In fog radio access networks (F-RANs), caching popular content at edge fog access points (FAPs) helps alleviate the burden on base stations and backhaul links. To improve signal quality and connectivity, this work integrates cooperative communication and non-orthogonal multiple access (NOMA) into content-centric F-RANs with unreliable backhauls. Specifically, a NOMA-enabled joint transmission scheme is considered, where cache-enabled FAPs are coordinated into clusters to perform non-coherent joint transmission and NOMA, enabling multiplexing signals for multiple users. Under a hybrid caching policy and non-uniform Nakagami-mfading channels, the system performance is analyzed in terms of the successful content delivery probability and outage achievable rate. To optimize FAP coordination, the clustering problem is formulated as a coalitional game, and a low-complexity transfer-based clustering algorithm is designed. Furthermore, a hierarchical hybrid NOMA-based algorithm is developed to enhance multi-user access efficiency. Simulation results demonstrate that: 1) The NOMA-enabled joint transmission scheme allows the FAPs efficiently leverage the cached content to mitigate backhaul unreliability; 2) The NOMA-based design outperforms the orthogonal multiple access-based design by guaranteeing improved signal quality while maintaining the efficiency of multi-user access; 3) The coalitional game-based clustering algorithm effectively manages co-channel interference and improves spectrum utilization.

Gaining accurate channel state information (CSI) through a low-cost scheme has always been difficult in wireless communication systems. One of the current research directions is to obtain the CSI from the channel knowledge map (CKM) based on the users’ location. However, the direct utilization of CSI in CKM is hindered due to the sensitivity of instantaneous CSI to time-varying scattering environments and positioning errors. To address this issue, this paper proposes a channel prediction scheme that combines the CKM with historical user CSI to enhance the beamforming performance in multiple-input multiple-output (MIMO) systems. Specifically, the joint-orthogonal matching pursuit algorithm is used to accurately reconstruct the user channel with high precision using a limited number of pilots, and the multi-path components tracking algorithm is employed to extract the common and independent support sets of paths from the estimated channel and the CKM. Lastly, an adaptive and low-complexity predictor is utilized to obtain the future user CSI. The proposed scheme has been evaluated using multiple measured channel datasets, the results indicate a significant improvement in predicting channel cosine similarity compared to directly using the CSI from CKM and existing schemes.

Reconfigurable intelligent surfaces (RISs), as ar-tificial electromagnetic structures with programmable electro-magnetic characteristics, have the potential to enhance the signals collected by service base stations in multi-cell Internet of things (IoT) networks. This capability improves the information extraction and utilization in communication systems, presenting numerous promising applications in the sixth-generation (6G) communication systems-IoT network environment. This paper proposes an optimization framework for the transmission sum-rate in a multicell, multi-user wireless communication system assisted by RIS. Firstly, establish transmission power allocation constraints for training and data symbols based on the distances of users from the transmitter, along with corresponding sum-rate objective functions. Utilize the multidimensional feature parameters of the RIS and long short-term memory (LSTM) to establish the relationship between user mobility distance and transmission power. Then, based on the obtained power prediction data, calculate the corresponding sum-rate using the previously defined objective functions. The obtained predictions contribute to more accurately assessing future communication environments, thereby aiding in optimizing the performance of communication systems. Simulation results validate the significant potential of LSTM in RIS-assisted multi-user wireless network systems.

With the development of the 5G communication system, research on propagation characteristics of millimeter-wave (mm-wave) band has aroused significant attention. In particular, it is imperative to understand the similarities between the instantaneous channel characteristics of mm-wave band and sub-6 GHz band, which can be leveraged to facilitate beamforming and user scheduling. Towards this end, this paper presents a channel measurement campaign at both 4.9 GHz and 28 GHz in an urban micro-cell scenario using a virtual antenna array and conducts a detailed comparative study on the channel statistics. The measurement includes line-of-sight and non-line-of-sight propagation environments. Parameter extraction and analysis including power delay profiles (PDPs), path loss (PL), root mean square (RMS) delay spread (DS), and azimuth of arrival (AOA) shows that the 28 GHz channel has similar statistics compared to 4.9 GHz, while the 28 GHz band exhibits much fewer multipath components (MPCs). These results show that it is possible to leverage low-band channel estimations to facilitate the high-band, or vice versa.

