The satellite-enabled Internet of Things (S-IoT) plays a crucial role by providing stable and global connectivity. However, its rapid growth brings many challenges in managing massive devices and addressing security threats. In this paper, we propose a new distributed network architecture combined with non-orthogonal multiple access (NOMA) for S-IoT. We consider a secure NOMA transmission scenario, where an appropriate legitimate device in an NOMA cluster is chosen as a jammer. To maximize the system’s total secrecy rate, we formulate an optimal secure NOMA clustering and power allocation, which is non-convex and difficult to solve directly. To solve the joint optimization problem, the original problem is transformed into two subproblems, and we propose staged algorithms to solve them efficiently. Firstly, a distributed iterative NOMA clustering algorithm is proposed to iteratively group S-IoT devices into multiple NOMA clusters. Then, a particle swarm optimization (PSO)-based optimal secure power allocation (OSPA) algorithm and a soft actor critic (SAC)-based OSPA are proposed to allocate powers for intra-cluster devices. The PSO/SAC-based OSPA algorithm can be performed among different NOMA clusters in a parallel way, which greatly improves the efficiency of power allocation. Finally, an optimal dynamic jammer strategy is proposed to dynamically select an idle device to act as a jammer, greatly improving the security performance of the systems. The simulation results demonstrate the advantages of the proposed distributed algorithms and also show that the proposed scheme greatly outperforms the state-of-the-art schemes in terms of the secrecy rate.

High throughput with constraints of high reliability and low latency brings a great challenge to random access (RA) protocol. A novel high reliability and low latency distributed random access (DiRA) scheme is proposed for RA systems with multiple access points (APs) and a central processing unit (CPU) to meet the requirements of the industrial Internet of Things (IIoT) networks. IIoT devices send packets to APs with the irregular repetition slotted ALOHA (IRSA) protocol. A comprehensive packet collision resolution scheme is proposed and employed at APs, which effectively combined the intra-slot, inter-slot, AP-CPU cooperation-based network-aided, and virtual multi-input multi-output (V-MIMO) packet collision resolution schemes. Then, the optimization problem of the temporal degree distribution of IRSA is formulated and solved under reliability and latency constraints. Numerical results show that the proposed protocol improves throughput and achieves a carried density of devices 257%, 292%, and 328% times that of the full cooperation-based RA scheme, for a target access success probability of 99.999% and a frame duration of 40 slots, for 4, 9, and 16 APs respectively.

Multiple input multiple output (MIMO) technology that has been broadly applied necessitates detectors with high performance and low complexity. The detection problem becomes severe when a large scale of antennas is employed, and a variety of approaches have been proposed to deal with this problem among which expectation propagation (EP) proves to be able to perform efficient detection, especially for high-order constellations. However, the traditional EP algorithm treats all variables in an independent way, making it unable to exploit additional relations among symbols that are useful for further potentials in improving the detection performance. Therefore, we propose to utilize the Tree-EP framework that introduces pairwise approximations for variables on a constructed tree graph. Following the Tree-EP paradigm, three algorithms are proposed among which a belief propagation (BP) based Tree-EP algorithm is of significant effectiveness. It can be proved in theory that the solution of the BP based Tree-EP algorithm is a fixed point of Bethe free energy, leading to guaranteed convergence by effective message passing. Simulation results demonstrate that the BP based Tree-EP outperforms EP in both canonical and massive MIMO systems with complexities of the same order.

