Daiju Nakano

Wireless data center networking with steered-beam mmWave links

This paper presents a new type of wireless networking applications in data centers using steered-beam mmWave links. By taking advantage of clean LOS channels on top of server racks, robust wireless packet-switching network can be built. The transmission latency can be reduced by flexibly bridging adjacent rows of racks wirelessly without using long cables and multiple switches. Eliminating cables and switches also reduces equipment costs as well as server installation and reconfiguration costs. Security can be physically enhanced with controlled directivity and negligible wall penetration. The aggregate data transmission BW per given volume is expected to scale as the fourth power of carrier frequency. The paper also deals with the architecture of such network configurations and a preliminary demonstration system.

MIMO link design strategy for wireless data center applications

This paper deals with mm Wave MIMO link design strategy for wireless data center applications where the MIMO degrees of freedom is taken into account in multi-node packet networking environments. The problem is treated differently from the coordinated multiuser MIMO situation and the link design is optimized independently in each node with meeting control and data plane requirements for contention-based packet switching. In particular, we propose using an interference-aligned out-of-band control plane to improve the unidirectional bonded in-band data plane collision-related performance degradation with a limited number of antenna elements per node. We also present a high-level implementation plan.

43.1: Color Filterless Liquid Crystal Display Illuminated with LEDs

We have prototyped a 13.3-inch diagonal color filterless LCD illuminated with LEDs. A new color directional backlight combined with a microlens attached liquid crystal cell plate shows the feasibility of a new power efficient LCD with better color and lead-free features.

Multi-Gbps 60-GHz single-carrier system using a low-power coherent detection technique

We describe a multi-Gbps 60-GHz single-carrier system using a low-power coherent detection technique. To realize low-power operation at such a high data rate, it is crucial to design the system with reduced oversampling factor and bit depth. A table-based IQ phase rotator and a time-domain polyphase equalizer have been designed for realizing a robust and low-power coherent link under these conditions with rounding-error-free operations and effective interpolations. The entire baseband signal processing is implemented in FPGAs and we are successful in multi-Gbps per-packet transmissions per the IEEE 802.15.3c single-carrier PHY (SC-PHY) format for π/2-BPSK and π/2-QPSK modulations at a full data rate. We confirmed that the 60-GHz single-carrier system can be robust to the carrier and sampling frequency offsets within 50 ppm, even with 2× oversampling factor and 3-bit ADCs, which can lower the power consumption.

Multi-Gbps wireless systems over 60-GHz SiGe radio link with BW-efficient noncoherent detections

This paper describes a demonstration of multi-Gbps wireless systems using 60-GHz SiGe radio chipsets with noncoherent detection techniques. The modulation and demodulation are performed with BW-efficient frequency-shift keying schemes, such as MSK, by partitioning the function into the radio chip and baseband FPGA. With integrated mixer/sign modulator and appropriate precoder, an IQ-based radio interface is used in TX, while the noncoherent detections are achieved by using FM discriminator and CDR (Clock Data Recovery) in RX. As a result, multi-Gbps data rate systems can be built without using high sampling rate ADC/DAC, and the efficiency better than ASK or FSK modulation schemes is achieved.

Wave-Based Reservoir Computing by Synchronization of Coupled Oscillators

We propose wave-based computing based on coupled oscillators to avoid the inter-connection bottleneck in large scale and densely integrated cognitive systems. In addition, we introduce the concept of reservoir computing to coupled oscillator systems for non-conventional physical implementation and reduction of the training cost of large and dense cognitive systems. We show that functional approximation and regression can be efficiently performed by synchronization of coupled oscillators and subsequent simple readouts.

An Energy-Efficient Computing Approach by Filling the Connectome Gap

This paper presents an energy-efficient neuromorphic computing approach by filling the connectome gap between algorithm, brain, and VLSI. The gap exists in structural features such as the average number of synaptic connections per neural node as well as in dimensional features. We argue that the energy dissipation in complex computing tasks is more predominantly bounded by the control processes that synchronize and redirect both computing processes and data rather than the computing processes themselves. Therefore, it is crucial to fill the connectome gap and to avoid excessive interactions of the computing process and data with the control processes when achieving energy-efficient computing for large-scale cognitive computing tasks. The use of freespace optics is proposed as a means to efficiently handle sparse but still heavily entangled connections.

Exploiting Heterogeneous Units for Reservoir Computing with Simple Architecture

Reservoir computing is a computational framework suited for sequential data processing, consisting of a reservoir part and a readout part. Not only theoretical and numerical studies on reservoir computing but also its implementation with physical devices have attracted much attention. In most studies, the reservoir part is constructed with identical units. However, a variability of physical units is inevitable, particularly when implemented with nano/micro devices. Here we numerically examine the effect of variability of reservoir units on computational performance. We show that the heterogeneity in reservoir units can be beneficial in reducing the prediction error in the reservoir computing system with a simple cycle reservoir.

Dynamics of Reservoir Computing at the Edge of Stability

We investigate reservoir computing systems whose dynamics are at critical bifurcation points based on center manifold theorem. We take echo state networks as an example and show that the center manifold defines mapping of the input dynamics to higher dimensional space. We also show that the mapping by center manifolds can contribute to recognition of attractors of input dynamics. The implications for realization of reservoir computing as real physical systems are also discussed.

Photonic Reservoir Computing Based on Laser Dynamics with External Feedback

Reservoir computing is a novel paradigm of neural network, offering advantages in low learning cost and ease of implementation as hardware. In this paper we propose a concept of reservoir computing consisting of a semiconductor laser subject to external feedback by a mirror, where input signal is supplied as modulation pattern of mirror reflectivity. In that system, non-linear interaction between optical field and electrons are enhanced in complex manner under substantial external feedback, leading to achieve highly nonlinear projection of input electric signal to output optical field intensity. It is exhibited that the system can most efficiently classify waveforms of sequential input data when operating around laser oscillation’s effective threshold.