Accurate channel state information (CSI) is crucial for optimizing system performance in wireless communications. One of the current research directions is to extract the CSI from the channel knowledge map (CKM) based on users' location. While such an approach is promising for large-scale CSI acquisition, e.g., pathloss, it is still questionable whether CKM can help to predict instantaneous CSI which is very sensitive to positioning error and scattering environment changes. To answer this question, this paper proposes a channel prediction scheme that combines the CKM with historical user CSI to improve the beamforming performance in multiple-input multiple-output (MIMO) systems. Specifically, it utilizes the complex amplitude information of multi-path components (MPCs) and employs a low-complexity method to predict the future MIMO CSI. Through experiments based on real-world channel data, the results demonstrate that the proposed scheme outperforms state-of-the-art ones that use the CKM alone or autoregressive schemes without CKM. In the non-line-of-sight scenarios, when the positioning error exceeds 0.525 m, small-scale CSI in CKM provides little gain. In line-of-sight environments, the threshold for the usability of small-scale CSI in terms of positioning error is approximately 0.725 m or slightly higher. When the positioning error is less than 0.225 m, the CKM is beneficial to predict instantaneous CSI in both scenarios.

Non-orthogonal multiple access (NOMA) has drawn much attention due to its capability in massive connections. It enables various joint designs with advanced technologies, e.g., cooperative transmission and aerial base station (ABS)-assisted networks. In this paper, we consider an efficient NOMA enabled cross-tier joint transmission design. This design jointly applies zero-forcing beamforming and NOMA to realize joint transmission and regular transmission for the users in different tiers. We evaluate the performance of the design under a large-scale clustered ABS-assisted network scenario. Theoretical expressions for the outage probability and area outage spectral efficiency are derived. Numerical results show that, although splitting power may lead to slight degradation for the macro-cell users, the system can still expect a decreased overall outage probability because joint transmission improves the received signal quality for the ABS-tier users. The macro-cell users may not always suffer outage performance degradation since they can keep receiving signals instead of staying idle until the cross-tier joint transmission is suspended as in the orthogonal scheme. Besides, with properly selected NOMA power allocation coefficient, a more reliable communication link can be guaranteed for the macro-cell user, if compared with the conventional orthogonal scheme.

Reconfigurable intelligent surfaces (RISs)-assisted Internet of Things (IoT) networks have attracted a great deal of interest due to the potential contributions to the next generation wireless networks. In this article, an adaptive RIS clustering system with weak channels or obstacles is investigated. Ideally, there is a suitable RIS that adopts the self-organized RIS-assisted (SORA) scheme between a base station (BS) and a user equipment (UE) for reflection transmission. However, due to the nonideal channel scenarios, a single RIS may not be capable of connecting the BS with the UE. To tackle these nonideal cases, we propose a complementary RIS-cluster-assisted (C-RCA) strategy by reflecting signals among clusters to improve the performance of the overall system. The performances of the two strategies in terms of outage probability (OP) and ergodic capacity (EC), derived using approximate closed-form expressions, are analyzed. By increasing the numbers of complementary RISs and the reflecting elements on each RIS simultaneously, these performance metrics as well as the effective throughput and energy efficiency (EE) are evaluated under different signal-to-noise ratios (SNRs). The obtained results demonstrated that, in contrast to the ideal case, the network EE of the proposed C-RCA strategy is higher than the SORA scheme under the larger target spectral efficiency (SE).

The acquisition of channel state information (CSI) is a vital and challenging task in wireless communications, especially for high mobility scenarios with rapidly varying channels. Channel prediction, as an effective approach to acquire CSI, is considered a promising approach to improve the communication performance. However, most of the current prediction methods with the assumption of slowly varying channel components cannot cope with rapid variation. In this paper, we propose a novel channel prediction scheme to incorporate the mobility of both transceivers and scatterers. Based on the estimated mobility parameters, the component-wise channel extraction results are derived and then the channel frequency response is predicted. In addition, the prediction performance and the computational complexity of the proposed scheme are analyzed and evaluated, and the relationship between the mobility parameter estimation error and the channel component prediction accuracy is revealed as well. Through predicted results based on the simulated and measured data, the performance of the proposed scheme surpasses the conventional schemes with genie-aided information.

