User Selection Scheme Research Articles

A Novel User Selection Strategy with Incentive Mechanism Based on Time Window in Mobile Crowdsensing

With the rapid development of smart phones and wireless communication, mobile sensing has become an efficient environmental data acquisition method capable of accomplishing large-scale and highly complex sensing tasks. Currently, participants want to collect continuous data over a period of time. However, the number of participants varies widely in some periods. In view of this application background, this paper proposes a new incentive mechanism of extra rewards: premium and jackpot incentive mechanism (PJIM), and a new participant selection method based on time window: participant selection for time window dependent tasks (PS-TWDT). In the PJIM, the platform divides the time period of sensing tasks according to the time distribution of task participants and adopts different incentive strategies in different situations; at the same time, it introduces the prize pool mechanism to attract more participants to participate in the sensing task with fewer participants. In the PS-TWDT, we design a participant selection method based on dynamic programming algorithm. The goal is to maximize the data benefit while the sensing time of the selected participants covers the task time period. In addition, the updating strategy of participants’ credit value is added, and the credit value of participants is updated according to their willingness to participate in the task and data quality. Finally, simulation experiment verifies that the incentive mechanism and participant selection method proposed in this paper have good performance.

Emergency Communications Based on Throughput-Aware D2D Multicasting in 5G Public Safety Networks.

Emergency communications need to meet the developing demand of equipment and the complex scenarios of network in public safety networks (PSNs). Heterogeneous Cloud Radio Access Network (H-CRAN), an important technology of the 5th generation wireless systems (5G), plays an important role in PSN. H-CRAN has the features of resource sharing and centralized allocation which can make up for resource shortage in emergency communications. Therefore, an emergency communications strategy based on Device-to-device (D2D) multicast is proposed to make PSN more flexible and rapid. Nearby users can communicate directly without a base station through D2D. This strategy may guarantee high speed data transmission and stable continuous real-time communications. It is divided into three steps. Firstly, according to the distance between users, the alternative cluster head is divided. Secondly, two kinds of cluster head user selection schemes are developed. One is based on terminal power and the other is based on the number of extended users. Last but not least, the Hungarian Algorithm based on throughput-aware is used to channel multiplexing. The numerical results show that the proposed scheme can effectively extend the coverage of PSN and optimize the utilization of resources.

Zero-Forcing Oriented Power Minimization for Multi-Cell MISO-NOMA Systems: A Joint User Grouping, Beamforming, and Power Control Perspective

Future wireless communication systems have been imposed high requirement on power efficiency for operator's profitability as well as to alleviate information and communication technology (ICT) global carbon emission. To meet these challenges, the power consumption minimization problem for a generic multi-cell multiple input and single output non-orthogonal multiple access (MISO-NOMA) system is studied in this work. The associated joint user grouping, beamforming (BF) and power control problem is a mixed integer non-convex programming problem, which is tackled by an iterative distributed methodology. Towards this end, the near-optimal zero-forcing (ZF) BF is leveraged, wherein the semiorthogonal user selection (SUS) strategy is applied to select BF users. Based on these, the BF vectors and BF users are determined for each cell using only local information. Then, two distributed user grouping strategies are proposed. The first one, called channel condition based user clustering (CCUC), performs user grouping in each cell based on the channel conditions. This is conducted independently of the power control part and has low computational complexity. Another algorithm, called power consumption based user clustering (PCUC), uses both the channel conditions and inter-cell interference information to minimize each cell's power consumption. In contrary to CCUC, PCUC is optimized jointly with the power control. Finally, with the obtained user grouping and BF vectors, the resultant power allocation problem is optimally solved via an iterative algorithm, whose convergence is mathematically proven given that the problem is feasible. We perform Monte-Carlo simulation and numerical results show that the proposed resource management methods outperform various conventional MISO schemes and the non-clustered MISO-NOMA strategy in several aspects, including power consumption, outage probability, energy efficiency, and connectivity efficiency.

