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A neural network (NN)‐assisted probabilistic shaping (PS) distribution matcher is proposed, in which the model is simplified by a structured optimization method. The NN algorithm can encode the information sequence, making the signal obey the Gaussian distribution, and can directly restore the received signal. In addition, the algorithm uses the novel training method at both ends of the transmitter and receiver so that the system performance is significantly improved. PS system verification experiments have been carried out under 16QAM‐DMT modulation format. Under the hard decision forward error correction (FEC) threshold of 3.8*10−3 BER, the proposed system achieves 1.1 dB improvement compared to the traditional 16QAM‐DMT system. [ABSTRACT FROM AUTHOR]

In this article, we propose a three-dimensional (3D) multi-input multi-output (MIMO) channel model for air-to-ground (A2G) communications in unmanned aerial vehicles (UAV) environments, where the UAV transmitter and ground receiver are in motion in the air and on the ground, respectively. A novel angular estimation algorithm is proposed to estimate the real-time azimuth angle of departure (AAoD), elevation angle of departure (EAoD), azimuth angle of arrival (AAoA), and elevation angle of arrival (EAoA) based on the non-stationary nature of the channel model. In the model, we investigate the time-varying spatial cross-correlation functions (CCFs) and temporal auto-correlation functions (ACFs) with respect to the different moving directions and velocities of the UAV transmitter and ground receiver. Furthermore, we derive and study the Doppler power spectral densities (PSDs) and power delay profiles (PDPs) of the proposed channel model. Numerical results show that characteristics of the proposed channel model are very close to those of practical measurements, which provide a new and practical approach to evaluate the performance of next generation UAV-MIMO communication systems. [ABSTRACT FROM AUTHOR]

In this paper, we consider an energy harvesting device-to-device (D2D) communication system, where D2D transmitter can use mode A to directly communicate with D2D receiver or use mode B as a relay to assist cellular communication while communicating with D2D receiver by adopting non-orthogonal multiple access technology. Firstly, the outage probability expression in two modes is derived, and the communication mode is determined according to outage performance. Then, assuming that the full system information is available, the channel allocation and relay selection are completed by Kuhn–Munkres algorithm, and the offline power allocation of D2D users is realized by reinforcement learning. Next, the offline optimization results are taken as the training data set to train the neural network, and the optimal model of the transmission power is obtained. Considering the transmission power constraint, the online power allocation optimization algorithm is further proposed. Numerical results demonstrate the accuracy of derived outage probability, and the proposed resource allocation algorithm can improve the performance of hybrid system. [ABSTRACT FROM AUTHOR]

• Multiple-Input Multiple-Output (MIMO) is a wireless technology that uses multiple transmitters and receivers to transfer more data at the same time. • A high performance belief propagation detection-decoding algorithm for NB-LDPC MIMO codes with a low complexity approach. • Vertical Shuffle Schedule (VSS) reduces processing latency and therefore introduces greater flexibility into the receiver. • A dynamic approach can detect the closest point to the channel observation without calculating all the candidate symbols in a constellation. MIMO systems exploit multi-path propagation in a rich broadcast environment to improve throughput and performance of digital communication systems. The correspondent demappers require additional computational complexity. In this paper, a new detection-decoding approach based on vertical shuffle scheduling is proposed. Space exploration for the maximum likelihood detection is reduced to a dynamic region that surrounds the received symbol. Thus, a dynamic approach is proposed to detect the closest point of the channel observation without calculating all the candidate symbols in a constellation. In addition, a novel method based on EXIT chart study is proposed to find the sufficient number of neighboring points to search around a local minimum and then compute by recursion their Euclidean distances. Compared to the conventional Maximum Likelihood detector, the proposed algorithm allows a reduction in the computational complexity, in terms of number of multiplication, reaching 98%. The simulation results show that the proposed algorithm outperforms the state-of-the-art algorithms like MMSE, sphere decoding, DBTC and DaVinci codes. [ABSTRACT FROM AUTHOR]

