User Scheduling Algorithm Research Articles

Low-Complexity Power Allocation in NOMA Systems With Imperfect SIC for Maximizing Weighted Sum-Rate

In this paper, we investigate the power allocation for maximizing weighted sum rate (WSR) in downlink multiple carriers non-orthogonal multiple access (MC-NOMA) systems with imperfect successive interference cancellation (SIC). We formulate the power allocation problem as a non-convex optimization problem with the total power constraint of all sub-channels while considering often-neglected issues of SIC error and power order constraints at users. First, we discuss that the optimization problem assuming receivers can perform perfect SIC, and we provide a concavity condition of the WSR maximization problem for the MC-NOMA system. When the concavity condition is not satisfied, a fractional quadratic transformation is used to overcome the difficulty of problem non-convexity. Based on the transformation, we propose an iterative power allocation algorithm. Then, we consider the SIC error and the power order constraints in the optimization problem and present a power allocation method with imperfect SIC. Moreover, for both the perfect and imperfect SIC, we derive some propositions of the optimal power allocation solution to the WSR maximization problem and propose a low-complexity power allocation algorithm based on these propositions. Finally, we provide a joint user scheduling and power allocation algorithm for maximizing the WSR. The simulation results illustrate that the proposed resource allocation methods have a better performance than the existing schemes.

Joint Scheduling and Deep Learning-Based Beamforming for FD-MIMO Systems Over Correlated Rician Fading

In this paper, we investigate the downlink transmission for full-dimension multiple-input multiple-output (FD-MIMO) systems over correlated Rician fading channels. With only statistical channel state information at the BS, the beamforming vectors of each user are decoupled from each other through the maximization of average signal-to-leakage-plus-noise ratio (SLNR) lower bound, and the optimal beamforming vector which involves the line-of-sight component and correlation matrix of both directions is derived. To reduce the time of acquiring the beamforming vector for each user, a deep learning (DL)-based algorithm is proposed. A sub-optimal analytical beamforming algorithm is also proposed for comparison. Based on the proposed beamforming method, the ergodic rate of each user is analyzed and simple closed-form approximations are derived, which are very useful in evaluating the system performance and user scheduling. Moreover, two user scheduling algorithms referred to as most dissimilar and minimum interference-to-signal factor algorithm are proposed, which greatly reduce the complexity compared to the sum rate based greedy scheduling algorithm. Simulation results validate the performance of the proposed beamforming and scheduling algorithms, and verify the accuracy of the derived ergodic rate approximations.

Distributed Transmission Scheduling and Power Allocation in CoMP

The performance of wireless networks can be largely enhanced by coordinated multipoint (CoMP). To design an efficient CoMP in multiuser multiple-input multiple-output scenario, conventional transmission scheduling and power allocation are usually performed in a static and centralized manner. In this paper, we focus on dynamic and distributed transmission scheduling and power allocation. We first determine the coordinated base-station sets (defined as CBSs) candidates in each subband by the channel energy ( i.e., square Frobenius norm of channel matrix) of each user. Each CBS candidate contains a set of coordination base-stations and edge users. By chordal distance, we can measure the orthogonality between space spanned of users in the same CBS candidate. Then, we propose two heuristic user scheduling algorithms based on channel energy and chordal distance between users to determine the set of users served by each CBS candidate. The first algorithm is based on an open problem, which reveals the philosophy of user scheduling with orthogonalization threshold guarantee. The second one deals with user scheduling by selecting a set of edge users with the largest total channel energy and orthogonalization threshold guarantee. With the total channel energy per CBS candidate, the CBSs and their served edge users can be determined. Then, water-filling power allocation is further applied to CBSs with block diagonalization precoding. Algorithm performance is demonstrated by extensive simulations.

Multiuser 3D massive MIMO transmission in full-duplex cellular system

In this paper, we provide an effective multiuser transmission scheme in three-dimensional (3D) massive multiple-input multiple-output (MIMO) cellular systems, where the full-duplex (FD) base station (BS) equips two separate large-scale uniform planar antenna array (UPA). In order to reduce the computational and implementation complexity, we investigate the characteristic of the beam-domain (BD) 3D massive MIMO channels and self-interference (SI) channel. We propose the 3D multiuser beamspace transmission (MUBT) scheme that requires the spatial angular information of the users and the SI channel. We show that, due to the reduced dimension property of the effective beamspace channel, the overhead for channel estimation is reduced. Furthermore, a user scheduling algorithm is proposed to enable the 3D MUBT scheme in the FD systems. Finally, both the theoretical analysis and simulation results show the the SI can be effectively reduced and demonstrate the effectiveness and superiority of the proposed 3D MUBT scheme on spectral efficiency compared with the conventional half-duplex (HD) and FD transmission schemes.

