE for a given number of stages in a short-code system. In this paper, we introduce a method for finding an appropriate set of time-invariant weights for systems using long codes. The weights are dependent on moments of the eigenvalues of the correlation matrix, exact expressions of which can be derived. This set of weights is optimal in the sense that it minimizes the ensemble averaged MSE over all code-sets. The loss incurred by averaging rather than using the optimal, time-varying weights is practically negligible, since the eigenvalues of sample correlation matrices are tightly clustered in most cases of interest. The complexity required for computing the weights increases linearly with the number of users but is independent of the processing gain, hence on-line weight updating is possible in a dynamic system. Simulation results show that a few stages is usually sufficient for near-MMSE performance.

Adaptive symbol and parameter estimation in asynchronous multiuser CDMA detectors

Existing multiuser code-division multiple-access (CDMA) detectors either have to rely on strict power control or near-perfect parameter estimation for reliable operation. A novel adaptive multiuser CDMA detector structure is introduced. Using either an extended Kalman filter (EKF) or a recursive least squares (RLS) formulation, adaptive algorithms which jointly estimate the transmitted bits of each user and individual amplitudes and time delays may be derived. The proposed detectors work in a tracking mode after initial delay acquisition is accomplished using other techniques not discussed here. Through computer simulations, we show that the algorithms perform better than a bank of single-user (SU) receivers in terms of near-far resistance. Practical issues such as the selection of adaptation parameters are also discussed.

Placement Optimization of UAV-Mounted Mobile Base Stations

In terrestrial communication networks without fixed infrastructure, unmanned aerial vehicle-mounted mobile base stations (MBSs) provide an efficient solution to achieve wireless connectivity. This letter aims to minimize the number of MBSs needed to provide wireless coverage for a group of distributed ground terminals (GTs), ensuring that each GT is within the communication range of at least one MBS. We propose a polynomial-time algorithm with successive MBS placement, where the MBSs are placed sequentially starting on the area perimeter of the uncovered GTs along a spiral path toward the center, until all GTs are covered. Numerical results show that the proposed algorithm performs favorably compared with other schemes in terms of the number of required MBSs as well as time complexity.

Optimal save-then-transmit protocol for energy harvesting wireless transmitters

In this paper, the design of a wireless communication device relying exclusively on energy harvesting is considered. Due to the inability of rechargeable energy sources to charge and discharge at the same time, a constraint we term the energy half-duplex constraint, two rechargeable energy storage devices (ESDs) are assumed so that at any given time, there is always one ESD being recharged. The energy harvesting rate is a random variable that is constant over the time interval of interest. A save-then-transmit (ST) protocol is introduced, in which a fraction of time ρ (dubbed the save ratio) is devoted exclusively to energy harvesting, with the remaining fraction 1 − ρ used for data transmission. The ratio of the energy obtainable from an ESD to the energy harvested is termed the ESD efficiency, η. We address the practical case of the secondary ESD being a battery with η < 1, and the main ESD being a super-capacitor with η = 1. The optimal save-ratio that minimizes outage probability is derived, from which some useful design guidelines are drawn. Numerical results are provided to validate our proposed study.

Digital Network Coding Aided Two-Way Relaying: Energy Minimization and Queue Analysis

In this paper, we consider a three-node, two-way relay system with digital network coding. The aim is to minimize total energy consumption while ensuring queue stability at all nodes, for a given pair of random packet arrival rates. Specifically, we allow for a set of transmission modes and solve for the optimal fraction of resources allocated to each mode. First, we formulate and solve the static-channel problem, where all link gains are constant over the duration of transmission. Then, we solve the fading-channel problem, where link gains are random. We call the latter the ergodic energy efficiency problem and show that its solution has a water-filling structure. Finally, we provide a detailed analysis of the queues at each node when a random scheduling method that closely approximates the theoretical design is used.

Box-constrained maximum-likelihood detection in CDMA

The detection strategy usually denoted optimal multiuser detection is equivalent to the solution of a (0,1)-constrained maximum-likelihood (ML) problem, a problem which is known to be NP-complete. In contrast, the unconstrained ML problem can be solved quite easily and is known as the decorrelating detector. In this paper, we consider the box-constrained ML problem and suggest a general iterative solution algorithm. Special cases of this algorithm correspond to known, nonlinear successive and parallel interference cancellation structures, using a clipped soft decision function for making tentative decisions. These structures are therefore maximum-likelihood under the assumption that the detected data vector is constrained to lie within a hypercube. Convergence issues are investigated and an efficient implementation is suggested. The BER performance is studied via computer simulations and the expected performance improvements over unconstrained ML is verified.