Industrial IoT faces adversity in radio environment due to harsh physical condition and interference from co-located wireless systems. To mitigate these challenges, channel hopping is leveraged in a number of standards, including IEEE 802.15.4- 2015. The baseline version of the channel hopping described in this standard does not guarantee the best performance, especially in terms of network stability and latency. This paper illustrates the problem by means of a test-bed, and then proposes a channel blacklisting algorithm, which makes use of the channel quality statistics as they are stored in the Cloud. Claims of improvement are corroborated by the results obtained through simulation.

In this paper, we propose a cyclostationary noise model for narrowband power line communication (NB-PLC) based on frequency-shift (FRESH) filtering. The FRESH filters are designed to shape an input white noise spectrum to a cyclic spectrum extracted from experimental noise measurements. The noise modeling problem is considered as a system identification problem that minimizes the time-averaged mean square error (TA-MSE) between a reference measured noise and the model generated noise. We propose the normalized mean square error (NMSE) in the cyclic auto-correlation between the measured and the generated noise as a performance measure. The noise waveform generated by the proposed model shows a good agreement with that of measured noise in terms of the cyclic auto-correlation NMSE. In addition, the numerical results show a performance enhancement, in terms of the cyclic auto-correlation NMSE, over the time-region-based NB-PLC noise model presented in the literature, at the same model complexity. Moreover, the proposed model provides a scalable performance-complexity tradeoff.

Narrowband interference (NBI) is a significant impairment for multi-carrier modulation systems in both wireless and wireline channels. NBI may be generated by switching power supplies and legacy communication systems, and in many instances may be tonal in nature [1]. Recently, a novel method for mitigating the effect of NBI was proposed in [2] which works on minimizing the NBI spectral leakage by downconvering, nulling, and upconverting the received signal. In this paper we address the key question of how the algorithm performs as the number of interferers scales. We perform a distortion analysis on the received signal and obtain the following results under the assumption of an idealized analog front end: a) the distortion scales linearly with the number of interferers b) the distortion is independent of interferer frequency and amplitude. We also carry out a signal-to-interference noise ratio (S!NR) analysis of the proposed algorithm and show a good match between theory and simulation results.

Non-Gaussian noise/interference severely limits communication performance of narrowband powerline communication (PLC) systems. Such noise/interference is dominated by periodic impulsive noise whose statistics varies with the AC cycle. The periodic impulsive noise statistics deviate significantly from that of additive white Gaussian noise, thereby causing dramatic performance degradation in conventional narrowband PLC systems. In this paper, we propose a robust transmission scheme and corresponding receiver methods to combat periodic impulsive noise in OFDM-based narrowband PLC. Towards that end, we propose (1) a time-frequency modulation diversity scheme at the transmitter and a diversity demodulator at the receiver to improve communication reliability without decreasing data rates; and (2) a semi-online algorithm that exploits the sparsity of the noise in the frequency domain to estimate the noise power spectrum for reliable decoding at the diversity demodulator. In the simulations, compared with a narrowband PLC system using Reed-Solomon and convolutional coding, whole-packet interleaving and DBPSK/BPSK modulation, our proposed transceiver methods achieve up to 8 dB gains in Eb/N0with convolutional coding and a smaller-sized interleaver/deinterleaver.

Non-Gaussian noise/interference severely limits communication performance of narrowband powerline communication (PLC) systems. Such noise/interference is dominated by periodic impulsive noise whose statistics varies with the AC cycle. The periodic impulsive noise statistics deviates significantly from that of additive white Gaussian noise, thereby causing dramatic performance degradation in conventional narrowband PLC systems. In this paper, we propose a robust transmission scheme and corresponding receiver methods to combat periodic impulsive noise in OFDM-based narrowband PLC. Towards that end, we propose (1) a time-frequency modulation diversity scheme at the transmitter and a diversity demodulator at the receiver to improve communication reliability without decreasing data rates; and (2) a semi-online algorithm that exploits the sparsity of the noise in the frequency domain to estimate the noise power spectrum for reliable decoding at the diversity demodulator. In the simulations, compared with a narrowband PLC system using Reed-Solomon and convolutional coding, whole-packet interleaving and DBPSK/BPSK modulation, our proposed transceiver methods achieve up to 8 dB gains in Eb/N0with convolutional coding and a smaller-sized interleaver/deinterleaver.