Beamforming for multi-antenna wireless communication systems has been widely studied and applied in practice. However, its performance in high mobility scenarios deteriorates dramatically due to severe channel aging. This issue stimulates the research of channel prediction in high mobility scenarios. This paper studies the general high-mobility Doppler domain wireless channel characterization and reveals that: 1) the Doppler frequency of the cluster corresponding to the near scatterers varies approximately linearly over short periods; 2) the linear-fitting characteristics of autoregressive model leads to poor channel prediction performance; 3) the parameter estimation algorithms of the chirp model which encompasses the characteristics are particularly complex. Given the shortcomings of existing works, this paper adopts the short-time Fourier transform to pre-estimate the parameter range and leverages the polynomial Fourier transform to obtain the initial values of the parameters. The downhill simplex algorithm is used to search for the fine-grained values of the parameters. In addition, the orthogonal matching pursuit algorithm is utilized to reconstruct the sparse signal. Evaluation results under the COST2100 channel model and a channel measurement campaign indicate that the proposed scheme can enhance the channel prediction accuracy or reduce the computing overhead compared to the existing matrix completion and polynomial iteration method.

Aerial base stations (ABS) provide promising solutions for wireless coverage in adverse scenarios. By jointly designing with cooperative transmission, the system performance can even be boosted. In this paper, we consider an ABS-assisted cooperative system, where multiple ABSs hover around the macro base station (MBS) and relay the downlink signals through non- coherent joint transmission (NC-JT) to the user equipment (UE). Interfering nodes are randomly distributed over the 2D plane. Non-uniform line-of- sight (LoS) channel model is assumed for the desired signal propagation, while the communication links between ground terminals follow a distance related probabilistic LoS and non-line-of-sight (NLoS) channel model. Based on stochastic geometry framework, we derived closed form success probability for the cooperative system. Numerical results verify the accuracy of our expressions and show that jointly transmitting signals from the sky can bring in significant enhancement for the coverage performance of the system.

In this paper, the power allocation and number of multiplexed users in a downlink non-orthogonal multiple access (NOMA) system are studied. Considering user performance loss with the increase of multiplexed users, the interaction between the users who have accessed the sub-channel (AUs) and users who will access the sub-channel later (LAUs) is modeled as a multi-level Stackelberg game. To protect the benefit of AUs, the LAU, who acts as a follower, needs to pay for each AU and it will not access the sub-channel when its utility is non-positive. In this way, the number of multiplexed user can be well limited. We prove the total revenue maximization problem is convex when the signal to interference plus noise ratio (SINR) for each multiplexed user is higher than or equal to 0dB. Based on the above, we propose a multi-level price-based power allocation algorithm to limit the number of multiplexed users. Simulation results show that our proposed algorithm achieves better performance in terms of the total revenue and the achievable rate.

The use of aerial base stations (ABSs) is gaining attention due to its potentials to provide a flexible wireless coverage in adverse scenarios. Investigations on key performance metrics are desirable to ensure the feasibility of these ABS-assisted networks, especially when they are jointly designed with advanced transmission technologies, e.g., cooperative transmissions and non-orthogonal multiple access (NOMA). In this paper, we consider an ABS-assisted cooperative system with NOMA enabled to boost connectivity ability. It is assumed that multiple ABSs hover around a macro base station to relay downlink signals to user equipments, while interfering nodes are randomly distributed on the ground. We assume a more realistic channel model featured with a distance-related probabilistic line-of-sight and non-line-of-sight propagation, as well as non-identical small-scale fading. We derive the outage probability, and study the impacts of various parameters on the system performance. Numerical results unveil that: 1) The reliability of backhauls plays an important role in the system and determines the outage performance floor. 2) Joint transmissions from the sky can bring in a significant performance enhancement for the system. 3) The NOMA based transmission outperforms the traditional orthogonal multiple access with an improved outage performance, provided a properly selected NOMA power allocation coefficient.

