scholarly journals Low-Complexity User Scheduling with Switched Tilting for 3D Cellular Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Haijing Liu ◽  
Hui Gao ◽  
Tiejun Lv
Keyword(s):  
Large Scale ◽  
Matrix Theory ◽  
Low Complexity ◽  
Base Station ◽  
Optimal Number ◽  
Cellular Systems ◽  
Rate Performance ◽  
User Scheduling ◽  
Sum Rate ◽  
Computational Resources

We propose a low-complexity user scheduling scheme to enhance the sum rate performance for a multicell downlink system, in which the base station (BS) is equipped with a large-scale active antenna array. First, we divide each cell intoNregions according to the vertical beamwidth of the BS antennas. Next, candidate user equipment (UE) items are assigned to corresponding groups to their locations. Each scheduling slot is also divided intoNequal-time subslots. Then, at each subslot, we focus on one UE group, select the optimal number,K*, of UEs for simultaneous data transmission in the manner of round-robin scheduling, and adjust the BS antenna tilting to the optimal angleθtilt*. In particular,K*andθtilt*for each UE group are both obtained by means of large-system asymptotic analysis. Benefiting from the random matrix theory tools, the asymptotic analytical results are independent of instantaneous channel state information of UE, which make it possible to solveK*andθtilt*offline, therefore saving the online computational resources significantly. Numerical results verify that the proposed scheme achieves good sum rate performance with extremely low computational complexity.

Performance Analysis of Low Complexity Multiuser Scheduling Algorithms in MIMO System

2013 ◽  
Vol 392 ◽  
pp. 867-871
Author(s):  
Ming Xia Lv ◽  
Yan Kun Lai ◽  
Dong Tang
Keyword(s):  
Mimo System ◽  
Scheduling Algorithm ◽  
Low Complexity ◽  
Base Station ◽  
User Scheduling ◽  
Sum Capacity ◽  
Multiuser Scheduling ◽  
The Common ◽  
The Cost ◽  
Selection Algorithms

The total throughput of the communication system can be maximized by allocating the common radio resource to the user or the user group having the best channel quality at a given time and the multiuser diversity gain can be obtained when multiple users share the same channel at one time. The object to select the users is to select the users with the maximum sum capacity. As for a scheduling algorithm, exhaustive algorithm can get the largest capability of the system by multi-user scheduling. However, this algorithm is quite complex hence the cost of operation to a base station has substantial increased. We compare the multiuser performance of two fast user selection algorithms with low complexity in MIMO-MRC systems with co-channel interferences. From the simulation results, these two algorithms not only decrease the computational complexity of the scheduling algorithm but also retain large capability of the MIMO system.

scholarly journals Performance Comparison of Practical Resource Allocation Schemes for Device-to-Device Communications

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Gábor Fodor
Keyword(s):  
Resource Allocation ◽  
Power Control ◽  
Large Scale ◽  
Low Complexity ◽  
Base Station ◽  
Performance Comparison ◽  
Superior Performance ◽  
Channel Gain ◽  
D2d Communications ◽  
Device To Device

Device-to-device (D2D) communications in cellular spectrum have the potential of increasing the spectral and energy efficiency by taking advantage of the proximity and reuse gains. Although several resource allocation (RA) and power control (PC) schemes have been proposed in the literature, a comparison of the performance of such algorithms as a function of the available channel state information has not been reported. In this paper, we examine which large scale channel gain knowledge is needed by practically viable RA and PC schemes for network assisted D2D communications. To this end, we propose a novel near-optimal and low-complexity RA scheme that can be advantageously used in tandem with the optimal binary power control scheme and compare its performance with three heuristics-based RA schemes that are combined either with the well-known 3GPP Long-Term Evolution open-loop path loss compensating PC or with an iterative utility optimal PC scheme. When channel gain knowledge about the useful as well as interfering (cross) channels is available at the cellular base station, the near-optimal RA scheme, termed Matching, combined with the binary PC scheme is superior. Ultimately, we find that the proposed low-complexity RA + PC tandem that uses some cross-channel gain knowledge provides superior performance.

scholarly journals Backhaul-Aware Resource Allocation and Optimum Placement for UAV-Assisted Wireless Communication Network

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1397
Author(s):  
Yishi Xue ◽  
Bo Xu ◽  
Wenchao Xia ◽  
Jun Zhang ◽  
Hongbo Zhu
Keyword(s):  
Communication Network ◽  
Resource Allocation ◽  
Wireless Communication ◽  
Large Scale ◽  
Optimization Problem ◽  
Matrix Theory ◽  
Base Station ◽  
Achievable Rate ◽  
Multiple User ◽  
Wireless Communication Network

