To support delay-sensitive traffic in multi-channel cognitive radio systems, designing a channel access scheme faces two major challenges, namely, the long waiting time due to continuous channel occupancy of primary users (PUs) and the performance degradation due to transmission collisions among secondary users (SUs). To address both issues, we propose a two-phase channel access scheme, which consists of a distributed channel negotiation phase and a hopping-based channel access phase for each SU. Specifically, in its first phase, an SU attempts to negotiate a specific initial slot/channel differing from the ones chosen by other SUs. Then, in its second phase, the SU chooses a channel in each time slot in a hopping-based manner to transmit data, where the hopping starts from its initial channel and follows a common hopping sequence. Virtual channels are introduced to accommodate the situation when the number of SUs is larger than that of actual channels. The average maximal waiting time due to the channel negotiation phase is derived, and the effective capacity of the service process for each SU in the channel access phase is analyzed. Numerical results show that the proposed scheme can support a higher traffic load under the statistical delay constraint, as compared with fixed or random channel access schemes.
Network densification is one of the dominant evolutions to increase network capacity toward future cellular networks. However, the complex and random interference in the resultant interference-limited heterogeneous cellular networks (HCN) may deteriorate packet transmission reliability and increase transmission delay, which are essential performance metrics for system design in HCN. By modeling the locations of base stations (BSs) as superimposed of independent Poisson point process, we propose an analytical framework to investigate delay and reliability tradeoffs in HCN in terms of timely throughput and local delay. In our analysis, we take the BS activity and temporal correlation of transmissions into consideration, both having significant effects on the performances. The effects of mobility, BS density, and association bias factor are evaluated through numerical results.
A special permutation group of polar codes based on $N$ /4-cyclic shift is designed and analyzed for practical use. A permutation-transformation equivalence is firstly introduced to transfer the effect of permutation on the codeword side to the uncoded side. Then, we introduce the $N$ /4-cyclic shift permutation and analyze the conditions under which it can permute a codeword to another for polar codes that even do not fully respect partial order. We also reveal that the value assignment of frozen bits should follow specific rules related to the permutation pattern. Finally, a novel polar-specific implicit indication method is presented by applying the $N$ /4-cyclic shift permutation group to the practical wireless communication scenarios such as Physical Broadcasting Channel (PBCH) of a cellular network, which significantly simplifies the detection algorithm.
In this paper, we propose a comprehensive Polar coding solution that integrates reliability calculation, rate matching and parity-check coding. Judging a channel coding design from the industry's viewpoint, there are two primary concerns: (i) low-complexity implementation in application-specific integrated circuit (ASIC), and (ii) superior \& stable performance under a wide range of code lengths and rates. The former provides cost- \& power-efficiency which are vital to any commercial system; the latter ensures flexible and robust services. Our design respects both criteria. It demonstrates better performance than existing schemes in literature, but requires only a fraction of implementation cost. With easily-reproducible code construction for arbitrary code rates and lengths, we are able to report ``1-bit'' fine-granularity simulation results for thousands of cases. The released results can serve as a baseline for future optimization of Polar codes.
It is a promising technology to replace traditional transceiver design with neural network (NN)-based autoencoder to realize end-to-end communication. The joint optimization of multiple blocks helps the communication system to achieve better performance. However, this approach needs a differentiable channel modeling to train both NNs at the transceiver. For a non-differentiable channel in a real scenario, gradient backpropagation cannot be performed. In this paper, we propose a Kalman-based autoencoder framework to achieve gradient estimation and backpropagation by adding a control layer at the last layer of the encoder NN, which combines the rich feature representations learned by the NN with the Bayesian filter method based on Extended Kalman Filter (EKF) and Cubature Kalman Filter (CKF). According to simulation results, the proposed framework has a fast convergence rate and strong robustness in both additive white Gaussian noise (AWGN) and Rayleigh block fading (RBF) of perturbation scenarios.
Materials combining high porosity, mechanical durability, and multifunctionality have drawn significant research interest because of their potential in engineering applications. Herein, the porous air-dried nanocomposite aerogels containing reduced graphene oxide (RGO) and chitosan (CS) are fabricated by self-assembling an aqueous dispersion of graphene oxide and chitosan with the addition of hydroiodic acid (HI) followed by recasting the hybrid hydrogel with an ice-template method. The strong cross-linked composite aerogels obtained have reversible compressibility, exceptional elasticity, and high electrical conductivity, which are derived from the restacking inhibition and steric hindrance of the polymer chains. What's more, the successive soaking–drying experiments indicate that the as-prepared graphene-based aerogels exhibit excellent environmental stability and reuseability. The regenerated electrical conductivity remains almost the same and more than 90% of its maximum compressive stress at a strain of up to 92% is retained after five cycles. This makes them ideal candidates for potential applications in areas of supercapacitors and energy storage.
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