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In this paper, we discuss four different optimization problems for distributed antenna systems (DAS) with and without D2D communication, respectively. The first and the third problems are maximizing spectral efficiency (SE) and energy efficiency (EE) of the DAS with D2D communication on the conditions of the minimum SE of DAS as well as D2D pair, the maximum transmit power of each remote access unit (RAU) and maximum transmit power of D2D transmitter. The second and the forth problems are maximizing SE of the DAS on the conditions of the minimum SE as well as the maximum transmit power of RAUs. We exploit the sub-gradient iteration method to obtain the optimal power allocation and summarize optimal power allocation algorithms for the first and second problems. We exploit fractional programming method to investigate the third and fourth problems and develop corresponding optimal power allocation algorithms. Simulation results demonstrate the effectiveness of the proposed power allocation algorithms and show the SE and EE of the DAS by using D2D communication are much better than DAS without D2D communication. [ABSTRACT FROM AUTHOR]

The versatility of simple electronic nodes and debugging of communication protocols in unlicensed frequency bands constitute the main reasons for the adoption of industrial wireless sensor networks (IWSNs). However, the industrial environments, in which IWSNs function, are characterized by a harsh impact of physical and electromagnetic factors that destabilize the operation of equipment and worsen the noise immunity of channels. To consider the effect of these two groups of factors on communication quality, we develop a novel model of an IWSN channel as the dependence of bit error probability (BEP) on signal distortions and interference impact. We found that direct sequence spread spectrum (DSSS) codes of a signal have different effects on the compensation of nonlinear signal distortions and external interference. Further, we propose an algorithm for the distribution of DSSS codes among real transmitters by BEP values in channels with known additive and multiplicative interference. Here, the distribution of codes is based on the minimax criterion. Finally, for cases when a signal is characterized by a-priori uncertainties of fading, we suggest an alternative algorithm for selecting a DSSS code based on Pareto bicriteria optimization. [Display omitted] • We model an IWSN channel with hardware signal distortion, fading and narrowband interference. • An algorithm for distributing DSSS codes among real transmitters minimizes BEP in the worst channel. • An algorithm for DSSS code selection with signal fading uncertainty reduces required computational costs. [ABSTRACT FROM AUTHOR]

In transmit-reference (TR) receivers, noise in the reference (pilot) pulse causes a noise × noise term in the decision statistic. This term severely degrades receiver performance. We propose a detection algorithm to decrease the noise in the reference pulse in TR receivers. Computer simulations show that at BER = 10−5, the proposed algorithm outperforms the existing algorithm by about 0.8 dB in both coded and uncoded scenarios. In high-rate applications, inter-symbol interference (ISI) drastically impairs the received signal. Monobit quantization intensifies the ISI and hence dramatically degrades the receiver performance. At first glance, channel coding increases ISI and seems useless to combat ISI. However, we propose to employ channel coding to overcome the severe performance loss caused by ISI. Simulation results show that in high SNR values, channel coding tackles the ISI problem especially when convolutional coding is used. Moreover, simulations reveal that convolutional coding is more robust to ISI compared to block coding schemes. Furthermore, the digital circuit design of coded/uncoded traditional and proposed monobit TR receivers is done in 0.18 µm CMOS technology at 2 V supply voltage. Simulations confirm the numerical results obtained in MATLAB. Finally, the power consumption of each receiver is reported. [ABSTRACT FROM AUTHOR]

Employing switchable directional antennas in the user equipment (UE) is becoming a popular method to replace conventional beamforming methods. This approach is mainly applicable to mmWave networks due to the small size of directional microstrip antenna elements on corresponding frequencies, and requires exploiting proper transmit antenna selection (TAS) schemes to obtain the optimal directivity of selected active antennas. TAS is rather complex in the heterogeneous cellular networks with underlaid D2D communication. For each D2D user, selecting transmit antennas with maximum radiation gain does not necessarily lead to the optimal throughput due to the potential interference that might be imposed on other high priority users, thus, finding the optimal transmit antennas of users is generally a challenging issue in networks with multi-antenna D2D users. In this work, based on Lagrangian relaxation method, we propose a novel and efficient transmit antenna selection and resource (channel and power) allocation (ASRA) for D2D mmWave networks. In order to validate the performance of our proposed algorithm, we devise another efficient low-complexity greedy-based ASRA as well. Numerical results verify the performance of our proposed Lagrangian-based ASRA in comparison to other methods. [ABSTRACT FROM AUTHOR]