Robust user scheduling with COST 2100 channel model for massive MIMO networks

The problem of user scheduling with reduced overhead of channel estimation in the uplink of massive multiple-input multiple-output (MIMO) systems has been investigated. The authors consider the COST 2100 channel model. In this paper, they first propose a new user selection algorithm based on knowledge of the geometry of the service area and location of clusters, without having full channel state information at the BS. They then show that the correlation in geometry-based stochastic channel models (GSCMs) arises from the common clusters in the area. In addition, exploiting the closed-form Cramer–Rao lower bounds, the analysis for the robustness of the proposed scheme to cluster position errors is presented. It is shown by analysing the capacity upper bound that the capacity strongly depends on the position of clusters in the GSCMs and users in the system. Simulation results show that though the BS receiver does not require the channel information of all users, by the proposed geometry-based user scheduling algorithm the sum rate of the system is only slightly less than the well known greedy weight clique scheme.

User scheduling for downlink FD-MIMO systems under Rician fading exploiting statistical CSI

In this paper, we consider the user scheduling algorithm for downlink full-dimension multiple-input multiple-output (FD-MIMO) system under Rician fading channels. We assume that two-dimensional (2D) large-scale antenna array is deployed at base station (BS). An approximation of users signal-to-interference-plus-noise ratio (SINR) and a lower bound of users average signal-to-leakage-plus-noise ratio (SLNR) are derived. Based on these, two user scheduling algorithms exploiting only statistical channel state information (CSI) are proposed. The proposed algorithms take both the achievable sum rate and fairness into account. Simulation results reveal that the proposed user scheduling algorithms can make good trade-off between the achievable rate and fairness.

Channel transmission strategy for mmWave hybrid UAV communications with blockage

The blockage is a tough hurdle for millimetre-wave (mmWave) unmanned aerial vehicle (UAV) communications. In this Letter, the authors propose an angle domain channel transmission scheme for mmWave hybrid UAV communication with blockage. Firstly, they investigate the angle domain channel transmission of mmWave UAV communication systems with massive array antennas. Then, they solve the blockage problem through the multi-UAV coordination. Specially, they provide a practical user scheduling algorithm to maximize the achievable sum rates. Finally, simulation results are provided to show the effectiveness of the proposed method.

Joint User Scheduling and Power Allocation Optimization for Energy-Efficient NOMA Systems With Imperfect CSI

Non-orthogonal multiple access (NOMA) exploits successive interference cancellation technique at the receivers to improve the spectral efficiency. By using this technique, multiple users can be multiplexed on the same subchannel to achieve high sum rate. Most previous research works on NOMA systems assume perfect channel state information (CSI). However, in this paper, we investigate energy efficiency improvement for a downlink NOMA single-cell network by considering imperfect CSI. The energy efficient resource scheduling problem is formulated as a non-convex optimization problem with the constraints of outage probability limit, the maximum power of the system, the minimum user data rate, and the maximum number of multiplexed users sharing the same subchannel. Different from previous works, the maximum number of multiplexed users can be greater than two, and the imperfect CSI is first studied for resource allocation in NOMA. To efficiently solve this problem, the probabilistic mixed problem is first transformed into a non-probabilistic problem. An iterative algorithm for user scheduling and power allocation is proposed to maximize the system energy efficiency. The optimal user scheduling based on exhaustive search serves as a system performance benchmark, but it has high computational complexity. To balance the system performance and the computational complexity, a new suboptimal user scheduling scheme is proposed to schedule users on different subchannels. Based on the user scheduling scheme, the optimal power allocation expression is derived by the Lagrange approach. By transforming the fractional-form problem into an equivalent subtractive-form optimization problem, an iterative power allocation algorithm is proposed to maximize the system energy efficiency. Simulation results demonstrate that the proposed user scheduling algorithm closely attains the optimal performance.

