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Emerging non-volatile memories (eNVM) promise to solve the imminent von Neumann bottleneck by enabling future computing systems to utilize the computing-in-memory (CIM) paradigm offering exceptional energy efficiency and performance advantages. As Moore's law becomes obsolete, CIM architectures are prominent candidates to push the boundaries of existing computing systems and usher in a new generation of computing models, such as neuromorphic systems. Furthermore, conventional systems face another significant problem in addition to the von Neumann bottleneck. Hardware security threats (e.g., Rowhammer) have gained momentum and can expose an entirely pristine attack surface for adversaries. These vulnerabilities distinguish themselves by being particularly challenging to patch because their origin lies in the rigid hardware layout. Unfortunately, neuromorphic systems are no exception. We presented NeuroHammer as one of the first unique hardware security attacks on eNVMs, enabling an attacker to intentionally flip bits in memristive crossbar arrays. This article extends our previous results by thoroughly examining the underlying concepts leading to the NeuroHammer attack. First, we investigate memory access patterns to gain insight into the tangible impact of NeuroHammer. Second, we extend our simulation methodology to accommodate transistor/one resistive (1T1R) crossbar structures and prove the prevalence of the NeuroHammer attack. Finally, we discuss the real-world implications of NeuroHammer on CIM architectures.

The optimal energy signal design for wireless powered communication networks (WPCNs) enabling energy-sustainable communication for a large number of low-power devices is still an open problem in practical systems. In this work, we study a multi-user WPCN, where a multi-antenna base station (BS) sends an energy signal to multiple single-antenna users, which, in turn, harvest energy from the received signal and utilize it for information transmission in the uplink. In contrast to the existing works on multiple-input single-output (MISO) WPCN design, in this paper, we jointly optimize the energy signal waveform and downlink beamforming at the BS for energy harvesting (EH) devices described by non-linear circuit-based models. To this end, we assume that the BS broadcasts a pulse-modulated signal employing multiple energy signal vectors and we formulate an optimization problem for the joint design of the downlink transmit energy signal vectors, their number, the durations of the transmit pulses, and the time allocation policy for minimization of the average transmit power at the BS. We show that for single-user WPCNs, a single energy signal vector, which is collinear with the maximum ratio transmission (MRT) vector and drives the EH circuit at the user device into saturation, is optimal. Next, for the general multi-user case, we show that the optimal signal design requires a maximum number of energy signal vectors that exceeds the number of users by one and propose an algorithm to obtain the optimal energy signal vectors. Since the complexity of the optimal design is high, we also propose two suboptimal schemes for WPCN design. First, for asymptotic massive WPCNs, where the ratio of the number of users to the number of BS antennas, i.e., the system load, tends to zero, we show that the optimal downlink transmit signal can be obtained in closed-form and comprises a sequence of weighted sums of MRT vectors. Next, based on this result, for general WPCNs with finite system loads, we propose a suboptimal closed-form MRT-based design and a suboptimal semidefinite relaxation (SDR)-based scheme. Our simulation results reveal that the proposed optimal scheme and suboptimal SDR-based design achieve nearly identical performance and outperform two baseline schemes, which are based on linear and sigmoidal EH models. Furthermore, we show that, if the system load of the WPCN is low, the performance gap between the proposed suboptimal solutions is small and becomes negligible as the number of BS antennas tends to infinity.

We study two-user multiple-input single-output (MISO) wireless powered communication networks (WPCNs), where the user devices are equipped with non-linear energy harvesting (EH) circuits. We consider time-division duplex (TDD) transmission, where the users harvest power from the signal received in the downlink phase, and then, utilize this harvested power for information transmission in the uplink phase. In contrast to existing works, we adopt a non-linear model of the harvested power based on a precise analysis of the employed EH circuit. We jointly optimize the beamforming vectors in the downlink and the time allocated for downlink and uplink transmission to minimize the average transmit power in the downlink under per-user data rate constraints in the uplink. We provide conditions for the feasibility of the resource allocation problem and the existence of a trivial solution, respectively. For the case where the resource allocation has a non-trivial solution, we show that it is optimal to employ no more than three beamforming vectors for power transfer in the downlink. To determine these beamforming vectors, we develop an iterative algorithm based on semi-definite relaxation (SDR) and successive convex approximation (SCA). Our simulation results reveal that the proposed resource allocation scheme outperforms two baseline schemes based on linear and sigmoidal EH models, respectively.

