Signal estimation in cognitive satellite networks for satellite-based industrial internet of things

Satellite industrial Internet of Things (IIoT) plays an important role in industrial manufactures without requiring the support of terrestrial infrastructures. However, due to the scarcity of spectrum resources, existing satellite frequency bands cannot satisfy the demand of IIoT, which have to explore other available spectrum resources. Cognitive satellite networks are promising technologies and have the potential to alleviate the shortage of spectrum resources and enhance spectrum efficiency by sharing both spectral and spatial degrees of freedom. For effective signal estimations, multiple features of wireless signals are needed at receivers, the transmissions of which may cause considerable overhead. To mitigate the overhead, part of parameters, such as modulation order, constellation type, and signal to noise ratio (SNR), could be obtained at receivers through signal estimation rather than transmissions from transmitters to receivers. In this article, a grid method is utilized to process the constellation map to obtain its equivalent probability density function. Then, binary feature matrix of the probability density function is employed to construct a cost function to estimate the modulation order and constellation type for multiple quadrature amplitude modulation (MQAM) signal. Finally, an improved M 2 M ∞ method is adopted to realize the SNR estimation of MQAM. Simulation results show that the proposed method is able to accurately estimate the modulation order, constellation type, and SNR of MQAM signal, and these features are extremely useful in satellite-based IIoT

Performance of Cross-layer Design with Multiple Outdated Estimates in Multiuser MIMO System

By combining adaptive modulation (AM) and automatic repeat request (ARQ) protocol as well as user scheduling, the cross-layer design scheme of multiuser MIMO system with imperfect feedback is presented, and multiple outdated estimates method is proposed to improve the system performance. Based on this method and imperfect feedback information, the closed-form expressions of spectral efficiency (SE) and packet error rate (PER) of the system subject to the target PER constraint are respectively derived. With these expressions, the system performance can be effectively evaluated. To mitigate the effect of delayed feedback, the variable thresholds (VTs) are also derived by means of the maximum a posteriori method, and these VTs include the conventional fixed thresholds (FTs) as special cases. Simulation results show that the theoretical SE and PER are in good agreement with the corresponding simulation. The proposed CLD scheme with multiple estimates can obtain higher SE than the existing CLD scheme with single estimate, especially for large delay. Moreover, the CLD scheme with VTs outperforms that with conventional FTs

Spectral Efficiency of Multi-User Adaptive Cognitive Radio Networks

In this correspondence, the comprehensive problem of joint power, rate, and subcarrier allocation have been investigated for enhancing the spectral efficiency of multi-user orthogonal frequency-division multiple access (OFDMA) cognitive radio (CR) networks subject to satisfying total average transmission power and aggregate interference constraints. We propose novel optimal radio resource allocation (RRA) algorithms under different scenarios with deterministic and probabilistic interference violation limits based on a perfect and imperfect availability of cross-link channel state information (CSI). In particular, we propose a probabilistic approach to mitigate the total imposed interference on the primary service under imperfect cross-link CSI. A closed-form mathematical formulation of the cumulative density function (cdf) for the received signal-to-interference-plus-noise ratio (SINR) is formulated to evaluate the resultant average spectral efficiency (ASE). Dual decomposition is utilized to obtain sub-optimal solutions for the non-convex optimization problems. Through simulation results, we investigate the achievable performance and the impact of parameters uncertainty on the overall system performance. Furthermore, we present that the developed RRA algorithms can considerably improve the cognitive performance whilst abide the imposed power constraints. In particular, the performance under imperfect cross-link CSI knowledge for the proposed `probabilistic case' is compared to the conventional scenarios to show the potential gain in employing this scheme

Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation

Symbol-level precoding is a new paradigm for multiuser downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by designing the precoded signal of the multiantenna transmitter on a symbol level, taking into account both channel state information and data symbols. Previous literature has studied this paradigm for MPSK modulations by addressing various performance metrics, such as power minimization and maximization of the minimum rate. In this paper, we extend this to generic multi-level modulations i.e. MQAM and APSK by establishing connection to PHY layer multicasting with phase constraints. Furthermore, we address adaptive modulation schemes which are crucial in enabling the throughput scaling of symbol-level precoded systems. In this direction, we design signal processing algorithms for minimizing the required power under per-user SINR or goodput constraints. Extensive numerical results show that the proposed algorithm provides considerable power and energy efficiency gains, while adapting the employed modulation scheme to match the requested data rate

Performance of variable rate and variable power MQAM system based on bit error rate and channel estimates

We consider the effect of an imperfect channel estimate on a variable rate and variable power (VRVP) multilevel quadrature amplitude modulation (MQAM) system, where the transmit power and data rate are varied relative to the estimate of the received signal. Based on the VRVPMQAM system operating over a Rayleigh flat-fading channel, we derive a bit error rate (BER) estimator using a maximum a posteriori (MAP) estimation approach. We apply the BER estimator to the VRVP-MQAM system, and thereby derive and obtain system expressions which are applicable to any channel estimation technique. In addition, the resulting formulations are also useful for analyzing the effect of channel state information (CSI). Consequently, we derive and obtain an optimal solution for our proposed system and generate numerical results to compare the variations of system performance with imperfect CSI

Channel Estimation and Prediction Based Adaptive Wireless Communication Systems

Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at high Doppler shifts with same SNR and target BER=10-4. It was shown that the performance at higher Doppler frequency shifts (<30Hz) was improved by more than 2dB over channel estimation at target BER=10-4 and 32QAM constellation used

Study of the CAC mechanisms for telecommunications systems with adaptive links according to propagation conditions

This paper presents the framework and the activities of a PhD research work in progress supported by Alcatel Alenia Space in collaboration with TeSA and SUPAERO. It deals with Connection Admission Control (CAC) for Telecommunications Systems with adaptive links according to propagation conditions. Indeed, in high frequency bands communications, deep fadings may occur because of atmospheric propagation losses. The mitigation techniques used to counteract fades impacts the system capacity, therefore the CAC mechanism. The CAC which only uses current capacity information may lead to intolerable dropping of admitted connection, and thus breaches the QoS guarantees made upon connection acceptance. New CAC mechanisms shall be studied to take into account the capacity variation and the mitigation techniques (IFMT) developed to compensate the attenuation in Ka and above frequency range