An opportunistic scheduling algorithm using aged CSI in massive MIMO systems

In time-division duplex (TDD) massive multiple-input multiple-output (MIMO) systems, the spatial multiplexing gain cannot be fully achieved since available pilot resources at each channel coherence time interval are limited. In this paper, we propose an Opportunistic user Scheduling algorithm, termed OpSAC, that uses Aged Channel state information (CSI) to increase spatial multiplexing gain without incurring additional pilot overhead. Assuming the base station (BS) employs two popular precoders of maximum ratio transmission (MRT) and zero-forcing (ZF), we first derive their closed-form lower bounds on the achievable sum-rate under channel aging. According to the analysis results, we develop a heuristic solution that estimates the amount of channel variation for each user by using correlation of CSI samples, and exploits channel conditions to opportunistically schedule more users by using aged CSI, thereby enhancing spectral efficiency. Through numerical analysis and simulation we confirm that the proposed lower bounds are very tight, and show the impact of channel aging on the performance of massive MIMO systems. In addition, it is shown that OpSAC achieves near-optimal performance and considerably outperforms the conventional user scheduling algorithm that uses current CSI only.

Enhancing Multiuser MIMO Through Opportunistic D2D Cooperation

We propose a cellular architecture that combines multiuser MIMO downlink with opportunistic use of unlicensed Industrial, Scientific, and Medical Radio (ISM) bands to establish device-to-device (D2D) cooperation. The architecture consists of a physical-layer cooperation scheme based on forming downlink virtual MIMO channels through D2D relaying, and a novel resource allocation strategy for such D2D-enabled networks. We prove the approximate optimality of the physical-layer scheme, and demonstrate that such cooperation boosts the effective $ \mathsf {SNR}$ of the weakest user in the system, especially in the many-user regime, due to multiuser diversity. To harness this physical-layer scheme, we formulate the cooperative user scheduling and the relay selection problem using the network utility maximization framework. For such a cooperative network, we propose a novel utility metric that jointly captures fairness in throughput and the cost of relaying in the system. We propose a joint user scheduling and relay selection algorithm, which we prove to be asymptotically optimal. We study the architecture through system-level simulations over a wide range of scenarios. The highlight of these simulations is an approximately $6x$ improvement in data rate for cell-edge (bottom fifth-percentile) users (over the state-of-the-art) while still improving the overall throughput, and considering various system constraints.

Statistical CSIT Aided User Scheduling for Broadcast MU-MISO System

Recent studies show that the statistical channel state information (SCSI) helps to largely increase the capacity of communication systems when the instantaneous perfect CSI is unavailable. In this paper, we consider multiuser multiple-input-single-output broadcast channels where the transmitter has the knowledge of SCSI. The major issue of concern in our paper is to improve the average group-rate of the whole system by scheduling users over different time slots. With SCSI at the transmitter side, we are able to precode signals and, hence, compute the theoretical achievable group-rate of arbitrary user groups. Based on the group-rates, we propose tier-2 Munkres user scheduling algorithm (T2-MUSA) that leads to higher average group-rate than existing algorithms with generally better fairness. The optimality of the proposed algorithm in energy-fair user scheduling space is proved and we derive a lower bound of a special case to verify the validity of our simulations. In addition, many conventional user scheduling algorithms maintain queue stability by solving a weighted sum-rate (WSR) problem, using queue lengths to represent weight coefficients. Inspired by T2-MUSA, we propose a QoS-based MUSA (QB-MUSA) aimed at stabilizing queue lengths and maximizing throughput. In results, we show that QB-MUSA exhibits higher throughput than the conventional WSR-based algorithm.

Multi‐pair massive MIMO relay networks: power scaling laws and user scheduling strategy

This study studies a multi-pair massive multiple-input multiple-output (MIMO) relaying network, where multiple pairs of users are served by a single relay station with a large number of antennas, and the amplify-and-forward protocol and zero-forcing (ZF) beamforming are used at the relay. The authors investigate the ergodic achievable rates for the users and obtain tight approximations in closed form for finite number of antennas. The rate performance and power efficiency are studied based on the analytical results for asymptotic scenarios, and the effect of scaling factors of transmit powers for users and relay are discussed. The closed-form expressions enable us to determine the optimal user scheduling which maximizes the ergodic sum-rate for the selected pairs. A simplified user scheduling algorithm is proposed which greatly reduces the average complexity of the optimal use pair search without any rate loss. Moreover, the complexity reduction for the proposed algorithm increases nonlinearly with the increase of the number of user pairs, which indicates that the simplified scheduling algorithm has notable advantages when the number of users is increased. The tightness for the analytical approximations and the superiority of the proposed algorithm are verified by Monte-Carlo simulation results.

