It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

Communication at millimeter wave (mmWave) frequencies is defining a new era of wireless communication. The mmWave band offers higher bandwidth communication channels versus those presently used in commercial wireless systems. The applications of mmWave are immense: wireless local and personal area networks in the unlicensed band, 5G cellular systems, not to mention vehicular area networks, ad hoc networks, and wearables. Signal processing is critical for enabling the next generation of mmWave communication. Due to the use of large antenna arrays at the transmitter and receiver, combined with radio frequency and mixed signal power constraints, new multiple-input multiple-output (MIMO) communication signal processing techniques are needed. Because of the wide bandwidths, low complexity transceiver algorithms become important. There are opportunities to exploit techniques like compressed sensing for channel estimation and beamforming. This article provides an overview of signal processing challenges in mmWave wireless systems, with an emphasis on those faced by using MIMO communication at higher carrier frequencies.

An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems

An architectural approach that meets high bandwidth requirements by introducing a communication architecture based on lightpaths, optical transmission paths in the network, is introduced. Since lightpaths form the building block of the proposed architecture, its performance hinges on their efficient establishment and management. It is shown that although the problem of optimally establishing lightpaths is NP-complete, simple heuristics provide near optimal substitutes for several of the basic problems motivated by a lightpath-based architecture. >

Lightpath communications: an approach to high bandwidth optical WAN's

The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traffic volumes, real-time extraction of fine-grained analytics, and agile management of network resources, so as to maximize user experience. Fulfilling these tasks is challenging, as mobile environments are increasingly complex, heterogeneous, and evolving. One potential solution is to resort to advanced machine learning techniques, in order to help manage the rise in data volumes and algorithm-driven applications. The recent success of deep learning underpins new and powerful tools that tackle problems in this space. In this paper, we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas. We first briefly introduce essential background and state-of-the-art in deep learning techniques with potential applications to networking. We then discuss several techniques and platforms that facilitate the efficient deployment of deep learning onto mobile systems. Subsequently, we provide an encyclopedic review of mobile and wireless networking research based on deep learning, which we categorize by different domains. Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.

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Deep Learning in Mobile and Wireless Networking: A Survey

A system and method for wireless communication between a plurality of subscriber units and a base station, the base station communicating information signals from an originating source to a destination subscriber unit over a channel at an assigned one of a plurality of frequencies using repetitive time frames, each said time frame comprising a sequence of time slots. The channel is defined as having the same one or more time slots from the sequence of time slots in one or more of the time frames. The base station includes a central processing unit capable of assigning a duration of time for the information signals being sent to the destination subscriber unit. The duration equals the duration of one or more time slots in the same frame. The central processing unit maintains a memory of which time slots of each time frame have been assigned and provides the time slot assignment, and therefore channel assignment, by consulting said memory. The system includes a multiplexer for multiplexing the information signals onto the assigned channel; and a transmitter for transmitting the information signals to the destination subscriber unit using the assigned channel.

Subscriber RF telephone system for providing multiple speech and/or data signals simultaneously over either a single or a plurality of RF channels

This paper presents a 10 Gbps millimeter wave OFDM experimental system using a highly efficient modulation and coding scheme where iterative phase noise compensation can drastically alleviate performance degradation due to phase noise. 60 GHz frequency synthesizer in a silicon RF-CMOS IC suffers from relatively large phase noise, which severely degrades the performance of the 10 Gbps OFDM using 64QAM and LDPC code with coding rate of 14/15. In order to alleviate this impairment, the experimental system applies combination of decision-directed phase noise compensation (DD-PNC), decision-directed channel estimation (DDCE) and packet interleaving (P-IL) to OFDM reception processing. The sophisticated combination of iterative processing provides a synergistic effect on coping with the influence of the phase noise by exploiting outputs of the LDPC decoder. Experimental results of the 10 Gbps OFDM with 60 GHz cable connection demonstrate that the combination can achieve 10 Gbps throughput at SNR of 25.8 dB when the phase noise level is -89 dBc/Hz at 1 MHz offset.

10 Gbps millimeter-wave OFDM experimental system with iterative phase noise compensation

ATM Routing Algorithms with Multiple QOS Requirements for Multimedia Internetworking

A wireless communication device that transmits a wireless signal by carrying out linear precoding processing using a plurality of transmission antennas is provided with: a phase pattern control unit for selecting a phase pattern that reduces peak-to-average power ratio; a phase rotation unit for carrying out phase rotation on a modulation signal using the phase pattern selected in the phase pattern control unit; a control signal generation unit for generating a control signal based on the phase pattern selected in the phase pattern control unit; and a preceding unit for carrying out linear precoding processing on output signals from the phase rotation unit and output signals from the control signal generation unit.

Wireless communication device and wireless communication method

ATM Routing Algorithms with Multiple QOS Requirements for Multimedia Internetworking (Special Issue on Multimedia on Demand)

This paper proposes two new types of maximum a posteriori probability (MAP) receivers for multiple-input-multiple-output and orthogonal frequency-division multiplexing mobile communications with a channel coding such as the low-density parity-check code. One proposed receiver employs the expectation-maximization algorithm so as to improve performance of approximated MAP detection. Differently from a conventional receiver employing the minimum mean-square estimation (MMSE) algorithm, it applies the recursive least squares (RLS) algorithm to the channel estimation in order to track a fast fading channel. For the purpose of further improvement, the other proposed receiver applies a new adaptive algorithm that can be derived from the message passing on factor graphs. The algorithm exploits all detected signals but one of targeted time, and can gain a considerable advantage over the MMSE and RLS. Computer simulations show that the first proposed receiver is superior in channel-tracking ability to the conventional receiver employing the MMSE. Furthermore, it is demonstrated that the second proposed receiver remarkably outperforms both the conventional and the first proposed ones.

Hiroshi Suzuki

Papers

10 Gbps millimeter-wave OFDM experimental system with iterative phase noise compensation

ATM Routing Algorithms with Multiple QOS Requirements for Multimedia Internetworking

Wireless communication device and wireless communication method

ATM Routing Algorithms with Multiple QOS Requirements for Multimedia Internetworking (Special Issue on Multimedia on Demand)

Adaptive MAP receiver via the EM algorithm and message passings for MIMO-OFDM mobile communications