To accommodate the proliferation of Internet-of-Things (IoT) applications, next-generation wireless communication networks, particularly the sixth-generation (6G), are expected to offer excellent support for the massive access of machine-type communication (MTC). In this paper, we investigate the grant-free random access (GFRA) employing orthogonal preambles in cell-free massive multiple-input multiple-output (mMIMO), which shows immense potential for enabling massive connectivity. In particular, we take into account the capture effect, defined as successful decoding despite preamble collisions, when the received signal-to-interference-plus-noise ratio (SINR) exceeds a predefined threshold. To this end, we develop an analytical framework to model GFRA with the capture effect adopting stochastic geometry. Subsequently, approximate analytical expressions for the received SINR and the access success probability for the typical GFRA frame structure are derived. Furthermore, leveraging these theoretical expressions, we formulate an optimization problem to determine the optimal preamble length that maximizes effective throughput. Simulation results validate the accuracy of our theoretical analyses and demonstrate the superior access performance of the optimized frame structure, whereas a frame structure with a constant preamble length does not consistently attain maximum effective throughput across varying user densities.

In this paper, we investigate the grant-based massive random access in cell-free (CF) massive multiple-input multiple-output (mMIMO) networks. A fixed cluster-based collision resolution random access (FCCRRA) protocol is proposed to mitigate severe pilot collisions for massive Internet of Things (IoT) by leveraging the difference in received power distribution across distributed access points (APs). Particularly, the cooperation among clustered APs and the enhanced normalized conjugate beamforming (ECB) are jointly exploited to achieve a low-complexity distributed contention resolution. Moreover, we derive the theoretical received power distribution of a user equipment (UE) across different APs and coverage areas and then formulate an optimization problem to determine a suitable parameter for fixed clustering. The results verify the superior performance of the proposed FCCRRA to benchmarks in terms of throughput and access success probability.

Massive machine-type communication (MTC) is expected to be one of the key concerns in future B5G and 6G. However, the explosive growth of MTC devices (MTDs) in Internet of Things (IoT) poses great challenges for the initial access procedure. To address this issue, we propose a cluster-aided collision resolution random access (CACRRA) protocol for grant-based random access (RA) in the distributed massive multiple input multiple output (mMIMO) systems, which takes full advantage of the spatial multiplexing provided by distributed mMIMO. By exploiting the difference of large-scale fading coefficients between different access points (APs) and MTDs, we further propose an exclusive clustering algorithm to cluster APs for each pilot. Moreover, the pilot collision resolution is performed distributedly in each cluster by leveraging the channel hardening and the favorable propagation of mMIMO channels, which achieves a large reuse factor of pilots. Simulation results show that the proposed CACRRA can efficiently resolve the pilot collision and significantly improve the access performance. Specifically, the proposed protocol can improve the RA throughput more than nine times compared to the conventional protocol in incredibly crowded scenarios.

In this paper, we study a joint user pairing and power allocation problem in the 5th generation (5G) satellite random access (RA) networks, where some user equipments (UEs) are assisted by relay satellite UEs to establish satellite access. We aim to maximize the total sum rate of the RA system by jointly optimizing user pairing and power allocation. The above joint optimization problem is a non-convex mixed-integer problem, which is challenging to solve. To solve this problem, we decompose it into two subproblems. Firstly, a problem for optimal user pairing is formulated to find the optimal user pairing relationship. To solve this subproblem efficiently, a Q-learning based distributed user pairing algorithm (QL-DUPA) is proposed, which converts the user pairing problem to a Q-learning process. The Q-learning process can achieve a near-optimal solution and is practically feasible. Then, a problem for optimal power allocation is formulated to find the optimal power allocation coefficients in each user pair. The subproblem is convex and the optimal solution is obtained using convex optimization. Next, a satellite RA scheme with collision resolution is proposed based on the joint optimization of user pairing and power allocation, and we analyze its total sum rate. Simulation results show that the proposed satellite RA scheme with collision resolution greatly outperforms the existing schemes in terms of total sum rate.

In this paper, an enhanced energy-harvesting irregular repetition slotted ALOHA (EEH-IRSA) is proposed for wireless sensors networks (WSNs). We consider that each sensor device has a finite-sized battery that is recharged by the harvested energy from the environment in a probabilistic manner. The performance of the proposed EEH-IRSA is analyzed by using the density evolution (DE) method and the optimal degree distribution for different battery capacity is obtained by using the differential evolution algorithm. Simulation results show that the throughput of the proposed EEH-IRSA scheme can achieve 1.14 packets/slot, which is about 44.5% larger than that of the traditional EH-IRSA.