An integrated circuit (IC) for decoupling of multiple-input multiple-output (MIMO) antennas as well as for aperture and impedance tuning is demonstrated in this paper. The IC decouples the adjacent stripes of the inverted-F antenna (IFA) forming the two separate IFAs for MIMO operation in middle- and high-cellular frequency bands. For low-band operation the IC joins the stripes, forming a single IFA with double the physical length. The same IC is also used for impedance and aperture tuning of the antennas. The IC is designed and fabricated in dedicated 130 nm RF switch technology. The design and measurement results are presented in the paper.

In this paper, we study information-theoretic limits for simultaneous wireless information and power transfer (SWIPT) systems employing practical nonlinear radio frequency (RF) energy harvesting (EH) receivers (Rxs). In particular, we consider a SWIPT system with one transmitter that broadcasts a common signal to an information decoding (ID) Rx and multiple EH Rxs. Owing to the nonlinearity of the EH Rxs' circuitry, the efficiency of wireless power transfer depends on the waveform of the transmitted signal. We aim to answer the following fundamental question: What is the optimal input distribution of the transmit signal waveform that maximizes the information transfer rate at the ID Rx conditioned on individual minimum required direct-current (DC) powers to be harvested at the EH Rxs? Specifically, we study the conditional capacity problem of a SWIPT system impaired by additive white Gaussian noise subject to average-power (AP) and peak-power (PP) constraints at the transmitter and nonlinear EH constraints at the EH Rxs. To this end, we develop a novel nonlinear EH model that captures the saturation of the harvested DC power by taking into account not only the forward current of the rectifying diode but also the reverse breakdown current. Then, we derive a novel semi-closed-form expression for the harvested DC power, which simplifies to closed form for low input RF powers. The derived analytical expressions are shown to closely match circuit simulation results. We solve the conditional capacity problem for real- and complex-valued signalling and prove that the optimal input distribution that maximizes the rate-energy (R-E) region is unique and discrete with a finite number of mass points. Furthermore, we show that, for the considered nonlinear EH model and a given AP constraint, the boundary of the R-E region saturates for high PP constraints due to the saturation of the harvested DC power for high input RF powers. In addition, we devise a suboptimal input distribution whose R-E tradeoff performance is close to optimal. All theoretical findings are verified by numerical evaluations.

This paper presents a novel dual-band class-E/F power amplifier (PA) with switchable output power. It is targeted to work in a BPSK/OOK transmitter in smart facility applications like an autarkic asset-tracking system based on small sensor nodes. The amplifier is fully-integrated and able to operate at both 434 MHz and 868 MHz without the need for additional inductors, making the design very area-efficient. The output power settings at 868 MHz are controllable between -1.79 dBm and -24.61 dBm at 4.96 mA and 1.43 mA current consumption, respectively. The whole circuit including all inductors and the matching network in front of the antenna consumes only 0.9 mm2 chip area and is fully integrated in a 180 nm CMOS process together with a VCO and a PLL.

A monolithic low noise variable gain amplifier (LNA) operating at 60 GHz is presented. It is designed for a sixport receiver, which is completely integrated on a single chip. These chips are build in highly miniaturized sensors to measure distances with radar. Therefore a high performance LNA is indispensable. The circuit has been designed using a new 0.13 μm SiGe BiCMOS process from IHP (SG13G2). For implementation a three stage architecture is chosen. Measurements show a tuneable gain from 16 to 24 dB at 60 GHz, an input matching of -17 dB and an output matching of -14 dB. The circuit consumes 13 mA from a 3.3 V supply.

This work presents an intelligent analog image sensor system for smart camera applications with the need of edge or marker detection. The system consists of a 3×3 read-out CMOS image sensor, an analog Sobel stage and additional circuitry like operational amplifiers and comparators to compute a 1 bit image with the edges present in the taken photo. This information can then be further processed digitally to detect specific shapes in order to control robot routines, for example. The architecture of the proposed system is highly desirable as dedicated analog hardware has significant advantages in terms of power and speed compared to digital implementations. The overall system is simulated with the help of a 3×3 CMOS image sensor IC as well as Cadence Virtuoso for analog circuit simulation and MATLAB to convert the sequential information back to an image, and compared to other state of the art CMOS image sensors with edge detection capability. The analog Sobel circuit runs with a clock of 10 MHz and consumes less than 0.79 mW average power for the computation of the example image, and the whole 200×200 pixel image sensor consumes only 5.5 mW at a frame rate of 75 fps.