The demand for smart environment technologies necessitates technical innovations in sensor networks. It is now well expected that smart sensor technologies will soon be deployed for a wide variety of applications. Interest in applications of sensor networks will keep growing and will create a new class of industrial standardizations in various different application domains. In this context, the papers in this special section cover a number of novel contributions related to energy efficient PHY-aided MAC techniques and sensor applications. Targeted are recent trends, research outcomes, practical developments of sensor infrastructure, reliable MAC solutions leveraging advanced PHY-layer aspects, and internet-of-things (IoT) solutions as well as compact and low-power sensor device technologies, which are applied to challenge measurement problems and applications.

It is now well expected that low-power sensor networks will soon be deployed for a wide variety of applications. These networks could potentially have millions of nodes spread in complex indoor/outdoor environments. One of the major deployment challenges under such diverse communication environments is providing reliable communication links to those low cost and/or battery-powered sensor nodes. Over the past few years, research in physical (PHY)-layer has demonstrated promising progresses on link reliability and energy efficiency. In modern medium access control (MAC) design, energy efficiency has become one of the key requirements and is still a hot research topic. In this overview, we provide a broad view encompassing both PHY- and MAC-layer techniques in the field of sensor networks with a focus on link reliability and energy efficiency. We review work in systems employing various PHY techniques in spatial diversity, energy efficient modulation, packet recovery, and data fusion, as well as MAC protocols in contention-based duty cycling, contention-free duty cycling, and hybrid duty cycling. The latest developments in cross-layer MAC designs that leverage PHY-layer techniques are presented. We also provide a synopsis of recent development and evolution of sensor network applications in industrial communications.

A Smart Grid intelligently monitors and controls energy flows in an electric grid. Having up-to-date distributed readings of grid conditions helps utilities efficiently scale generation up or down to meet demand. Narrowband powerline communication (PLC) systems can provide these up-to-date readings from subscribers to the local utility over existing power lines. A key challenge in PLC systems is overcoming additive non-Gaussian noise. In this paper, we propose to use a cyclostationary model for the dominant component of additive non-Gaussian noise. The key contributions are (1) fitting measured data from outdoor narrowband PLC system field trials to a cyclostationary model, and (2) developing a cyclostationary noise generation model that fits measured data. We found that the period in the cyclostationary model matched half of the period of the main powerline frequency, which is consistent with previous work in indoor PLC additive noise modeling.

In downlink multiuser multiple-input multiple-output (MIMO) systems, system performance highly depends on the reliability of downlink channel state information (CSI) at the base station (BS). In frequency division duplexing, the most practical solution is to have downlink CSI from the users fed back to the BS. Most work on this feedback design has assumed independent block fading channels. However, this paper proposes a new differential feedback scheme using the observation that the channel realizations are usually temporally correlated. The sum-rate loss assuming differential feedback is analyzed for a system with the number of users K equal to the number of transmit antennas M. When K >; M, a user selection algorithm based on an approximated signal-to-interference plus noise ratio (SINR) estimation is proposed. In simulation results, the proposed differential feedback scheme increases the sum-rate compared to previous differential feedback schemes. Moreover, the proposed user selection algorithm outperforms semi-orthogonal user selection in the moderate signal-to-noise ratio (SNR) region, despite requiring less feedback information. In low mobility channels, utilizing the channels' time correlation during quantization is shown to play a bigger role in determining sum-rate performance than multiuser diversity for most SNR regimes when a practical number of users is considered.

In modern wireless communications, systems that send a common information stream (called multicasting systems) are widely needed for distributing content such as television or radio. In this paper, the multiple antenna physical layer multicasting channel is considered, in which a common message is simultaneously transmitted to multiple single-antenna users. To achieve the capacity of this multicasting set-up, the covariance matrix of the transmit signal vector needs to be determined to maximize the smallest maximum achievable rate among all the users. In this paper, we develop a simple successive algorithm to determine the covariance matrix of the signal vector under the assumption that channel state information (CSI) is perfectly available at the transmitter. We first characterize properties of the capacity achieving covariance matrix and derive a closed-form expression for the matrix in the two-user case. We then derive a closed-form expression for the rate maximizing beamformer in the case of two users and propose a successive beamforming algorithm that generates the beamforming vector with low computational complexity. In the proposed precoding design scheme, the covariance matrix is successively constructed by orthogonalizing the subspace spanned by each user's channel vector until the maximum number of recursions (which is the same as the minimum of the number of transmit antennas and the number of users) is reached. The achievable rate of the proposed scheme is compared with the capacity of optimal transmission, transmit beamforming, antenna subset selection, and open-loop transmission which does not require CSI at the transmitter. As the number of users and/or antennas grows large, it is shown that the average achievable rate of the proposed scheme achieves the same average achievable rate scaling as the true capacity while reducing the computational complexity.