Driven by its agile maneuverability and deployment, the unmanned aerial vehicle (UAV) becomes a potential enabler of the terrestrial networks. In this paper, we consider downlink communications in a UAV-assisted wireless communication network, where a multi-antenna UAV assists the ground base station (GBS) to forward signals to multiple user equipments (UEs). The UAV is associated with the GBS through in-band wireless backhaul, which shares the spectrum resource with the access links between UEs and the UAV. The optimization problem is formulated to maximize the downlink ergodic sum-rate by jointly optimizing UAV placement, spectrum resource allocation and transmit power matrix of the UAV. The deterministic equivalents of UE’s achievable rate and backhaul capacity are first derived by utilizing large-dimensional random matrix theory, in which, only the slowly varying large-scale channel state information is required. An approximation problem of the joint optimization problem is then introduced based on the deterministic equivalents. Finally, an algorithm is proposed to obtain the optimal solution of the approximate problem. Simulation results are provided to validate the accuracy of the deterministic equivalents, and the effectiveness of the proposed method.

scholarly journals ISSOR Signal Detection for Energy Efficient and Low Complexity Large Scale MIMO System

2019 ◽  
Vol 9 (1S5) ◽  
pp. 327-334
Keyword(s):  
Signal Detection ◽  
Energy Efficient ◽  
Communication Systems ◽  
Large Scale ◽  
Mimo System ◽  
Low Complexity ◽  
High Energy ◽  
Base Station ◽  
User Equipment ◽  
Multiple User

Scalable version of multiuser MIMO called Large-scale MIMO is a one of the powerful technology in future wireless communication systems in which huge amount of BS (base station) antennas utilized to process multiple user equipment. Energy consumed is high with more antennas and also it leads to increase the signal detection complexity and overall circuit power consumption. Designing energy efficient and low complexity MIMO system is considered as a challenging issue. This paper presents the ISSOR signal detection for energy efficient and low complexity large scale MIMO system. VA-GSM (Variable Antenna Generalized spatial modulation) is used in which the number of active antenna transmissions are varied for every transmission in the large scale MIMO. In transmitter side, Eigen value based approach is used for antenna selection. Then, improved symmetric successive over relaxation (ISSOR) approach is proposed for low complexity signal detection in receiver side. The number of user equipment, transmit power, as well as the amount of antennas at the base station, are considered as the optimal system parameters which are chosen for enhancing the efficiency of utilized energy in the system. The proposed scheme implemented in MATLAB software. The proposed scheme attained the high energy efficiency compared to other approaches. Moreover, the BER is utilized to estimate the performance of an offered algorithm and also compared to the previously determined algorithm of existing literatures.

scholarly journals Sum Rate of Multiuser Large-Scale MIMO in the Presence of Antenna Correlation and Mutual Coupling

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Yusheng Li ◽  
Kang An ◽  
Tao Liang ◽  
Weixin Lu
Keyword(s):  
System Performance ◽  
Mutual Coupling ◽  
Large Scale ◽  
Mimo System ◽  
Base Station ◽  
Closed Form Expression ◽  
Channel State ◽  
Antenna Correlation ◽  
Sum Rate ◽  
The Impact

A multiuser large-scale MIMO system with antenna correlation and mutual coupling is investigated in this paper. Based on the maximum signal-to-interference-plus-noise ratio (SINR) criteria, the optimal beamforming (BF) vector at the base station (BS) for each user is first obtained using statistical channel state information (CSI). Then, a closed-form expression for the achievable sum rate is derived in terms of a finite number of generalized Meijer-G functions, which is applicable to an arbitrary number of array elements and/or users, and provides an efficient means of evaluating the system performance. Finally, numerical results are provided to confirm the validity of the theoretical analysis and show the impact of various channel parameters on the system performance.

scholarly journals Sum Rate Analysis of MU-MIMO with a 3D MIMO Base Station Exploiting Elevation Features

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Xingwang Li ◽  
Lihua Li ◽  
Fupeng Wen ◽  
Junfeng Wang ◽  
Chao Deng
Keyword(s):  
Channel Model ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Base Station ◽  
Rate Performance ◽  
High Rise ◽  
Rate Analysis ◽  
Input Multiple Output ◽  
Sum Rate

Although the three-dimensional (3D) channel model considering the elevation factor has been used to analyze the performance of multiuser multiple-input multiple-output (MU-MIMO) systems, less attention is paid to the effect of the elevation variation. In this paper, we elaborate the sum rate of MU-MIMO systems with a 3D base station (BS) exploiting different elevations. To illustrate clearly, we consider a high-rise building scenario. Due to the floor height, each floor corresponds to an elevation. Therefore, we can analyze the sum rate performance for each floor and discuss its effect on the performance of the whole building. This work can be seen as the first attempt to analyze the sum rate performance for high-rise buildings in modern city and used as a reference for infrastructure.