By means of random multiple access (RMA), there is a prevailing tendency for massive machine-type terminals to have access into networks without numerous signaling interactions and frequent resource scheduling. Being one of the promising techniques to fulfill this requirement, sparse code multiple access (SCMA) is anticipated to notably broaden connections for the communication system. However, when applying RMA in the SCMA uplink, as massive terminals would randomly transmit their packets in an uncoordinated way, it is quite possible for some terminals to share an identical codebook so as to introduce the codebook collision problem. In this case, an indefinite number of terminals with possible codebook collisions would competitively share a same block of channel resources, resulting in an overloading status and deteriorated performance. To deal with this problem, we illustrate first the potential utilization of codebook collisions for RMA and propose then a partial Gaussian tree approximation (PGTA) detector to relieve heavy computational burden due to overloading conditions. With approximate decomposition of likelihood functions that has rarely been discussed, the proposed PGTA detector with proper message passing rules is able to approach the performance of a traditional message passing detector with considerably lower complexity.

Integrating massive MIMO and simultaneous wireless information and power transfer (SWIPT) technology over the Rician fading channel is an effective method to achieve green communication under 5G background. This paper investigates system that the base station (BS) transmits both wireless energy and information simultaneously to the users. The users send pilots by utilizing the harvested energy from the BS to estimate the channel state, and then obtain the downlink channel state through the channel’s reciprocity to complete uplink and downlink information transmission. We propose an iterative algorithm to jointly optimize the downlink transmitting power of the BS and the power splitting (PS) ratios for minimizing the sum of transmitting power with uplink and downlink signal-to-interference-plus-noise ratio (SINR) constraints. Simulation results prove that the proposed algorithm outperforms over existing related algorithms in terms of transmitting power.

This paper is investigating and comparing three channel models for the fifth generation (5G) wireless communications: the quasi deterministic radio channel generator (QuaDRiGa), the NYUSIM developed by New York University (NYU) and the more general 5G (MG5G) channel model. The three channel models employ different approaches to model the time non-stationary characteristics of the 5G wireless communications, such as the geometry-based drifting modeling and cluster birth-death methodology. Simulations are carried out using the three channel models to analyze the statistical properties including angle power spectrum (APS), power delay profile (PDP), temporal autocorrelation function (ACF), and spatial cross-correlation function (CCF). Simulation results show that the calculation of angular parameters contributes to the performance of APS, generation approaches of path powers and cluster parameters have significant impact on PDP performance, the performance of ACF and CCF varies mainly due to the calculations of path delays and angle spreads for the three channel models in urban macrocell (UMa) mobile NLOS environments.

In this paper, random interleaving multiplexing for random access scheme is proposed to further improve throughput and energy efficiency in satellite networks, which resort to the state-of-art physical layer techniques that can resolve multiple packet collisions. The bit and symbol level interleavers are randomly selected by active users from sets of interleavers, which are utilized to differentiate signals of different users sharing a subframe, and MAP detector can be employed to decode multiple superimposed packets. By further utilizing transmission diversity and interference cancellation technique, the proposed scheme can combine with Contention resolution diversity slotted ALOHA (CRDSA), called RIM-CRDSA protocols, and its an upper bound of throughput is derived. Simulation results show that the peak throughput of RIM-CRDSA can approach 2.0 bits/symbol, which largely outperform conventional random access protocols.