In orthogonal frequency division-multiple access (OFDMA) systems, the available downlink frequency is divided into subbands which are shared among users. The transmitter determines the users that are scheduled on each subband, and the data rate for each user. To enable these transmitter choices, each user feeds back a channel quality indicator (CQI), giving a compressed version of its observed signal-to-interference-noise ratio (SINR) on all subbands. In this paper, we classify existing CQI compression schemes into symmetric and asymmetric schemes. Symmetric schemes aim to accurately represent the CQI on all subbands, and are shown to be suitable when the receiver cannot accurately predict the subbands on which it will be scheduled. This happens, for instance, when the receiver is fast-moving, or when a round- robin scheduler is employed, or during low load conditions. Asymmetric schemes, on the other hand, greedily achieve accuracy only in high-SINR subbands, and are shown to perform well in high-load cellular networks with proportional fair scheduling and low-speed users. We propose one new scheme in each category. Simulation results for a 3GPP LTE cellular network show that our proposed schemes achieve similar or better performance than the current best-M feedback scheme used in LTE, with 30% less overhead.

The theory of multiple-input-multiple-output (MIMO) technology has been well developed to increase fading channel capacity over single-input-single-output (SISO) systems. This capacity gain can often be leveraged by utilizing channel state information at the transmitter and the receiver. Users make use of this channel state information for transmit signal adaptation. In this correspondence, we derive the capacity region for the MIMO multiple access channel (MIMO MAC) when partial channel state information is available at the transmitters, where we assume a synchronous MIMO multiuser uplink. The partial channel state information feedback has a cardinality constraint and is fed back from the basestation to the users using a limited rate feedback channel. Using this feedback information, we propose a finite codebook design method to maximize the sum rate. In this correspondence, the codebook is a set of transmit signal covariance matrices. We also derive the capacity region and codebook design methods in the case that the covariance matrix is rank one (i.e., beam- forming). This is motivated by the fact that beamforming is optimal in certain conditions. The simulation results show that when the number of feedback bits increases, the capacity also increases. Even with a small number of feedback bits, the performance of the proposed system is close to an optimal solution with the full feedback.

In downlink multiuser systems, multiple-input multiple-output (MIMO) technology can be leveraged to increase capacity in fading channels. Knowledge of channel state information at the transmitter (CSIT) is important to obtaining this capacity gain. It is unrealistic to obtain perfect CSIT, but partial CSIT can often be made available by using some practical feedback method. Based on partial CSIT, codebook techniques have been shown to improve performance of MIMO multiuser systems. Unfortunately, the codebook design problem has not been fully investigated. In this paper, we consider a multiuser multiple antenna downlink model with unitary precoding using a codebook consisting of 2B unitary matrices. The appropriate precoding matrix is chosen from this codebook, which is known to both the basestation and the receivers. By defining and using a carefully chosen distance function, the minimum distance of the codebook is shown to relate to the average sum-rate of the unitary precoded system. From our analysis, a codebook design criterion is developed based on maximizing the minimum distance of the codebook. Then, a framework for constructing the codebook is presented to maximize this minimum distance. Monte Carlo simulation results are given to show the average sum-rate capacity performance of the proposed codebook design.

We propose a new closed-loop MIMO (Multiple- Input Multiple-Output) signal processing scheme that combines transmit beamforming and spatial multiplexing in Rayleigh frequency-flat fading channel environment. Diversity gain is achieved by beamforming, and multiplexing gain by spatial multi- plexing. The proposed scheme is particularly useful for downlink communication, where the number of transmit antennas at the base station is greater than the number of receive antennas at the mobile. Beamforming weight vectors are computed at the receiver using the estimated channel matrix and are sent to the transmitter. The computation is based on the mutual information maximization criterion which reduces to a symmetric eigenvalue problem. The BER (Bit Error Rate) performance comparisons with other known schemes are also presented for the cases of the ML (Maximum Likelihood) decoding and the MMSE (Minimum Mean-Squared Error) nulling and ordered-cancellation decod- ing, through extensive Monte-Carlo simulation. The simulation results show that the proposed scheme has lower BER than the other schemes.