Multiuser Selection Criteria for MIMO-NOMA Systems With Different Detectors

Non-orthogonal multiple access (NOMA) is an effective way to improve the spectrum efficiency of multiple-input multiple-output (MIMO) systems, where this advancement can be fully exploited by employing a proper user selection strategy in the multiuser MIMO system. However, for multiuser scenarios, information-theoretic throughput may not be properly used as the performance indicator since the constraints at the receiver (e.g., suboptimal detectors) are not taken into consideration. In this paper, we adopt the error probability (EP) as the performance metric, which is equivalent to the practical throughput efficiency and can take the critical constraints into consideration. We analyze the pair-wise error probability (PEP) performance of different detectors and propose two kinds of user selection methods to minimize the PEP. To facilitate the detection performance evaluation, we further investigate the multiuser diversity of the proposed selection methods and derive a tight lower PEP bound for the case with randomly selected users. From the analytical and numerical results, we demonstrate that the proposed multiuser selection methods can suppress the inter-user interference effectively and achieve better performance than that of the state-of-the-art method.

Enhance Latency-Constrained Computation in MEC Networks Using Uplink NOMA

Non-orthogonal multiple access (NOMA) based mobile edge computing (MEC) networks can enhance delay-constrained computation. Most of the existing works focus on the energy or delay minimization, and the study on NOMA based MEC in terms of successful computation probability has been limited, which motivates this work. In particular, randomly deployed edge computing users are modeled as the homogeneous Poisson Point Process and are divided into two groups namely center group (C-group) and edge group (E-group) for uplink NOMA grouping. We propose a new hybrid offloading scheme in a NOMA-based MEC network that can operate in three different modes, namely partial offloading, complete local computation, and complete offloading. We firstly consider a NOMA grouping scenario where a user from the C-group and a user from the E-group are each given a fixed location. The probability that the computation can be completed within the given delay budget is derived and the optimal parameters, i.e., the time for offloading, the power allocation, and the offloading ratios for the two fixed users, are obtained. It reveals that the optimal offloading ratios are determined by the difference of the computational capability between the edge computing user and the MEC server, and that the locations of users have a big impact on the successful computation probability. Inspired by this, we further study three distance-dependent NOMA grouping schemes in the MEC offloading. Specifically, we provide closed-form mathematical expressions of the successful computation probability and its partial optimal solutions for these three schemes. Simulation results verify the accuracy of the analytical results and compare the performance of the proposed offloading scheme with the existing schemes. Insights on the pros and the cons of different user selection schemes are also provided.

Hybrid beamforming design based on unsupervised machine learning for millimeter wave systems

SummaryThis article proposes a hybrid beamforming design with reduced channel state information (CSI) feedback. We use a beam sweeping procedure to provide channel measurements and feed a CSI report scheme. Thereby, the base station (BS) can perform an adequate estimation of the channel characteristics with reduced signaling overhead. Consequently, we need short pilot sequences and very few precoding matrix indicators (PMIs) to properly describe channel behavior. Moreover, we also evaluate different user selection strategies based on unsupervised machine learning framework that exploits the channel information provided by the proposed beam sweeping scheme. Our performance evaluation indicates that the user selection based on fuzzy c‐means is able to efficiently explore the reduced CSI. The proposed hybrid beamforming scheme reduces the multi‐user interference and achieves significant gains in total data rate as channel conditions and interference environment becomes more challenging.

Joint Subcarrier and Power Allocation in NOMA: Optimal and Approximate Algorithms

Non-orthogonal multiple access (NOMA) is a promising technology to increase the spectral efficiency and enable massive connectivity in 5G and future wireless networks. In contrast to orthogonal schemes, such as OFDMA, NOMA multiplexes several users on the same frequency and time resource. Joint subcarrier and power allocation problems (JSPA) in NOMA are NP-hard to solve in general. In this family of problems, we consider the weighted sum-rate (WSR) objective function as it can achieve various tradeoffs between sum-rate performance and user fairness. Because of JSPA's intractability, a common approach in the literature is to solve separately the power control and subcarrier allocation (also known as user selection) problems, therefore achieving sub-optimal result. In this work, we first improve the computational complexity of existing single-carrier power control and user selection schemes. These improved procedures are then used as basic building blocks to design new algorithms, namely Opt-JSPA, $\varepsilon$-JSPA and Grad-JSPA. Opt-JSPA computes an optimal solution with lower complexity than current optimal schemes in the literature. It can be used as a benchmark for optimal WSR performance in simulations. However, its pseudo-polynomial time complexity remains impractical for real-world systems with low latency requirements. To further reduce the complexity, we propose a fully polynomial-time approximation scheme called $\varepsilon$-JSPA. Since, no approximation has been studied in the literature, $\varepsilon$-JSPA stands out by allowing to control a tight trade-off between performance guarantee and complexity. Finally, Grad-JSPA is a heuristic based on gradient descent. Numerical results show that it achieves near-optimal WSR with much lower complexity than existing optimal methods.

