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The marriage of wireless big data and machine learning techniques revolutionizes the wireless system by the data-driven philosophy. However, the ever exploding data volume and model complexity will limit centralized solutions to learn and respond within a reasonable time. Therefore, scalability becomes a critical issue to be solved. In this article, we aim to provide a systematic discussion on the building blocks of scalable data-driven wireless networks. On one hand, we discuss the forward-looking architecture and computing framework of scalable data-driven systems from a global perspective. On the other hand, we discuss the learning algorithms and model training strategies performed at each individual node from a local perspective. We also highlight several promising research directions in the context of scalable data-driven wireless communications to inspire future research.

Consider a large-scale cellular network in which base stations (BSs) serve massive Internet-of-Things (IoT) devices. Since IoT devices are powered by a capacity-limited battery, how to prolong their working lifetime is a paramount problem for the success of cellular IoT systems. This paper proposes how to use BSs to manage the active and dormant operating modes of the IoT devices via downlink signaling in an energy-efficient fashion and how the IoT devices perform energy-efficient uplink power control to improve their uplink coverage. We first investigate the fundamental statistical properties of an activation signaling process induced by BSs that would like to activate the devices in their cells, which helps to derive the neat expressions of the true, false and total activation probabilities that reveal joint downlink power control and BS coordination is an effective means to significantly improve the activation performance. We then propose an energy-efficient uplink power control for IoT devices which is shown to save power and ameliorate the uplink coverage probability at the same time. We also propose an energy-efficient downlink power control and BS coordination scheme, which is shown to remarkably improve the activation and uplink coverage performances at the same time., Comment: 15pages, 7 figures

In this work, a novel energy-recycling single-antenna full-duplex (FD) radio is designed, in which a new 3-port element including a power divider and an energy harvester is added between the circulator and the receiver (RX) chain. The presence of this new element brings advantages over the state of the art in terms of both spectral efficiency and energy consumption. In particular, it provides the means of performing both an arbitrary attenuation of the incoming signal, which in turn increases the effectiveness of the state-of-the-art self-interference cancellation strategies subsequently adopted in the RX chain, and the recycling of a non-negligible portion of the energy leaked through the non-ideal circulator. The performance of this architecture is analyzed in a practically relevant 4-node scenario in which 2 nodes operate in FD and 2 nodes in half-duplex (HD). Analytical approximations are derived for both the achievable rates of the transmissions performed by the FD and HD radios and the energy recycled by the FD radios. The accuracy of these derivations is confirmed by numerical simulations. Quantitatively, achievable rate gains up to 40% over the state-of-the-art alternatives, in the considered scenario, are highlighted. Furthermore, up to 50% of the leaked energy at the circulator, i.e., 5% of the energy of the transmitted signal, can be recycled.

In this work, we consider a multiple-input single-output system in which an access point (AP) performs a simultaneous wireless information and power transfer (SWIPT) to serve a user terminal (UT) that is not equipped with external power supply. In order to assess the efficacy of the SWIPT, we target a practically relevant scenario characterized by imperfect channel state information (CSI) at the transmitter, the presence of penalties associated to the CSI acquisition procedures, and non-zero power consumption for the operations performed by the UT, such as CSI estimation, uplink signaling and data decoding. We analyze three different cases for the CSI knowledge at the AP: no CSI, and imperfect CSI in case of time-division duplexing and frequency-division duplexing communications. Closed-form representations of the ergodic downlink rate and both the energy shortage and data outage probability are derived for the three cases. Additionally, analytic expressions for the ergodically optimal duration of power transfer and channel estimation/feedback phases are provided. Our numerical findings verify the correctness of our derivations, and also show the importance and benefits of CSI knowledge at the AP in SWIPT systems, albeit imperfect and acquired at the expense of the time available for the information transfer.

