Low Complexity Adaptive Detection of Short CPM Bursts for Internet of Things in 6G.

With the standardization and commercialization of 5G, research on 6G technology has begun. In this paper, a new low-complexity soft-input-soft-output (SISO) adaptive detection algorithm for short CPM bursts is proposed for low-power, massive Internet of Things (IoT) connectivity in 6G. First, a time-invariant trellis is constructed on the basis of truncation in order to reduce the number of states. Then, adaptive channel estimators, recursive least squares (RLS), or least mean squares (LMS), are assigned to each hypothetical sequence by using the recursive structure of the trellis, and per-survivor processing (PSP) is used to improve the quality of channel estimation and reduce the number of searching paths. Then, the RLS adaptive symbol detector (RLS-ASD) and LMS adaptive symbol detector (LMS-ASD) could be acquired. Compared to using a least-squares estimator, the RLS-ASD avoids matrix inversion for the computation of branch metrics, while the LMS-ASD further reduces the steps in the RLS-ASD at the cost of performance. Lastly, a soft information iteration process is used to further improve performance via turbo equalization. Simulation results and analysis show that the RLS-ASD improves performance by about 1 dB compared to the state-of-the-art approach in time-variant environments while keeping a similar complexity. In addition, the LMS-ASD could further significantly reduce complexity with a power loss of approximately 1 dB. Thus, a flexible choice of detectors can achieve a trade-off of performance and complexity.

A Radio Environment Map Updating Mechanism Based on an Attention Mechanism and Siamese Neural Networks.

A radio environment map (REM) is an effective spectrum management tool. With the increase in the number of mobile devices, the wireless environment changes more and more frequently, bringing new challenges to REM updates. Traditional update methods usually rely on the amount of data collected for updating without paying attention to whether the wireless environment has changed enough. In particular, a waste of computational resources results from the frequently updated REM when the wireless environment does not change much. When the wireless environment changes a lot, the REM is not updated promptly, resulting in a decrease in REM accuracy. To overcome the above problems, this work combines the Siamese neural network and an attention mechanism in computer vision and proposes an update mechanism based on the amount of wireless environmental change starting from image data. The method compares the newly collected crowdsourced data with the constructed REM in terms of similarity. It uses similarity to measure the necessity of the REM to be updated. The algorithm in this paper can achieve a controlled update by setting a similarity threshold with good controllability. In addition, the effectiveness of the algorithm in detecting changes of the wireless environment has been demonstrated by combing simulation data.

Blind Turbo Equalization of Short CPM Bursts for UAV-Aided Internet of Things.

With the surge of Internet of Things (IoT) applications using unmanned aerial vehicles (UAVs), there is a huge demand for an excellent complexity/power efficiency trade-off and channel fading resistance at the physical layer. In this paper, we consider the blind equalization of short-continuous-phase-modulated (CPM) burst for UAV-aided IoT. To solve the problems of the high complexity and poor convergence of short-burst CPM blind equalization, a novel turbo blind equalization algorithm is proposed based on establishing a new expectation-maximization Viterbi (EMV) algorithm and turbo scheme. Firstly, a low complexity blind equalization algorithm is obtained by applying the soft-output Lazy Viterbi algorithm within the EM algorithm iteration. Furthermore, a set of initializers that achieves a high global convergence probability is designed by the blind channel-acquisition (BCA) method. Meanwhile, a soft information iterative process is used to improve the system performance. Finally, the convergence, bit error rate, and real-time performance of iterative detection can be further improved effectively by using improved exchange methods of extrinsic information and the stopping criterion. The analysis and simulation results show that the proposed algorithm achieves a good blind equalization performance and low complexity.

Detection of Transmitted Power Violation Based on Geolocation Spectrum Database in Satellite-Terrestrial Integrated Networks.

This paper investigates the detection of the transmitted power violation (TPV) in the satellite-terrestrial integrated network, where the terrestrial base station may break the spectrum policies so that severe damages are made to the satellite systems. Due to the lack of prior information on specific abnormal behaviors, this problem is complex and challenging. To tackle it, we first turn to the geolocation spectrum database based detecting framework, where not only the tasks of each segment but also the spectrum policies are specified. Then, the ternary hypothesis test and the generalized Neyman-Pearson (GMNP) test criterion are applied to maximize the detection probability under the false-alarm constraint. What is more, the Abnormal after Normal (AaN) detector is developed to simplify the analysis. Finally, simulations are conducted to demonstrate that the proposed detector can realize the detection of TPV in most cases at the expense of less than 10% detection probability.

Massive MIMO-Based Distributed Signal Detection in Multi-Antenna Wireless Sensor Networks.

For massive multiple-input multiple-output (MIMO) distributed wireless sensor networks, this paper investigates the role of multi-antenna sensors in improving network perception performance. First, we construct a distributed multi-antenna sensor network based on massive MIMO. By using the anti-fading characteristics of multi-antennas, it is better to achieve accurate detection than the single-antenna sensor network. Based on this, we derive a closed-loop expression for the detection probability of the best detector. Then, we consider the case that the sensor power resources are limited, and thus we want to use finite power to achieve higher detection probability. For this reason, the power was optimized by the alternating direction method of multipliers (ADMM). Moreover, we also prove that only statistical channel state is needed in large-scale antenna scenarios, which avoid the huge overhead of channel state information. Finally, according to the simulation results, the multi-antenna sensor network has better detection performance than the single-antenna sensor network which demonstrates the improved performance of the proposed schemes and also validates the theoretical findings.