User Selection for Millimeter Wave Non-Uniform Full Dimensional MIMO

The millimeter wave (mmWave) based full-dimensional (FD) MIMO communication is one of the promising technology to fulfill the demand of high data rate for the sixth generation (6G) services including 6D hologram, haptic and multi-sensory communications. In order to satisfy the requirements of 6G applications, we investigate a non-uniform rectangular array (NURA) structure with FD-MIMO antenna systems for the multiuser mmWave communications. For the dense scenarios where the number of users to be served is high, we propose user selection algorithms for both digital and hybrid transceiver designs in FD-MIMO with NURA for the multiuser mmWave communications. For the digital transceivers, the users are selected based on their channel correlation considering FD-MIMO with NURA structures. For the hybrid transceivers, sequential user and beam selection is performed using the correlation between the beamspace channels in FD-MIMO with NURA case. The superiority of the NURA compared to uniform antenna structure is shown through the performance evaluations in the multiuser mmWave communications. Besides, the sum data rate results and complexity analysis denote the feasibility of the proposed algorithms compared to the joint user and beam selection schemes.

Outage Probability of Cooperative NOMA Networks Under Imperfect CSI With User Selection

Non-orthogonal multiple access (NOMA) is a promising spectrally-efficient technology to satisfy the massive data requirement of the next-generation wireless communication networks. In this paper, we consider cooperative non-orthogonal multiple access (CNOMA) networks with relaying user selection, where a two-stage user selection scheme is adopted to optimize the received signal-to-noise ratio (SNR) of the weak user. We derive analytical expressions of the outage probability of the CNOMA users under two different types of channel estimation errors. Afterwards, we investigate the asymptotic characteristics the outage probability of the CNOMA systems in the high SNR regimes. Our results show that for the case of constant variance of the channel estimation error, the outage probability of each user is saturated and cannot be improved by increasing the transmit power of the access point. In contrast, there is no performance bottleneck of the outage probability for all the users when the variance of the channel estimation errors decease with SNR, whilst fully diversity gain is achieved by the weak user.

Cross PHY/APP Layer User Grouping and Power Allocation for Uplink Multiantenna NOMA Video Communication Systems

The previous suboptimal user pairing and optimal power control for uplink multiantenna NOMA systems considers the physical-layer-only to maximize the sum data rates. For video communications, the objective is changed to minimize the sum video distortion and then maximize the peak signal-to-noise ratio (PSNR). For uplink multiantenna NOMA systems, we propose 1) a novel weak set user selection scheme to maximize the ratio of signal power and the interference to the strong set users, 2) a novel iterative user substitution scheme based on video distortion in the application layer that increases the PSNR, and the video quality, 3) a novel optimal power allocation derived to minimize the video distortion in the application layer. 1) considers the physical-layer only and 2) and 3) consider the application layer too. The numerical results indicate that the proposed cross-layer scheme outperforms the previous physical-layer-only by 1.1 dB, and is only 0.8 dB away from the exhaustive upper bound in PSNR with 20 users and SNR = 15 dB. The complexity of the proposed scheme is slightly greater than that of the previous physical-layer-only scheme, but still much lower than that of the exhaustive upper bound.

Security and reliability trade‐off analysis of joint user and jammer selection in the face of co‐channel interference

In this study, the authors investigate the security and reliability trade-off (SRT) performance of a multiuser wireless network, where an eavesdropper attempts to overhear the confidential transmissions between a base station and multiple users under the impact of co-channel interference. To enhance the SRT performance of the network, the authors propose two joint user and jammer selection schemes, namely the joint optimal user and random jammer selection (JOU-RJS) scheme and the joint optimal user and optimal jammer selection (JOU-OJS) scheme. For SRT performance comparison purposes, the traditional multiuser scheduling (TMUS) scheme is also considered. The authors derive closed-form outage and intercept probability expressions for the JOU-RJS and JOUOJS schemes. Simulation results show that the SRTs of both JOU-RJS and JOU-OJS schemes are better than that of the TMUS scheme, where JOU-OJS achieves the best SRT performance. Additionally, this study also shows that an expected outage or intercept probability of the TMUS, JOU-RJS, and JOU-OJS schemes can be achieved by giving an appropriate overall rate. Finally, the sum of the outage and intercept probability can be minimised through an optimal power allocation between the selected user and friendly jammer for the proposed JOU-RJS and JOU-OJS.