scholarly journals Sum Rate Analysis for Massive MIMO Downlink With MRC Beamforming and User Selection

2021 ◽  
Vol 2113 (1) ◽  
pp. 012025
Author(s):  
Yiyang Wu ◽  
Chang Chang ◽  
Fei Xie ◽  
Dacheng Ju ◽  
Yilun Pan
Keyword(s):  
Channel Model ◽  
Base Station ◽  
Transmission Model ◽  
User Selection ◽  
Selection Algorithm ◽  
User Scheduling ◽  
Downlink System ◽  
Sum Rate ◽  
Simulation Results ◽  
Mimo Downlink

Abstract Average allocation of data rate to each user is inefficient since the resource a base station can allocate is limited. Thus, user selection and user scheduling need to be applied into multi-user massive multiple-input multiple-output (MIMO) downlink system. In this paper, we mainly focus on the methods of user selection. First, we establish a downlink system model including transmission model and channel model. Then, two user-rate based user selection algorithms via the signal-to-interference-plus-noise-ratio (SINR) are proposed, where the SINR is generated by MRC beamforming. Finally, simulation results are provided to compare the performance of two proposed algorithms and their fairness towards selected users. In the simulation results, location-based selection algorithm and random selection algorithm are jointly compared. The second proposed algorithm possesses the highest total sum-rate and is the optimal algorithms among the four algorithms.

Capacity Limits of Base Station Cooperation in Cellular Networks

2010 ◽  
pp. 102-132
Author(s):  
Symeon Chatzinotas ◽  
Muhammad Ali Imran ◽  
Reza Hoshyar
Keyword(s):  
Channel Model ◽  
High Capacity ◽  
Path Loss ◽  
Base Station ◽  
Cellular Systems ◽  
Current Channel ◽  
Capacity Limits ◽  
Base Station Cooperation ◽  
Rate Capacity ◽  
Sum Rate

In the information-theoretic literature, it has been widely shown that multicell processing is able to provide high capacity gains in the context of cellular systems. What is more, it has been proved that the per-cell sum-rate capacity of multicell processing systems grows linearly with the number of base station (BS) receive antennas. However, the majority of results in this area have been produced assuming that the fading coefficients of the MIMO subchannels are completely uncorrelated. In this direction, this chapter investigates the ergodic per-cell sum-rate capacity of the Gaussian MIMO cellular channel under correlated fading and BS cooperation (multicell processing). More specifically, the current channel model considers Rayleigh fading, uniformly distributed user terminals (UTs) over a planar cellular system, and power-law path loss. Furthermore, both BSs and UTs are equipped with correlated multiple antennas, which are modelled according to the Kronecker product correlation model. The per-cell sum-rate capacity is evaluated while varying the cell density of the system, as well as the level of receive and transmit correlation. In this context, it is shown that the capacity performance is compromised by correlation at the BS-side, whereas correlation at the UT-side has a negligible effect on the system’s capacity.

Low‐complexity user scheduling for MMSE relaying with large‐scale arrays

2015 ◽  
Vol 51 (2) ◽  
pp. 147-149
Author(s):  
Haijing Liu ◽  
Hui Gao ◽  
Tiejun Lv
Keyword(s):  
Large Scale ◽  
Low Complexity ◽  
User Scheduling

A Fast Scheduling Algorithm for Multiple User MIMO-MRC System

2013 ◽  
Vol 385-386 ◽  
pp. 1738-1742
Author(s):  
Dong Tang ◽  
Ming Xia Lv
Keyword(s):  
Computational Complexity ◽  
Mimo System ◽  
Scheduling Algorithm ◽  
Low Complexity ◽  
Base Station ◽  
User Group ◽  
User Scheduling ◽  
Channel Quality ◽  
Multiple User ◽  
The Cost

When multiple users share the same channel at one time, the total throughput of the communication system can be maximized by allocating the common radio resource to the user or the user group having the best channel quality at a given time and the multiuser diversity gain can be obtained. The object to select the users in the best group is to select the users with the maximum sum capacity. Because of the co-channel interferences among the users, user in the best group is often not the user with the best channel quality when only does it transmit to the base station. As for a scheduling algorithm, exhaustive algorithm is to search the whole possibilities of the user group and is an approach that can get the largest capability of the system by multi-user scheduling. However, this algorithm is quite complex and usually brings huge workload to a base station with multiple antennas, hence the cost of operation to a base station has substantially increased. We propose a fast user selection algorithm with low complexity to reduce the computational complexity of the scheduling algorithm. From the simulation results, this algorithm not only decreases the computational complexity of the scheduling algorithm but also retains large capability of the MIMO system.

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