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This paper presents a new cooperative wireless communication network strategy that incorporates energy cooperation and data cooperation. The model establishment, design goal formulations, and algorithms for throughput maximization of the proposed protocol are presented and illustrated using a three-node network with two energy harvesting (EH) user nodes and a destination node. Transmission models are established from the performance analysis for a total of four scenarios. Based on the models, we seek to find optimal energy management strategies by jointly optimizing time allocation for each user, power allocations over these time intervals, and data throughputs at user nodes so as to maximize the sum-throughput or, alternatively, the minimum throughput of the two users in all scenarios. An accelerated Newton barrier algorithm and an alternative algorithm based on local quadratic approximation of the transmission models are developed to solve the aforementioned optimization problems. Numerical experiments under practical settings provide supportive observations to our performance analysis., Comment: 30pages, 12 figures, journal

Considering a heterogeneous network (HetNet) system consisting of a macro tier overlaid with a second tier of small cells (SCs), this paper studies the mean square error (MSE) based precoding design to be employed by the macro base station and the SC nodes for multiple-input multiple-output (MIMO) downlinks. First, a new sum-MSE of all users based minimization problem is proposed aiming to design a set of macro cell (MC) and SC transmit precoding matrices or vectors. To solve it, two different algorithms are presented. One is via a relaxed-constraints based alternating optimization (RAO) realized by efficient alternating optimization and relaxing non-convex constraints to convex ones. The other is via an unconstrained alternating optimization with normalization (UAON) implemented by introducing the constraints into the iterations with the normalization operation. Second, a separate MSE minimization based precoding is proposed by considering the signal and interference terms corresponding to the macro tier and the SCs separately. Simulation results show that the sum-MSE based RAO algorithm provides the best MSE performance among the proposed schemes under a number of system configurations. When the number of antennas at the macro-BS is sufficiently large, the MSE of the separate MSE-based precoding is found to approach that of RAO and surpass that of UAON. Together, this paper provides a suite of three new precoding techniques that is expected to meet the need in a broad range of HetNet environments with adequate balance between performance and complexity., Comment: 13 pages, 8 figures. Submitted to IEEE Transactions on Vehicular Technology

This paper presents 3-D simulation of angled strike heavy ion induced charge collection in Silicon-Germanium Heterojunction Bipolar Transistors (SiGe HBTs). We select several different striking angles at various typical ion strike positions. The charge collection mechanism for each terminal is identified based on analysis of the device structure and simulation results. Angled strike ions induced charge collection present complex situation. With the change of striking angle, the longer the length of the ions track in sensitive volume, the more charge is collected. STI will prevent a part of diffused charge that charge collection reduces., 形態: カラー図版あり, 著者人数: 11名, Physical characteristics: Original contains color illustrations, Number of authors: 11

For the practical implementation of massive multiple-input multiple-output (MIMO) systems, the hybrid processing (precoding/combining) structure is promising to reduce the high cost rendered by large number of RF chains of the traditional processing structure. The hybrid processing is performed through low-dimensional digital baseband processing combined with analog RF processing enabled by phase shifters. We propose to design hybrid RF and baseband precoders/combiners for multi-stream transmission in point-to-point massive MIMO systems, by directly decomposing the pre-designed unconstrained digital precoder/combiner of a large dimension. The constant amplitude constraint of analog RF processing results in the matrix decomposition problem non-convex. Based on an alternate optimization technique, the non-convex matrix decomposition problem can be decoupled into a series of convex sub-problems and effectively solved by restricting the phase increment of each entry in the RF precoder/combiner within a small vicinity of its preceding iterate. A singular value decomposition based technique is proposed to secure an initial point sufficiently close to the global solution of the original non-convex problem. Through simulation, the convergence of the alternate optimization for such a matrix decomposition based hybrid processing (MD-HP) scheme is examined, and the performance of the MD-HP scheme is demonstrated to be near-optimal.

