Performance evaluation of wireless local area network with congested fading channels

The IEEE 802.11ay wireless communication standard consents gadgets to link in the spectrum of millimeter wave (mm-Wave) 60 Giga Hertz band through 100 Gbps bandwidth. The development of promising high bandwidth in communication networks is a must as QoS, throughput and error rates of bandwidth-intensive applications like merged reality (MR), artificial intelligence (AI) related apps or wireless communication boggling exceed the extent of the chronic 802.11 standard established in 2012. Thus, the IEEE 802.11ay task group committee has newly amended recent physical (PHY) and medium access control (MAC) blueprints to guarantee a technical achievement especially in link delay on multipath fading channels (MPFC). However, due to the congestion of super bandwidth intensive apps such as IoT and big data, we propose to diversify a propagation delay to practical extension. This article then focuses on a real-world situation and how the IEEE 802.11ay design is affected by the performance of mm-Wave propagation. In specific, we randomize the unstable MPFC link capacity by taking the divergence of congested network parameters into account. The efficiency of congested MPFC-based wireless network is simulated and confirmed by advancements described in the standard.

On the Zero-Outage Secrecy-Capacity of Dependent Fading Wiretap Channels

It is known that for a slow fading Gaussian wiretap channel without channel state information at the transmitter and with statistically independent fading channels, the outage probability of any given target secrecy rate is non-zero, in general. This implies that the so-called zero-outage secrecy capacity (ZOSC) is zero and we cannot transmit at any positive data rate reliably and confidentially. When the fading legitimate and eavesdropper channels are statistically dependent, this conclusion changes significantly. Our work shows that there exist dependency structures for which positive zero-outage secrecy rates (ZOSR) are achievable. In this paper, we are interested in the characterization of these dependency structures and we study the system parameters in terms of the number of observations at legitimate receiver and eavesdropper as well as average channel gains for which positive ZOSR are achieved. First, we consider the setting that there are two paths from the transmitter to the legitimate receiver and one path to the eavesdropper. We show that by introducing a proper dependence structure among the fading gains of the three paths, we can achieve a zero secrecy outage probability (SOP) for some positive secrecy rate. In this way, we can achieve a non-zero ZOSR. We conjecture that the proposed dependency structure achieves maximum ZOSR. To better understand the underlying dependence structure, we further consider the case where the channel gains are from finite alphabets and systematically and globally solve the ZOSC. In addition, we apply the rearrangement algorithm to solve the ZOSR for continuous channel gains. The results indicate that the legitimate link must have an advantage in terms of the number of antennas and average channel gains to obtain positive ZOSR. The results motivate further studies into the optimal dependency structures.

Design of a SIMO Deep Learning-Based Chaos Shift Keying (DLCSK) Communication System

This paper brings forward a Deep Learning (DL)-based Chaos Shift Keying (DLCSK) demodulation scheme to promote the capabilities of existing chaos-based wireless communication systems. In coherent Chaos Shift Keying (CSK) schemes, we need synchronization of chaotic sequences, which is still practically impossible in a disturbing environment. Moreover, the conventional Differential Chaos Shift Keying (DCSK) scheme has a drawback, that for each bit, half of the bit duration is spent sending non-information bearing reference samples. To deal with this drawback, a Long Short-Term Memory (LSTM)-based receiver is trained offline, using chaotic maps through a finite number of channel realizations, and then used for classifying online modulated signals. We presented that the proposed receiver can learn different chaotic maps and estimate channels implicitly, and then retrieves the transmitted messages without any need for chaos synchronization or reference signal transmissions. Simulation results for both the AWGN and Rayleigh fading channels show a remarkable BER performance improvement compared to the conventional DCSK scheme. The proposed DLCSK system will provide opportunities for a new class of receivers by leveraging the advantages of DL, such as effective serial and parallel connectivity. A Single Input Multiple Output (SIMO) architecture of the DLCSK receiver with excellent reliability is introduced to show its capabilities. The SIMO DLCSK benefits from a DL-based channel estimation approach, which makes this architecture simpler and more efficient for applications where channel estimation is problematic, such as massive MIMO, mmWave, and cloud-based communication systems.

Dynamic event-triggered fault detection filter design for dynamical systems under fading channels

This article investigates the dynamic event-triggered fault detection filter (FDF) design problem for linear continuous-time networked systems, considering the fading channels phenomenon and randomly occurring faults. A dynamic event-triggered mechanism (ETM) is introduced to reduce the network bandwidth occupation more efficiently by utilizing an internal variable which can enlarge the event-triggered intervals. Besides, the Zeno phenomenon is eliminated fundamentally by ensuring that the event-triggered intervals are positive lower bounded. After that, sufficient conditions are derived to guarantee the stochastic stability of the residual system with a desired [Formula: see text] performance and the co-design criterion of the FDF and the dynamic ETM is developed. Finally, an unmanned surface vehicle (USV) system is used to illustrate the applicability of the presented approach.