Performance Analysis for Multi-Hop Cognitive Radio Networks Over Cascaded Rayleigh Fading Channels With Imperfect Channel State Information

In this letter, we consider a cognitive radio network with imperfect channel state information where secondary users transmit signals using multi-hop relaying. When the channels between secondary users are modeled as cascaded Rayleigh fading, we derive the exact outage probability of the secondary network in an analytic form and the approximate outage probability in a closed form. Then we propose a secondary user selection scheme to minimize the outage probability. The validity of our analysis is verified through simulation.

Using Greedy Random Adaptive Procedure to Solve the User Selection Problem in Mobile Crowdsourcing

With the rapid development of mobile networks and smart terminals, mobile crowdsourcing has aroused the interest of relevant scholars and industries. In this paper, we propose a new solution to the problem of user selection in mobile crowdsourcing system. The existing user selection schemes mainly include: (1) find a subset of users to maximize crowdsourcing quality under a given budget constraint; (2) find a subset of users to minimize cost while meeting minimum crowdsourcing quality requirement. However, these solutions have deficiencies in selecting users to maximize the quality of service of the task and minimize costs. Inspired by the marginalism principle in economics, we wish to select a new user only when the marginal gain of the newly joined user is higher than the cost of payment and the marginal cost associated with integration. We modeled the scheme as a marginalism problem of mobile crowdsourcing user selection (MCUS-marginalism). We rigorously prove the MCUS-marginalism problem to be NP-hard, and propose a greedy random adaptive procedure with annealing randomness (GRASP-AR) to achieve maximize the gain and minimize the cost of the task. The effectiveness and efficiency of our proposed approaches are clearly verified by a large scale of experimental evaluations on both real-world and synthetic data sets.

Clustered Millimeter-Wave Networks With Non-Orthogonal Multiple Access

We introduce clustered millimeter wave networks with invoking non-orthogonal multiple access~(NOMA) techniques, where the NOMA users are modeled as Poisson cluster processes and each cluster contains a base station (BS) located at the center. To provide realistic directional beamforming, an actual antenna array pattern is deployed at all BSs. We propose three distance-dependent user selection strategies to appraise the path loss impact on the performance of our considered networks. With the aid of such strategies, we derive tractable analytical expressions for the coverage probability and system throughput. Specifically, closed-form expressions are deduced under a sparse network assumption to improve the calculation efficiency. It theoretically demonstrates that the large antenna scale benefits the near user, while such influence for the far user is fluctuant due to the randomness of the beamforming. Moreover, the numerical results illustrate that: 1) the proposed system outperforms traditional orthogonal multiple access techniques and the commonly considered NOMA-mmWave scenarios with the random beamforming; 2) the coverage probability has a negative correlation with the variance of intra-cluster receivers; 3) 73 GHz is the best carrier frequency for near user and 28 GHz is the best choice for far user; 4) an optimal number of the antenna elements exists for maximizing the system throughput.

Secrecy Outage Performance Analysis of DF Cognitive Relay Network With Co-channel Interference

In this paper, we investigate the secrecy outage performance of the decode-and-forward cognitive relay network with the existence of the co-channel interference, where all nodes are equipped with single antenna and all channels experience Rayleigh fading channels, which are also independent non-identical distribution (i.n.i.d). We also consider the multiple user selection scheme and the single eavesdropper, which could wiretap the information at each hop. There is no evidence of the direct links from the source to the destinations because of the bad conditions. To evaluate the system secrecy performance, we derive the closed form expressions of the secrecy outage probabilities, and the Monte Carlo simulations are also presented to validate the accuracy of the theoretical analysis.