In this paper, we propose a new transmit power diversity scheme for contention resolution diversity slotted ALOHA (CRDSA) under total transmit power limitation in satellite networks. In the proposed scheme, the total transmit power of each device within a frame is considered to be the same, and allocated to multiple packet replicas, and the transmit power of each packet replica can be different, which enables the transmit power diversity. The threshold based capture model is employed at the gateway demodulator, and the recovery-error probability based on this model is derived. The threshold of capture and transmit powers of packet replicas are also jointly optimized to maximize the achievable sum rate (ASR) of CRDSA under total transmit power limitation. Simulation results show that the proposed scheme is more than 50% higher than the conventional one in terms of normalized ASR.

In this article, we propose an optimal irregular repetition slotted ALOHA (IRSA) under total transmit power constraint for random access (RA) in the Internet-of-Things (IoT)-oriented satellite networks, which is named as an optimal power-limited IRSA (PL-IRSA). In this proposal, the total transmit power for each satellite machine-type device (SMD) within a frame is considered to be the same and equally allocated into its multiple packet replicas. Due to a variant number of packet replicas, the transmit power of each packet replica for different SMDs may be different. The difference of transmit powers of packet replicas and path loss enhance the received power diversity, which is able to improve the throughput by using the capture effect. At the receiver side, we introduce a semi-analytical (SEA) model to approximate the physical-layer decoding and derive an asymptotic packet loss rate (PLR) based on this SEA model. From the derived results, an optimization problem is formulated and solved to find out the optimal degree distributions for different total transmit powers and code rates, which maximize the normalized system throughput. The simulation results demonstrate that the proposed optimal PL-IRSA can lead to significant performance improvement with respect to conventional ones.

In this paper, cooperative contention resolution diversity slotted ALOHA (CRDSA) with transmit power diversity is proposed for multi-satellite networks with partly overlapped coverage areas. The proposed scheme combines packet and power diversity transmission with efficient interference cancellation (IC) technique, which greatly improves the throughput. The packet loss ratio (PLR) of cooperative CRDSA with transmit power diversity is derived, and by using it as a fitness function, we formulate an optimization problem to find the optimized transmit power distribution, which further improves the throughput of cooperative CRDSA. Simulation results show that the cooperative CRDSA with optimized transmit power distribution remarkably outperforms the one with uniform transmit power distribution in terms of throughput.

Orbital angular momentum (OAM) supplies a new degree of freedom for the electromagnetic (EM) wave, which can be used to increase communication capacity. The amplitude of the OAM wave is null in the center of the beam and the distribution of the electric field intensity is not uniform, so the study of the optimal receiving location of single OAM wave is necessary. Furthermore, in order to efficiently receive OAM waves with different OAM modes simultaneously on single receiving antenna, the common reception sampling region of multi-mode OAM waves should also be studied. However, few experiments study the region of multi-mode OAM waves. Here, concentric circular arrays are proposed to generate OAM waves with different OAM modes. Based on theoretical formulations of its radiation fields in the cylindrical coordinate system, its transmission and reception characteristics would be analyzed. Basically, the common reception sampling region of multi-mode OAM waves can be confirmed by calculating function formulas of the upper and lower boundaries of the region or analyzing amplitudes and phases of the axial ratio of optimal receiving location of multiple OAM waves. Numerical results show that methods of confirming the region are feasible and simple. When other parameters besides frequency are the same and the optimal receiving location of certain OAM mode wave at certain frequency is known, optimal receiving locations of certain OAM mode wave at other frequencies can be confirmed easily, according to the formula related to the optimal receiving location and frequency.

Channel quality metric is an important parameter for the adaptive Long Term Evolution (LTE) uplink, and has a great effect on the performance of the uplink. By modelling the data transmission in the LTE uplink as the complex modulated data pass through the additive Gaussian channel in the transform domain, the authors proposed a new metric, the ratio of the received equivalent average bit power to the average bit error power based on the idea of the modulation error ratio. The adaptive scheme with the proposed metric in the LTE uplink is also given. Simulation results demonstrate that the authors' proposed metric has a better control of the block error rate and can improve % in the throughput compared with the best metric among the conventional channel quality metrics.

