Jae-Mo Kang

Mode Switching for SWIPT Over Fading Channel With Nonlinear Energy Harvesting

We study mode switching (MS) between information decoding and energy harvesting (EH) for simultaneous wireless information and power transfer (SWIPT) over the fading channel. Unlike the existing result obtained with a simplistic assumption of linear EH, we consider a realistic scenario of the nonlinear EH. In this setting, to design the optimal MS, we address the problem of maximizing the average achievable rate under an average harvested energy constraint, which is generally nonconvex and combinatorial. Using the time-sharing condition, the optimal MS solution for the nonlinear EH is presented efficiently. From the obtained result and further analysis, we draw interesting and important insights into the optimized SWIPT system with nonlinear EH.

Wireless Information and Power Transfer: Rate-Energy Tradeoff for Nonlinear Energy Harvesting

In this paper, we study rate-energy (R-E) tradeoffs for simultaneous wireless information and power transfer (SWIPT). In the existing literature, by invoking a simplistic and ideal assumption of linear energy harvesting, the R-E tradeoff performance was analyzed only for the four SWIPT schemes: the dynamic power splitting, type-I on–off power splitting (OPS), static power splitting, and time switching. Different from such works, in this work, we consider the realistic and practical scenario of nonlinear energy harvesting. Furthermore, to characterize the R-E tradeoff with nonlinear energy harvesting, we propose a new SWIPT scheme, the generalized OPS (GOPS). As a special case of the proposed GOPS, we also investigate an additional SWIPT scheme, the type-II OPS. Through the analysis based on the realistic nonlinear models reported in the literature, we derive new theoretical results on the R-E tradeoff, which are in sharp contrast to those in the existing literature obtained with linear energy harvesting. Furthermore, we provide various useful insights into the SWIPT system with nonlinear energy harvesting.

Joint Design of Optimal Precoding and Cooperative Jamming for Multiuser Secure Broadcast Systems

A multiuser secure broadcast system is considered, where there are one multiantenna base station (BS), multiple single-antenna legitimate users, one multiantenna friendly jammer (FJ), and one multiantenna eavesdropper (Eve). We jointly design the optimal precoding matrix at the BS and the jamming covariance matrix at the FJ by minimizing the total transmit power of the BS and FJ under the signal-to-interference-plus-noise ratio constraints at the users and Eve. To solve this challenging problem, when the FJ has more antennas than the users and Eve, we first find the optimal structure of the jamming covariance matrix and, then, convert the problem into its equivalent convex form. Also, we propose an iterative algorithm to jointly design the precoding and jamming covariance matrices in all scenarios. The solution obtained by this algorithm is shown to be asymptotically optimal when the FJ has more antennas than the users and Eve. Numerical results show that the proposed schemes considerably outperform the existing schemes.

Optimal Training Design for MIMO-OFDM Two-Way Relay Networks

In this paper, we study a training design problem for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) amplify-and-forward (AF) two-way relay networks. Unlike the existing studies, we assume the spatially correlated fading and consider the nonreciprocal channel condition, which is a more practical assumption but makes the training problem more challenging. The equivalent channels of bidirectional relaying links, which consist of self-interfering channels and information-bearing channels, are estimated at each source node based on a linear minimum mean square error (LMMSE) approach. The total mean square error (MSE) of the channel estimation is minimized under the transmit power constraints at the source nodes and at the relay. To solve this problem, we first derive an optimal structure of the training signals, and then, convert the optimization problem into a tractable convex form, from which the optimal training scheme is designed efficiently. Furthermore, for a practical special case, the optimal training design is derived in semi-closed form, which provides useful insights. To reduce the required complexity, a low-complexity training scheme is also derived in closed-form. This scheme is shown to be asymptotically optimal in the high signal-to-noise ratio (SNR) regime and gives further insights into the optimal training. The performance of the proposed schemes is demonstrated through numerical simulations.

Rate-Energy Tradeoff and Decoding Error Probability-Energy Tradeoff for SWIPT in Finite Code Length

In this paper, the fundamental performance of the simultaneous wireless information and power transfer (SWIPT) system is studied. Unlike any existing works where the codelength was assumed to be infinity, we explicitly consider the case of the finite codelength, which is much more realistic especially for the practical SWIPT system due to its limited power and complexity. For the four well-known SWIPT schemes, we analyze the tradeoff between the rate and energy; then we study the optimality of those SWIPT schemes. Furthermore, to fully characterize the fundamental performance of the SWIPT system in the regime of finite codelength, we propose to additionally use the new tradeoff between the decoding error probability and the harvested energy. In the sense of this new tradeoff, we study the optimality of the four SWIPT schemes. For the analysis of the two types of tradeoffs, we consider two different cases: when the transmit power of symbols is adapted or not. For various scenarios, we provide useful insights into the performance of the SWIPT system in the finite codelength.

Max-Min Energy-Efficiency Optimization in Wireless Powered Communication Network with Harvest-Then-Transmit Protocol

In this paper, we propose an energy-efficient transmission scheme for wireless powered communication networks with harvest-then-transmit protocol. Specifically, considering fairness among users, we present time resource allocation scheme to maximize the individual energy efficiency(EE) of each user, defined as a ratio of the user throughput to its harvested energy,based on the max-min criterion. EE optimization problem is highly non-convex and difficult to directly tackle. To solve this difficulty, we initially convert two EE problem into its equivalent parameterized subtractive form and, then, the corresponding optimal solution is determined via efficient two-layer iterative algorithm. The simulation results show that the proposed scheme provides better EE performances than those of the conventional schemes and the fairness-based algorithm considerably outperforms the other schemes in terms of the minimum user EE.