User selection utilizing data properties in mobile crowdsensing

The information sensed by a mobile device is just data, while the aggregation of information sensed by thousands of devices is knowledge. This is the basic idea of Mobile CowdSensing (MCS). In MCS, the user selection problem has always been a key issue, where the task publisher attempts to recruit a suitable set of users to cooperatively sense the events or data at some particular time points and places. Hence, the temporal and spatial constraint becomes the main criterion to select the users. However, whether a user prefers to accomplish the sensing data not only depends on the temporal and spatial relationship, but also lies on the data property. In other words, a user is likely to take the sensing task if it is interested in the data to be sensed. In this paper, we propose a user Selection utilizing data properties in mobile crowdsensing (SPM), where a triple-layer structure considering not only the temporal and spatial probability, but also the data’s property is formulated, and task finishing probabilities are calculated in both the intentional and unintentional situations. Then, a greedy algorithm is proposed to select a suitable set of users for finishing the sensing tasks. We conduct extensive simulations based on three widely-used real-world traces: geolife, roma/taxi, epfl and a synthetic data set. The results show that, compared with other user selection strategies, SPM finishes the largest number of sensing tasks.

Low-Complexity Joint Antenna and User Selection Scheme for the Downlink Multiuser Massive MIMO System with Complexity Reduction Factors

Low-Complexity Joint Antenna and User Selection Scheme for the Downlink Multiuser Massive MIMO System with Complexity Reduction Factors

Joint user and relay selection for relay-aided RF/FSO systems over Exponentiated Weibull fading channels

In this paper, we investigate the performance of joint user and relay selection scheme for a multi-user relayed network over mixed radio-frequency (RF) and free space optical (FSO) system. In this set-up, the non line-of-sight (NLOS) RF link is modeled with Rayleigh fading whereas the LOS FSO path is modeled with Exponentiated Weibull (EW) distribution. We assume that the multiple users at source terminal communicate with the destination over multiple decode and forward relays which are located at the rooftops of the buildings to provide a perfect LOS path. In the proposed scheme, all users send pilot signals to the destination through relay terminals and the latter jointly selects the best user and relay based on the maximization of the end-to-end signal-to-noise ratio (SNR). To quantify the performance of the proposed scheme, closed form outage and error probability are derived. Moreover, asymptotic analysis is performed to obtain important system parameters including fading severity, number of users and relays in the system. Finally, Monte-Carlo (MC) simulations are carried out the verify the performance of the considered scheme.

User and Relay Selection With Artificial Noise to Enhance Physical Layer Security

In this paper, we first propose a joint user and relay selection (JURS) scheme to enhance physical layer security in a multi-user multi-relay network, where the best pair of the user and relay that maximizes the user-to-destination signal-to-interference-to-noise ratio (SINR) is jointly selected. We analytically examine the secrecy outage probability (SOP) of this scheme, based on which the optimal power allocation between the useful signal and artificial noise at the users is determined in order to minimize the corresponding SOP. To avoid the high complexity of the joint selection, we also propose a separate user and relay selection (SURS) scheme, where one relay is firstly selected to maximize the relay-to-destination SINR and a user is then selected to maximize the SINR from the user to the selected relay. We also derive the SOP of the SURS scheme and determine the corresponding optimal power allocation. As expected, the JURS scheme can outperform the SURS scheme. However, our examination also indicates that the low-complex SURS scheme can achieve similar secrecy performance as the high-complex JURS scheme under some specific conditions, e.g., when the number of users is much larger than that of the relays or when the average signal-to-noise ratio of user-to-relay channel is much higher than that of the relay-to-destination channel.

Safeguarding multiuser communication using full‐duplex jamming and Q‐learning algorithm

In this study, the authors consider secure communications in multiuser wireless networks where full-duplex (FD) jamming operates to enhance physical layer security. The considered multiuser system is equipped with FD legitimate receivers in contrast to conventional frameworks where a half-duplex (HD) receiver is at hand. This study investigates an alternative solution in which the authors take advantage of FD capability of the receivers to send jamming signals against the eavesdropper. Under these assumptions, the impact of self-interference and channel interference on physical layer security is investigated. They derive the expressions of secrecy outage probability and ergodic secrecy rate in the proposed system. Two FD jammer selection schemes are proposed to further improve the security. In addition, they apply a reinforcement learning technology, called Q-learning, to model the interaction between the source and multiple jamming users. The preliminary results show that the application of FD jamming and user selection scheme leads to a significant improvement in the wireless network security.