Downlink Performance of Pilot-Reused HetNet With Large-Scale Antenna Arrays

Considering a heterogeneous network where both macro base station (BS) and small cell (SC) nodes are equipped with massive number of antennas, this paper studies the performance for multiple-input multiple-output downlinks when the macro and small cells share the same spectrum, and hence interfere with each other. Suppose that the large-scale antenna arrays at both macro BS and SC nodes employ maximum-ratio transmission (MRT) or zero-forcing transmission (ZFT) precoding, and transmit data streams to served users simultaneously. A new pilot reuse pattern among SCs is proposed for channel estimation. Taking into account imperfect channel state information (CSI), capacity lower bounds for MRT and ZFT are derived, respectively, in closed-form expressions involving only statistical CSI, followed by asymptotic analyses for massive arrays under specific power scaling laws. Subsequently, two user scheduling algorithms, greedy scheduling and asymptotical scheduling algorithm (ASA), are proposed based on derived capacity lower bounds and asymptotic analyses, respectively. ASA is demonstrated to be a near optimal in the asymptotic regime and has low complexity. Finally, the derived closed-form expressions are verified to be accurate predictors of the system performance by Monte Carlo simulations. Numerical results demonstrate the effectiveness of the asymptotic analysis and proposed user scheduling schemes.

Sum-Rate Analysis for Massive MIMO Downlink With Joint Statistical Beamforming and User Scheduling

Statistical beamforming is an important technique for multi-user massive MIMO downlink, since it depends on the downlink channel covariance only. In this paper, we first derive an explicit analytical sum-rate expression for generic channel covariance-based beamforming scheme. Then, a low-complexity joint statistical beamforming and user scheduling algorithm via greedy search is proposed, where the beamforming is based on the signal-to-leakage-and-noise-ratio (SLNR) for closed-form design and tractable analysis, while the user scheduling is based on the derived sum-rate expression. Further, with the help of large-scale asymptotic simplifications and the introduction of the interference user number parameter, a simple analytical sum-rate expression of the joint algorithm is derived for channels with flat power beam spectrum. The expression explicitly exhibits the sum-rate behavior with respect to different network parameters and captures the effect of sum-rate-based user scheduling. Finally, simulation results are provided to verify our analytical results and to show the advantage of the proposed joint design compared with existing schemes.

Cognitive radio network with coordinated multipoint joint transmission

SummaryCognitive radio (CR) is considered to be a promising technology for future wireless networks to make opportunistic utilization of the unused or underused licensed spectrum. Meanwhile, coordinated multipoint joint transmission (CoMP JT) is another promising technique to improve the performance of cellular networks. In this paper, we propose a CR system with CoMP JT technique. We develop an analytical model of the received signal‐to‐noise ratio at a CR to determine the energy detection threshold and the minimum number of required samples for energy detection–based spectrum sensing in a CR network (CRN) with CoMP JT technique. The performance of energy detection–based spectrum sensing under the developed analytical model is evaluated by simulation and found to be reliable. We formulate an optimization problem for a CRN with CoMP JT technique to configure the channel allocation and user scheduling for maximizing the minimum throughput of the users. The problem is found to be a complex mixed integer linear programming. We solve the problem using an optimization tool for several CRN instances by limiting the number of slots in frames. Further, we propose a heuristic‐based simple channel allocation and user scheduling algorithm to maximize the minimum throughput of the users in CRNs with CoMP JT technique. The proposed algorithm is evaluated via simulation and found to be very efficient.