For the design and performance evaluation of potential massive multiple input and multiple output (MIMO) related algorithms, accurate channel models are indispensable. Spherical wavefront and array non-stationarity due to physically large antenna array are two new characteristics specific to massive MIMO propagation. In this paper, spherical wavefront effects can be well characterized by a predefined two-dimensional multi-confocal ellipse scattering geometry as in reference [1] and a 9- state Markov process is developed to capture the channel behaviors by array non-stationarity. Meanwhile, the associated approach to derive the state transition probabilities of the Markov process based on the outfield measurements is detailed. Finally, simulation results verify the validity of our proposal.

For the design, performance evaluation, and optimization of potential 3-D multiple input and multiple output (3-D MIMO) algorithms, an accurate stochastic channel model is indispensable. Simultaneously, it is desirable for the new 3-D MIMO channel model to be a further expansion of already well developed 2-D MIMO channel models to allow easy implementation and facilitate possible $3^{rd}$ generation partnership project standardization. This paper first shows our recent outfield channel measurement campaigns in urban macrocell scenarios with a planar antenna array and a crown-shaped antenna array installed on the base station and the user sides, respectively. A comprehensive methodology from the statistical analysis perspective to characterize the 3-D MIMO channel, particularly, in the elevation domain, is then elaborated upon. The framework of the new approach coincides with mainstream parametric stochastic models. Moreover, it is observed that, by recalculating the statistics of the large scale parameters as well as their cross-correlation matrix to rectify existent non-positive definite problem, adding distance dependent elevation angular spread and introducing a mixture of Von Mises Fisher distributions to describe the interdependence between azimuth and elevation, the accuracy of current standardized 3-D channel models can be improved upon. Finally, numerical results verify the validity of our proposal.

This paper proposes a selective AF-OFDM (Amplify-and-Forward, Orthogonal Frequency Division Multiplexing) relaying protocol, in which selective relaying policy is adequately utilized to improve the spectrum efficiency of cooperative multi-carrier transmission, and addresses the power minimization problem subject to a target quality of service (QoS) constraint for corresponding battery-operated systems. By transforming the original power minimization issue into a two-stage problem, i.e., a power loading subproblem and a selective relaying policy decision subproblem, an energy efficient power control (PC) technique is proposed. Specifically, the binary selective relaying policies are determined for each subcarrier based upon channel state information (CSI), while power loading can be mathematically solved by employing standard Lagrange techniques, leading to analytical solutions for individual transmit powers at the source and the relay. In order to further improve the energy efficiency, an independent \emph{min-min} relay selection policy is investigated by making use of available diversity of the multiple-relay channel. Numerical results illustrate the superiority of the proposed selective AF-OFDM relaying protocol and validate the efficiency of our proposed algorithms. It is shown that with PC, the proposed selective AF-OFDM relaying can significantly reduce the system power consumption, and the \emph{min-min} relay selection policy is more appropriate than the conventional \emph{max-min} strategy for our transmission protocol.

Selected mapping (SLM) works effectively in peak‐to‐average power ratio reduction for the single‐carrier frequency‐division multiple access (SC‐FDMA) system. However, the need for side information (SI) transmission results in data rate loss and increase of the system complexity. To avoid explicit SI transmission for SLM‐based SC‐FDMA systems, an SI embedding and detection scheme is proposed by exploiting the block pilot symbols . Specifically, to enable SI embedding, the authors propose to represent the SI index for each data symbol in the subframe by a location set of some selected subcarriers in the block pilot symbol. For SI detection, an optimal pilot‐aided maximum‐likelihood SI detector is presented. As a low‐complexity alternative, a suboptimal log‐likelihood ratio SI detector is also proposed. In addition, the authors provide theoretical analysis of SI detection error rate and discuss the effect of the proposed scheme on channel estimation. Simulation results show that, in SLM‐based SC‐FDMA systems, the proposed scheme significantly outperforms existing methods in terms of both SI detection and bit error rate (BER) and achieves the same BER performance as its counterpart with perfect SI.