Despite their near-noise power emission, ultra wideband (UWB) radios, particularly direct-sequence ultra wideband (DS-UWB), are still possible to cause harmful interference to legacy radio systems. When they participate in a large dense cognitive radio network (CRN) and transmit simultaneously, their joint power emission would be disastrous if without control. We address this problem by imposing a limit on the aggregate power emission of DS-UWB CRN. The limit is negotiable. It takes effect by letting each transmitter adapt to a spectrum void defined as the area below the limit itself and above the interference temperature experienced instantly by the transmitter. We propose a water-filling algorithm that maximises the sum capacity while enabling each transmitter to fit its power spectral density into, and thus to make the most of, the spectrum void. The algorithm is performed locally at the transmitter with low complexity. Numerical analysis based on a realistic office network shows that the algorithm can bring the aggregate power emission even down below the Federal Communications Commission limit for individual UWB device, but still guarantees a given bit-error performance to nearly 40 active users. [ABSTRACT FROM AUTHOR]

Standard power control techniques are not deployable in Aloha networks due to lack of central controlling entity and/or inefficiency of such algorithms in large networks with bursty traffic. To handle this problem in practice, simple transmission power selection algorithms are used for ranging and/or combating harsh channel conditions. In such algorithms, the transmission power is steadily increased by an amount called power step, until the packet is successfully transmitted. Noting that ranging is the major concern of this approach, small power steps are ideal for its operation. However, as we will show in this paper, using small power steps with this algorithm causes a throughput collapse in large networks, when capture effect is considered in the analysis. In the asymptotic case, the throughput of this algorithm will be less than the throughput of the Binary Exponential Backoff (BEB) scheme which only uses a single power level. To show these results, we will present an asymptotic analysis of this algorithm with small power steps in an ideal communication channel where BEB is used as the retransmission scheme. In order to strengthen the results, we will prove the existence of better choices for power steps by extending the analysis for large power steps and we will show that properly chosen large power steps guarantee higher throughputs and require approximately the same average powers as small power steps. Our analysis and simulation results show that small power steps should be avoided with the mentioned power selection algorithm except probably for ranging and once the ranging process is complete, larger power steps should be used to exploit the capture effect. [ABSTRACT FROM AUTHOR]

Emergency responders often experience poor quality wireless communications due to the complex radio-frequency propagation environment encountered at a typical emergency response location, such as an apartment complex, office building, or other large building structure. Our previous theoretical analysis in conjuction with simulation studies suggests that optimizing arrays of randomly located wireless transmitters can provide a significant increase in the received signal level for a receiver located in the array volume. Here we present experimental results from the application of our initial algorithm in representative complex propagation environments. Several different scenarios are included in the experiments to demonstrate the effectiveness of the optimization approach in an environment that contains a variety of scattering objects. For the various scenarios, we observed at least a 7 dB median gain over a single transmitter when the array consists of four transmitters. [ABSTRACT FROM AUTHOR]

The demand on wireless communications to provide high data rates, high mobility, and high quality of service poses more challenges for designers. To contend with deleterious channel fading effects, both the transmitter and the receiver must be designed appropriately to exploit the diversity embedded in the channels. From the perspective of receiver design, the ultimate goal is to achieve both low complexity and high performance. In this article, we first summarize the complexity and performance of low-complexity receivers, including linear equalizers and decision feedback equalizers, and then we reveal the fundamental condition when LEs and DFEs collect the same diversity as the maximum-likelihood equalizer. Recently, lattice reduction techniques were introduced to enhance the performance of low-complexity equalizers without increasing the complexity significantly. Thus, we also provide a comprehensive review of LR-aided low-complexity equalizers and analyze their performance. Furthermore, we describe the architecture and initial results of a very-large-scale-integration implementation of an LR algorithm. [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]