Active User Equipment Research Articles

Multi-User Massive MIMO Visible Light Communications With Limited Pilot Transmission

Visible light communication (VLC) building on the existing illumination infrastructure utilizes light emitting diode (LED) luminaries as wireless transmitters. To achieve data rates on the order of gigabits per second in VLC systems, multiple-input multiple-output (MIMO) transmission has been identified as a key technology. In this paper, we consider a centralized network architecture where the ceiling LED luminaries act as transmitter elements of a distributed massive MIMO VLC system. To obtain the full benefits of massive MIMO, channel state information must be available at the transmitter side. Downlink (DL) channel estimation in a massive MIMO system requires huge pilot overhead in DL as well as feedback overhead in uplink. This makes the implementation of massive MIMO system infeasible if not properly designed. In our study, we address the design of massive MIMO VLC systems with a limited number of DL pilot signals. We explore different DL pilot patterns (PPs) in frequency, time, and spatial domains where interpolation is performed to obtain the global channel matrix taking advantage of the indoor environment geometry and layout of luminaries. We then present data rate results for different DL PPs under the consideration of varying number of active user equipments through Monte-Carlo simulations.

A GCICA Grant-Free Random Access Scheme for M2M Communications in Crowded Massive MIMO Systems

A novel grant-free random access scheme with a high success rate is proposed to support massive access for machine-to-machine communications in massive multiple-input–multiple-output (MIMO) systems. This scheme allows active user equipments (UEs) to transmit their modulated uplink messages and super pilots consisting of multiple subpilots to a base station (BS). Then, the BS performs channel state information (CSI) estimation and uplink message decoding by utilizing a proposed graph combined clustering independent component analysis (GCICA) decoding algorithm and then employs the estimated CSIs to detect active UEs by using the characteristic of asymptotic favorable propagation of massive MIMO channel. We call this proposed scheme as the GCICA-based random access (GCICA-RA) scheme. We analyze the successful access probability, missed detection probability, and uplink throughput of the GCICA-RA scheme. Numerical results show that the GCICA-RA scheme significantly improves the successful access probability and uplink throughput, decreases missed detection probability, and provides low CSI estimation error at the same time.

Seamless connectivity with 5G enabled unmanned aerial vehicles base stations using machine programming approach

AbstractDeployment of a small unmanned aerial vehicle (UAV) mounted 5G base station is a promising solution for providing seamless network connectivity to users in a modern, data‐centric thrust areas. The key challenge is to find the location, the height and the optimum number of mounts. A machine programming based approach is proposed here for optimal placement of UAV‐mounted base station. The location of the deployment is determined using three clustering algorithms such as K‐means, K‐medoids, and fuzzy cluster means. Different sets of UAV‐mounted base stations have been deployed with variable user density at different heights. The impact on the network performance has been quantified through measurements of received power, signal to interference plus noise ratio (SINR), and path loss per active user equipment (UEs). To gain further insights, a scenario where UEs are connected only to the terrestrial base station, that is, the network is devoid of any sort of UAV mounted base station is evaluated. Numerical computations reaffirm that the proposed technique reduces the average path loss of the active UEs. Moreover, the use of height‐mounted base station also alleviates the issues arising due to low SINR values. The said technique shows immense potential in terms of seamless connectivity to end users in events of emergency and remote deployment scenarios, where ground‐based base station is not possible. The big transition of on‐ demand connectivity for 5G networks shall be benefitted from purpose‐built UAV infrastructure with specific locations or areas in mind.

Joint Detection and Decoding of Polar Coded 5G Control Channels

The recent release of the cellular standard known as 5G New Radio (5G-NR) has adopted polar codes for error protection in the physical downlink control channel (PDCCH). We develop a novel joint detection and decoding algorithm for 5G multiple-input multiple-output (MIMO) transceivers to achieve robustness against practical obstacles including channel state information (CSI) errors, noise, interferences, and pilot contamination. To optimize the performance of PDCCH detection, we incorporate the polar code information during signal detection by transforming the Galois field code constraints into the complex signal field. Specifically, our novel joint linear programming (LP) formulation takes into consideration the transformed polar code constraints. Our proposed detector can also be integrated with effective successive cancellation list (SCL) decoders to deliver superior receiver performance and improve the computational efficiency compared to turbo approach joint detection decoding design. Moreover, similar to 4G-LTE, each active user equipment (UE) must blindly detect its own PDCCH in the downlink search space. We further introduce a metric readily available at the detector that can be used to eliminate most of wrong PDCCH candidates before sending them to the decoder and therefore, improve the computational efficiency of PDCCH blind detection for 5G-NR.

Enhanced fair earliest due date first scheduling strategy for multimedia applications in LTE downlink framework

SummaryGuaranteeing a certain delay threshold for delay‐sensitive applications in long term evolution (LTE) cellular communication system is a very challenging mission. By implementing an optimal scheduling strategy, this mission will be achieved. In this article, a novel scheduler is introduced in order to meet a predefined level of service quality by guaranteeing a specific delay threshold for delay‐sensitive applications in LTE cellular systems. The proposed scheduler assigns the available resource blocks (RBs) to active user equipments (UEs) tacking into consideration several attributes. The expiration date of each packet, the channel quality, the average data rate previously achieved by each UE, and the number of dropped packets for each UE compared with the average number of packets totally dropped are all considered in the proposed scheduler working mechanism. Consequently, the proposed scheduling strategy reduces the number of packets dropped for multimedia applications, and at the same time maximizes the overall throughput of the network. Simulation results are provided to study and evaluate the performance of the proposed scheduling strategy. A comparative study is presented between the proposed strategy and the most recent scheduling techniques. The obtained results prove that the proposed scheduling strategy has considerably acceptable and appreciated results compared with the results of the state‐of‐the‐art scheduling techniques.