Multi-antenna relaying has emerged as a promising technology to enhance the system performance in cellular networks. However, when precoding techniques are utilized to obtain multi-antenna gains, the system generally requires channel state information (CSI) at the transmitters. We consider a linear precoding scheme in a MIMO relaying broadcast channel with quantized CSI feedback from both two-hop links. With this scheme, each remote user feeds back its quantized CSI to the relay, and the relay sends back the quantized precoding information to the base station (BS). An upper bound on the rate loss due to quantized channel knowledge is first characterized. Then, in order to maintain the rate loss within a predetermined gap for growing SNRs, a strategy of scaling quantization quality of both two-hop links is proposed. It is revealed that the numbers of feedback bits of both links should scale linearly with the transmit power at the relay, while only the bit number of feedback from the relay to the BS needs to grow with the increasing transmit power at the BS. Numerical results are provided to verify the proposed strategy for feedback quality control., Comment: 13pages appeared in IEEE Transactions on Signal Processing

This work investigates the use of N-face GaN-based heterostructures as a promising approach to overcome performance limitations commonly encountered in Gaface AlGaN/GaN HEMTs as their frequency of operation extends into the millimeter-wave and beyond. N-face (0001̄)?GaN, with its reversed direction of polarization compared to that of the Ga-face (0001), are well-suited for designing new device structures that address the problems of poor electron confinement and high ohmic contact resistance in highly-scaled GaN transistors. The fabrication and characterization of two N-face MISHEMT structures by plasma-assisted MBE are presented. The devices demonstrated good RF performance at 4 GHz, with the highest continuous-wave output power density and power-added efficiency exceeding 8 W/mm and 70%, respectively. At 10 GHz, an output power density and power-added efficiency of 4.2 W/mm and 49%, respectively, were achieved.

type:text, This paper investigates the problem of minimizing an L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints for one-dimensional (1-D) as well as a class of two-dimensional (2-D) state.space digital filters, where the 2-D digital filters are described by a transposed structure of the Fornasini.Marchesini second local state.space model. In each case, a novel iterative technique is developed to solve the constraint optimization problem directly. The proposed solution methods are largely based on the use of a Lagrange function and some matrix-theoretic techniques. Numerical examples are presented to demonstrate the effectiveness of the proposed techniques.

The joint optimization problem of error feedback and realization for two-dimensional (2-D) state-space digital filters to minimize the effects of roundoff noise at the filter output subject to L2-norm dynamic-range scaling constraints is investigated. It is shown that the problem can be converted into an unconstrained optimization problem by using linear-algebraic techniques. The unconstrained optimization problem at hand is then solved iteratively by applying an efficient quasi-Newton algorithm with closed-form formulas for key gradient evaluation. Analytical details are given as to how the proposed technique can be applied to the cases where the error-feedback matrix is a general, block-diagonal, diagonal, or block-scalar matrix. A case study is presented to illustrate the utility of the proposed technique.

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This paper investigates the problem of minimizing an L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints for one-dimensional (1-D) as well as a class of two-dimensional (2-D) state.space digital filters, where the 2-D digital filters are described by a transposed structure of the Fornasini.Marchesini second local state.space model. In each case, a novel iterative technique is developed to solve the constraint optimization problem directly. The proposed solution methods are largely based on the use of a Lagrange function and some matrix-theoretic techniques. Numerical examples are presented to demonstrate the effectiveness of the proposed techniques.

The joint optimization problem of error feedback and realization for two-dimensional (2-D) state-space digital filters to minimize the effects of roundoff noise at the filter output subject to L2-norm dynamic-range scaling constraints is investigated. It is shown that the problem can be converted into an unconstrained optimization problem by using linear-algebraic techniques. The unconstrained optimization problem at hand is then solved iteratively by applying an efficient quasi-Newton algorithm with closed-form formulas for key gradient evaluation. Analytical details are given as to how the proposed technique can be applied to the cases where the error-feedback matrix is a general, block-diagonal, diagonal, or block-scalar matrix. A case study is presented to illustrate the utility of the proposed technique.