Partition-Based Joint Placement of Gateway and Controller in SDN-Enabled Integrated Satellite-Terrestrial Networks.

The Integrated Satellite-Terrestrial Networks (ISTNs) with Software-Defined Networking (SDN) incorporated have become the emerging architecture and have attracted considerable attention recently. Therein, the joint gateway and controller placement problem is of fundamental significance for designing ISTNs with flexible and efficient management capabilities. Hence, how to achieve network reliability maximization with low network latency in the joint placement problem is worthy of in-depth study. In this paper, a network partition algorithm, Simulated Annealing Partition-based K-means (SAPKM), is proposed and analyzed for further ameliorating the problem. Experiments are performed on real network topologies to validate the effectiveness of our approach for the joint placement problem. Compared with the state-of-the-art existing works, numerical results show that SAPKM outperforms when deploying four or more controllers in terms of network reliability performance, network latency, and inter-plane latency with less than 2 ms to converge.

Auction-Based Secondary Relay Selection on Overlay Spectrum Sharing in Hybrid Satellite-Terrestrial Sensor Networks.

In this paper, we investigate the auction-based secondary relay selection on overlay spectrum sharing in hybrid satellite-terrestrial sensor networks (HSTSNs), where both the decode-and-forward (DF) and amplify-and-forward (AF) relay protocols are analyzed based on time division multiple access (TDMA). As both the primary and secondary networks are rational, honest but with incomplete network information, they prefer to obtain maximum possibility payoffs by the cooperation between the primary and secondary networks, and the competition among secondary networks. Hence, Vickery auction is introduced to achieve the effective and efficient secondary relay selection by distinct sub-time slot allocation for one shot in terms of a distributed manner. Finally, numerical simulations are provided to validate the effectiveness of the auction mechanism on cooperative spectrum sharing in HSTSNs for secondary relay selection. Besides, the effect of key factors on the performance of the auction mechanism are analyzed in details.

On the Performance of Cognitive Satellite-Terrestrial Relay Networks with Channel Estimation Error and Hardware Impairments.

This paper investigates the joint impact of channel estimation errors (CEEs) and hardware impairments (HIs) on the performance of a cognitive satellite-terrestrial relay network (CSTRN), where the terrestrial and satellite links are considered following Rayleigh fading and shadowed Rician (SR) fading distributions, respectively. Besides, the terrestrial relay is working in half-duplex decode-and-forward (DF) mode. By employing a general and practical model to account for both the CEEs and HIs at each link, the end-to-end signal-to-noise-plus-distortion-and-error ratio (SNDER) is first obtained for the CSTRN. Then, closed-form expressions for the outage probability (OP) and throughput of the CSTRN are obtained, which allows us to demonstrate the aggregate impact of CEEs and HIs. In order to gain insightful findings, we further elaborate on the asymptotic OP and throughput at the high signal-to-noise-ratio (SNR) condition and quantitatively determine the fundamental performance ceiling. Finally, Monte Carlo (MC) computer simulations are provided to verify the correctness of the analytical results. Besides, with representative numerical analysis's help, interesting findings are presented.

Performance Analysis of Two-Way Satellite Multi-Terrestrial Relay Networks with Hardware Impairments.

In this paper, we investigate the performance of a two-way hybrid satellite multi-terrestrial cooperative network with hardware impairments (HIs). Particularly, opportunistic relay selection scheme is employed in the considered network, which can substantially enhance the spectral efficiency and spatial diversity gain. By considering both the amplify-and-forward (AF) and decode-and-forward (DF) relay protocols, the closed-form expressions of the outage probability (OP) and throughput for the system are derived. Furthermore, in order to observe the effects of HIs level and the number of terrestrial relays on the system performance at high signal-to-noise ratios (SNRs), the asymptotic expressions of the system performance are also derived. Finally, computer results are presented to reveal the correctness of the analytical results.

Secure Multiuser Communications in Wireless Sensor Networks with TAS and Cooperative Jamming.

In this paper, we investigate the secure transmission in wireless sensor networks (WSNs) consisting of one multiple-antenna base station (BS), multiple single-antenna legitimate users, one single-antenna eavesdropper and one multiple-antenna cooperative jammer. In an effort to reduce the scheduling complexity and extend the battery lifetime of the sensor nodes, the switch-and-stay combining (SSC) scheduling scheme is exploited over the sensor nodes. Meanwhile, transmit antenna selection (TAS) is employed at the BS and cooperative jamming (CJ) is adopted at the jammer node, aiming at achieving a satisfactory secrecy performance. Moreover, depending on whether the jammer node has the global channel state information (CSI) of both the legitimate channel and the eavesdropper's channel, it explores a zero-forcing beamforming (ZFB) scheme or a null-space artificial noise (NAN) scheme to confound the eavesdropper while avoiding the interference to the legitimate user. Building on this, we propose two novel hybrid secure transmission schemes, termed TAS-SSC-ZFB and TAS-SSC-NAN, for WSNs. We then derive the exact closed-form expressions for the secrecy outage probability and the effective secrecy throughput of both schemes to characterize the secrecy performance. Using these closed-form expressions, we further determine the optimal switching threshold and obtain the optimal power allocation factor between the BS and jammer node for both schemes to minimize the secrecy outage probability, while the optimal secrecy rate is decided to maximize the effective secrecy throughput for both schemes. Numerical results are provided to verify the theoretical analysis and illustrate the impact of key system parameters on the secrecy performance.