In this paper, we investigate distributed subchannel allocation problem in small cell network (SCN) with non-orthogonal multiple access (NOMA) enhancement. Different from existing studies, we exploit NOMA for the purpose of mitigating aggregate inter-cell and intra-cell interference. The problem is analyzed through a locally cooperative game model, in which information is exchanged only among neighboring small cell base stations (SBSs) instead of all SBSs in the SCN. The existence of Nash equilibrium (NE) is confirmed by proving the formulated game as an exact potential game, which allows the application of best response algorithm to solve the problem locally or globally. It is shown that the aggregate interference can be more efficiently suppressed in the NOMA system, compared with traditional orthogonal multiple access (OMA) system. Furthermore, as the network grows denser, higher percentage of SBSs have the incentive to multiplex users via the NOMA technique, revealing the superiority of NOMA over OMA in future ultra dense network.

Aerial base station (ABS) provides a flexible solution for hotspot scenarios in traditional cellular networks, where macro-cell base stations (MBSs) are challenged by overwhelming short-time traffic demands. However, due to stretched transmission distances from sky, the system performance of this ABS-scheme is sometimes questioned. In this paper, we study the system performance of ABS-assisted networks by tools from stochastic geometry. The two-tier network consisting of MBSs and ABSs is modeled as the superposition of a Poisson point process over the infinite plane and a binomial point process within an overlapped finite circular area. We consider a more general probabilistic line-of-sight and non-line-of-sight propagation model and derive coverage probability as well as area spectral efficiency. Based on the proposed analytical framework, we study the impacts of various parameters and compare the ABS-scheme with a benchmark scheme, in which network densification is realized through deploying additional ground base stations (GBSs). Simulation results unveil that: 1) the height and ABS number should be carefully designed to obtain the optimal performance and 2) when the number of assisting BSs is limited, the ABS-scheme can achieve even better performance than the GBS-scheme, which validates the feasibility of enhancing system performance through ABSs in hotspot scenarios.

The conventional nonorthogonal multiple access (NOMA) strategy has secrecy challenge in coordinated multipoint (CoMP) networks. Under the secrecy considerations, this paper focuses on the security‐based NOMA system, which aims to improve the physical layer security issues of conventional NOMA in the coordinated multipoint (NOMA‐CoMP) networks. The secrecy performance of S‐NOMA in CoMP, that is, the secrecy sum‐rate and the secrecy outage probability, is analysed. In contrast to the conventional NOMA (C‐NOMA), the results show that the proposed S‐NOMA outperforms C‐NOMA in terms of the secrecy outage probability and security‐based effective sum‐rate.

MOTIVATION: Over the past decade, there has been a remarkable improvement in our understanding of the role of genetic variation in complex human diseases, especially via genome-wide association studies. However, the underlying molecular mechanisms are still poorly characterized, impending the development of therapeutic interventions. Identifying genetic variants that influence the expression level of a gene, i.e. expression quantitative trait loci (eQTLs), can help us understand how genetic variants influence traits at the molecular level. While most eQTL studies focus on identifying mean effects on gene expression using linear regression, evidence suggests that genetic variation can impact the entire distribution of the expression level. Motivated by the potential higher order associations, several studies investigated variance eQTLs. RESULTS: In this paper, we develop a Quantile Rank-score based test (QRank), which provides an easy way to identify eQTLs that are associated with the conditional quantile functions of gene expression. We have applied the proposed QRank to the Genotype-Tissue Expression project, an international tissue bank for studying the relationship between genetic variation and gene expression in human tissues, and found that the proposed QRank complements the existing methods, and identifies new eQTLs with heterogeneous effects across different quantile levels. Notably, we show that the eQTLs identified by QRank but missed by linear regression are associated with greater enrichment in genome-wide significant SNPs from the GWAS catalog, and are also more likely to be tissue specific than eQTLs identified by linear regression. AVAILABILITY AND IMPLEMENTATION: An R package is available on R CRAN at https://cran.r-project.org/web/packages/QRank . CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Small cell networks as an important evolution path for the next generation cellular networks, have drawn much attention. Different from traditional base stations (BSs) always-on model, we proposed a BSs on-off model where a new simple expression of the BS active probability of HetNet is derived. This model is more suitable for the practical network where BSs are not always-on. Based on this, we develop an analytical framework for downlink performance evaluation of small cell networks, adopting stochastic geometry theory. The system coverage probability (CP) is derived, which is analytical tractable and is useful for small cell networks. This new result is then applied to evaluate the 2-tier HetNet average rate (AR) and average energy efficiency (AEE). It is analytically shown that increasing the small cells density is beneficial to the system overall throughput, but not affect the system overall AEE obviously. While the range expansion is helpful to the overall AEE, but it will cause some loss in system throughput.