Competition-based distributed BS power activation and user scheduling algorithm

Existing cellular technologies in unlicensed band such as license assisted access (LAA)-LTE do not capture inter-cell interference (ICI) management which becomes more important in modern small cell network environments. Moreover, existing ICI management techniques not only can be operated in only licensed frequency band due to their centralized properties, but also have high computational complexities. In this paper, by invoking distributed optimization, we propose a fully distributed base station (BS) activation and user scheduling framework which can be operated in even unlicensed band because of its competition properties. Our simulation results demonstrate that (i) proposed competitionbased BS activation and user scheduling framework (CBA) increases throughput of cell edge users by 112%–335% compared to conventional algorithms, (ii) the CBA properly catches up with the performance of optimal algorithm up to 93% in terms of overall performance and up to 95% in terms of edge user throughput, and (iii) the CBA also provides higher performance gains in the larger ratio of edge users and the smaller cell size, which indicates that the CBA well adapts to cellular network trend where cells are gradually smaller and densely deployed.

Social fairness and channel loading effects in peer-to-peer connected networks

Spectral efficiency is significantly compromised when different users download same content over a wireless link. Especially in a peer-to-peer (PTP) network, this may also lead to congestion and unfair usage of the links by users with superior link conditions. In this paper, in order to address the above mentioned problems a socially fair user scheduling algorithm (SFUSA) for a PTP is proposed. The proposed algorithm selects a leader from the PTP who will download data and share it within the PTP using a short range ad-hoc wireless network. In order to select the leader SFUSA takes into consideration the traffic conditions in the link of individual users from the data access point along with social fairness factor of the users. It is shown through simulations that the proposed algorithm solves the problem of congestion at the data access point, along with increased retention of peers in a PTP with enhanced user satisfaction.

User Grouping and Scheduling for Joint Spatial Division and Multiplexing in FDD Massive MIMO System

Massive multiple-input multiple-output (MIMO) is a key technology for the 5th Generation wireless communication systems. Joint spatial division and multiplexing (JSDM) method can reduce the cost of downlink training and feedback for CSIT of frequency-division duplexing (FDD) system. In this paper, we studied user grouping and user scheduling problems based on JSDM, and proposed an improved greedy user scheduling algorithm with lower complexity. Numerical results show that the user grouping and scheduling based on the proposed improved algorithm have much lower computational complexity while resulting in only a slight loss in system performance.

Energy-Efficient Resource Allocation and User Scheduling for Collaborative Mobile Clouds With Hybrid Receivers

In this paper, we study the resource allocation and user scheduling algorithm for minimizing the energy cost of data transmission in the context of OFDMA collaborative mobile cloud (CMC) with simultaneous wireless information and power transfer (SWIPT) receivers. The CMC, which consists of several collaborating MTs offers one potential solution for downlink content distribution and for the energy consumption reduction at the terminal side. Meanwhile, as RF signal can carry both information and energy simultaneously, the induced SWIPT has gained much attention for energy efficiency design of mobile nodes. Previous work on the design of CMC system mainly focused on the cloud formulation or energy efficiency investigation, while how to allocate the radio resource and schedule user transmission lacks attention. With the objective to minimize the system energy consumption, an optimization problem which jointly considers subchannel assignment, power allocation and user scheduling for a group of SWIPT receivers has been presented. The formulated problem is addressed through the convex optimization technique. Simulation results demonstrate that the proposed user scheduling and resource allocation algorithms can achieve significant energy saving performance.

Highly Efficient 3-D Resource Allocation Techniques in 5G for NOMA-Enabled Massive MIMO and Relaying Systems

Non-orthogonal multiple access (NOMA) has been considered as a highly efficient communication technology in the fifth generation (5G) networks by serving multiple users concurrently through non-orthogonal sharing communication resources. NOMA can be combined with both massive multiple input multiple output (MIMO) and relaying technologies to further improve 5G system efficiency at the cost of increased complexity. These combinations rely on the efficient utilization of 3-D communication resources. In the first part of this paper, we investigate highly efficient 3-D resource allocation for massive MIMO-NOMA systems. Due to hardware complexity constraints and channel variation in the massive MIMO-NOMA system, efficient antenna selection and user scheduling algorithms are proposed for sum rate maximization. In the second part of this paper, a collaborative NOMA-assisted relaying (CNAR) system is proposed to serve multiple cell-edge users by 3-D resource utilization. To reduce the relaying complexity in CNAR system, a simplified-CNAR (S-CNAR) system is proposed as an alternative NOMA-enabled relaying strategy. Numerical results show that our antenna selection and user scheduling algorithms achieve similar performance to existing methods with reduced complexity. Under high target rate, CNAR obtains better performance over other transmission strategies and S-CNAR reaches similar performance by simplified relaying scheme.