An improved successive multiuser detection (SMUD) initial ranging (IR) algorithm with interference cancellation is presented for orthogonal frequency division multiple access systems followed by IEEE 802.16 m standard. The proposed method detects all the valid paths of IR subscriber stations, selects the path with the maximum signal‐to‐interference‐plus‐noise ratio, and estimates the parameters of the path by least‐square method. The estimated parameters are further processed by the parallel interference cancellation processing to improve their accuracy, and then the signal of the selected valid path is removed from the received signal in the successive interference cancellation (SIC) process. The proposed scheme can efficiently improve the parameter estimation accuracy of the selected valid path and reduce the residual multiple access interference in the SIC process. Simulation results show that the proposed method has a much better performance than the SMUD algorithm.

In the LTE system, uplink synchronization can be established through the random access channel, by which timing and frequency offsets between transceivers can be estimated and adjusted. As the single carrier frequency division multiple access (SC-FDMA) structure is utilized in LTE uplink, preambles for the random access channel should be generated and detected in the transform-domain at user equipments and the base station, respectively. However, in available literature, an explicit transform-domain signal model with respect to timing and frequency offsets has not been provided, and the impact of frequency offsets on the transform-domain signal is not analyzed either. Therefore, suffering from unknown interference among multiple user equipments, existing multiuser detection algorithms provide unsatisfied multiuser detection and estimation performance. In this paper, an explicit transform-domain signal model is first derived with respect to both timing and frequency offsets. The characteristic of transform-domain frequency offsets is then analyzed, which indicates that transform-domain frequency offsets behave differently with time-domain frequency offsets. After that, a multi-steps hybrid multiuser detection algorithm is proposed to improve the multiuser detection and estimation performance, and the Cramër-Rao bound to the accuracy of parameters estimation for the random access procedure is finally obtained. Simulation results show that the proposed algorithm is able to significantly improve the multiuser detection and estimation performance compared to existing ones.

An iterative maximum likelihood detection (IMLD) algorithm is proposed for the contention based orthogonal frequency-division multiple access (OFDMA) initial ranging (IR) process compliant with the IEEE 802.16 specifications. In contrast to the existing successive interference cancellation (SIC) based algorithms, which suffer both the impacts of channel estimation errors as well as uncanceled multiple access interference (MAI), the proposed IMLD cancels the reconstructed MAI from the received signal by iteratively constructing an objective function derived from the EM algorithm. This approach could implement the maximum likelihood detection in an adaptive way with the MAI decreasing over iterations. Theoretical analyses and Cramër-Rao lower bounds (CRLBs) to the accuracy of parameters estimation are also provided. Simulation results show that the IMLD is of quick convergence, and significantly improves the performance of multiuser detection and parameters estimation with lower complexity compared to available algorithms.

To avoid the transmission of side information and decrease the computational complexity in the conventional selected mapping (SLM) scheme, a novel set of conversion matrices (CMs) is proposed for the modified SLM scheme, and the signal processing scheme to remove the weighted factors on each subcarrier is also derived for wireless orthogonal frequency-division multiplexing (OFDM) systems. Computer simulations show that, without side information, the new scheme can achieve similar peak-to-average power ratio (PAPR) reduction and bit error rate (BER) performance with even lower computational complexity as compared with the available modified SLM schemes with the CMs.

We propose a new SNR estimation method based on the preamble for OFDM systems in frequency selective channels. The OFDM training symbols in the preamble are equalized by the known data in frequency domain and employed to estimate the noise variance. The second order moments of the received symbols are used to estimate the signal plus noise power in the OFDM packets. The SNRs on the subchannels and the average SNR of the packets can all be estimated. Simulation results show that the proposed method is robust to frequency selectivity in wireless channels, and its performance is considerably improved compared with the available methods.