Antenna calibration to enhance the channel reciprocity between the uplink and downlink channels is necessary for the practical wireless system operating in the time division duplexing (TDD) mode. This paper investigates on the computation of the antenna calibration coefficients of the cooperative base stations' antennas in the network multiple-input and multiple-output (MIMO) system. An efficient scheme for computing the calibration coefficients for an arbitrary number of distributed antennas is proposed. In addition, we also propose two methods of refining the calibration coefficients for the proposed scheme. The evaluations of the proposed scheme and methods are performed through computer simulations.

This paper investigates the performance of multi- antenna spatial diversity in the overlaid wireless ad hoc network. We apply the more practical stochastic geometry tools to model the network. Then we derive closed-form expressions for the outage probability of two coexisting networks employing two basic diversity techniques, the maximum ratio combining (MRC) and the transmit antenna selection (TAS). Monte Carlo simulations verify the accuracy of our expressions, based on which, we further evaluate these two basic diversity schemes from the newly developed perspectives of transmission capacity and overlaid network. We explore the gain source for the transmission capacity of the overlaid network over that of a single network. Our work shows that employing low complexity diversity schemes at either transmit or receive side can significantly improve the overall transmission capacity requiring little or no feedback.

This paper investigates the transmission capacity of the secondary network in overlaid ad hoc networks with multi-antenna spatial multiplexing. Based on stochastic geometry tools, we study the effects of the node density and the transmission power of the secondary network on the transmission capacity performance. We derive the optimal node density for the secondary network, and subsequently the optimal transmit power ratio between the primary network and the secondary network. Our findings show that increasing the node density of the secondary network will result in an increase in the transmission capacity of the secondary network under a reasonable target outage probability assumption. The optimal node density and transmit power ratio are mainly influenced by the target outage probability and the permitted outage probability increment. On the other hand, numerical results show that the transmission capacity increases over the antenna number. Moreover, the antenna number has little effect on the optimal transmission power ratio.

In this paper, we investigate the performance of open-loop spatial multiplexing in overlaid ad hoc networks. Based on a stochastic geometry model, we derive exact closed-form expressions for the transmission capacity of two coexisting networks (a primary network vs. a secondary network) employing spatial multiplexing with zero-forcing (ZF) receivers. Simulation results confirm the accuracy of our expressions. In addition, we discuss the impact of multi-antenna scheme on the transmission capacity of the overlaid networks. Our findings show that the sum transmission capacity of the overlaid networks will improve significantly over that of a single network if a slight outage probability increase is allowable for the primary network. This improvement can be further boosted if spatial multiplexing is employed with more antennas. But when the antenna number exceeds a certain limit, spatial multiplexing may produce negative effect for the overlaid network.

In this paper, we investigate the performance of multiuser scheduling with open-loop spatial multiplexing in ad hoc networks. Closed-form expressions for outage probability and spatial throughput are derived for spatial multiplexing transmission with zero forcing (ZF) receiver and multiuser scheduling. Monte Carlo simulation results reveal that these expressions accurately demonstrate the performance of multiuser scheduling with open-loop spatial multiplexing. Based on these expressions, transmission capacity performance is analyzed and the effects of system parameters over network performance metrics are studied. Our finding indicates that spatial multiplexing with opportunistic multiuser scheduling can provide boosted network performance for ad hoc network by exploiting multiuser diversity gain, whilst requiring very low feedback requirements.