Physical layer multicasting with opportunistic user selection (OUS) is examined for multicell multi-antenna wireless systems. By adopting a two-layer encoding scheme, a rate-adaptive channel code is applied in each fading block to enable successful decoding by a chosen subset of users (which varies over different blocks) and an application layer erasure code is employed across multiple blocks to ensure that every user is able to recover the message after decoding successfully in a sufficient number of blocks. The transmit signal and code-rate in each block determine opportunistically the subset of users that are able to successfully decode and can be chosen to maximize the long-term multicast efficiency. The employment of OUS not only helps avoid rate-limitations caused by the user with the worst channel, but also helps coordinate interference among different cells and multicast groups. In this work, efficient algorithms are proposed for the design of the transmit covariance matrices, the physical layer code-rates, and the target user subsets in each block. In the single group scenario, the system parameters are determined by maximizing the group-rate, defined as the physical layer code-rate times the fraction of users that can successfully decode in each block. In the multi-group scenario, the system parameters are determined by considering a group-rate balancing optimization problem, which is solved by a successive convex approximation (SCA) approach. To further reduce the feedback overhead, we also consider the case where only part of the users feed back their channel vectors in each block and propose a design based on the balancing of the expected group-rates. In addition to SCA, a sample average approximation technique is also introduced to handle the probabilistic terms arising in this problem. The effectiveness of the proposed schemes is demonstrated by computer simulations., Comment: Accepted by IEEE Transactions on Signal Processing

In Diffusion-based Molecular Communications, the channel between Transmitter Nano-machine (TN) and Receiver Nano-machine (RN) can be modeled by Additive Inverse Gaussian Channel, that is the first hitting time of messenger molecule released from TN and captured by RN follows Inverse Gaussian distribution. In this channel, a quantity-based modulation embedding message on the different quantity levels of messenger molecules relies on a time-slotted system between TN and RN. Accordingly, their clocks need to synchronize with each other. In this paper, we discuss the approaches to make RN estimate its timing offset between TN efficiently by the arrival times of molecules. We propose many methods such as Maximum Likelihood Estimation (MLE), Unbiased Linear Estimation (ULE), Iterative ULE, and Decision Feedback (DF). The numerical results shows the comparison of them. We evaluate these methods by not only the Mean Square Error, but also the computational complexity., Comment: 8 pages, 9 figures

LDPC code is a powerful error correcting code and has been applied to many advanced communication systems. The prosperity of software radio has motivated us to investigate the implementation of LDPC decoders on processors. In this paper, we estimate and compare complexity and power consumption of LDPC decoding algorithms running on general purpose processors. Using the estimation results, we show two power control schemes for software radio: SNR-based algorithm diversity and joint transmit power and receiver energy management. Overall, this paper discusses general concerns about using processors as the software radio platform for the implementation of LDPC decoders.

In the literature, J.-P. Cheng et al. have proposed the MIMO-OFDM PHY integrated (MOPI) scheme for achieving physical-layer security in practice without using any cryptographic ciphers. The MOPI scheme uses channel sounding and physical-layer network coding (PNC) to prevent eavesdroppers from learning the channel state information (CSI). Nevertheless, due to the use of multiple antennas for PNC at transmitter and beamforming at receiver, it is not possible to have spatial multiplexing nor use space-time codes in our previous MOPI scheme. In this paper, we propose a variant of the MOPI scheme, called P-MOPI, that works with a cryptographic cipher and utilizes precoding matrix index (PMI) as an efficient key-exchange mechanism. With channel sounding, the PMI is only known between the transmitter and the legal receiver. The shared key can then be used, e.g., as the seed to generate pseudo random bit sequences for securing subsequent transmissions using a stream cipher. By applying the same techniques at independent subcarriers of the OFDM system, the P-MOPI scheme easily allows two communicating parties to exchange over 100 secret bits. As a result, not only secure communication but also the MIMO gain can be guaranteed by using the P-MOPI scheme., Comment: 6 pages, 4 figures, topic on physical layer security in information theory