A Grant-Free Random Access Scheme for M2M Communication in Massive MIMO Systems

A novel grant-free random access scheme is proposed to support massive connectivity with low access delay and overhead for machine-to-machine communication in massive multiple-input–multiple-output systems. This scheme allows all active user equipments (UEs) to transmit their pilots and uplink messages via the same time–frequency resource and performs the joint active UEs detection and uplink message decoding without channel estimation in one shot by utilizing the proposed ensemble independent component analysis (EICA) decoding algorithm. We call the proposed scheme the EICA-based pilot random access (EICA-PA). We analyze the successful access probability, probability of missed detection, and uplink throughput of the EICA-PA scheme. Numerical results show that the EICA-PA scheme significantly improves the successful access probability and uplink throughput, decreases missed detection probability and provides low-frame error rate at the same time.

MIMO Cellular Networks Performance Under User-Assisted Relaying

We design user-assisted relaying strategies and analyze their performance in a multiple-input-multiple-output uplink cellular network. In user-assisted relaying, the base station serves an active user equipment (UE) using a transmission scheme adaptive between direct transmission and relaying via another UE according to a cooperation strategy. Modeling the network based on stochastic geometry and Poisson point processes, we propose a practical, geometric-based cooperation strategy determining how to select the relaying UE and when to perform relaying transmission. The proposed relaying transmission employs a simple transmit beamforming and one of two optimized receive combining schemes depending on interference awareness. The extra interference generated by relaying UEs is captured in an interference model that accounts for the adaptive transmission and random locations of these UEs. Integrating the proposed cooperation strategy, transmit and receive beamforming design, and interference model, we analyze the network outage rate performance. Provided sufficient density of potential relay UEs, results demonstrate user-assisted relaying to be most beneficial for cell edge UEs when the relaying UEs are equipped with multiple antenna elements and their signals propagate in relatively high shadowing environments.

Artificial bee colony algorithm for energy efficiency optimisation in massive MIMO system

This paper deals with antenna selection for multi-user massive MIMO systems with the aim of maximising energy efficiency. Massive MIMO technology, by employing a large number of antennas at base station, provides huge improvements in throughput and energy efficiency. The increased number of antennas leads to additional energy consumption due to RF chains and signal processing circuit. The main purpose of the paper is to determine the optimal subset of antennas at the base station that should be activated to serve a given number of active user equipment. This idea is implemented using artificial bee colony algorithm which has proven it efficiency by specifying the best control parameters.

Artificial bee colony algorithm for energy efficiency optimisation in massive MIMO system

This paper deals with antenna selection for multi-user massive MIMO systems with the aim of maximising energy efficiency. Massive MIMO technology, by employing a large number of antennas at base station, provides huge improvements in throughput and energy efficiency. The increased number of antennas leads to additional energy consumption due to RF chains and signal processing circuit. The main purpose of the paper is to determine the optimal subset of antennas at the base station that should be activated to serve a given number of active user equipment. This idea is implemented using artificial bee colony algorithm which has proven it efficiency by specifying the best control parameters.

A Novel SCMA System for Coexistence of Active Users and Inactive Users

This letter proposes a new sparse code multiple access (SCMA) system for handling the coexistence of active user equipments (UEs) and inactive UEs, which share the same frequency/time resources for an uplink grant-free scenario. SCMA systems use a message passing algorithm, which considers all UEs to be active UEs. Therefore, inactive UEs cause significant decoding problem in SCMA systems. In order to solve the coexistence problem, we propose code words and a novel SCMA receiver which can distinguish the signal of active/inactive UEs. The numerical results show that the proposed SCMA receiver achieves a remarkable enhancement in false alarm probability, miss detection probability, and bit-error rate.

Random Access in C-RAN for User Activity Detection With Limited-Capacity Fronthaul

Cloud-Radio Access Network (C-RAN) is characterized by a hierarchical structure in which the baseband processing functionalities of remote radio heads (RRHs) are implemented by means of cloud computing at a Central Unit (CU). A key limitation of C-RANs is given by the capacity constraints of the fronthaul links connecting RRHs to the CU. In this letter, the impact of this architectural constraint is investigated for the fundamental functions of random access and active User Equipment (UE) identification in the presence of a potentially massive number of UEs. In particular, the standard C-RAN approach based on quantize-and-forward and centralized detection is compared to a scheme based on an alternative CU-RRH functional split that enables local detection. Both techniques leverage Bayesian sparse detection. Numerical results illustrate the relative merits of the two schemes as a function of the system parameters.

Achieving Maximum Energy-Efficiency in Multi-Relay OFDMA Cellular Networks: A Fractional Programming Approach

In this paper, the joint power and subcarrier allocation problem is solved in the context of maximizing the energy-efficiency (EE) of a multi-user, multi-relay orthogonal frequency division multiple access (OFDMA) cellular network, where the objective function is formulated as the ratio of the spectral-efficiency (SE) over the total power dissipation. It is proven that the fractional programming problem considered is quasi-concave so that Dinkelbach's method may be employed for finding the optimal solution at a low complexity. This method solves the above-mentioned master problem by solving a series of parameterized concave secondary problems. These secondary problems are solved using a dual decomposition approach, where each secondary problem is further decomposed into a number of similar subproblems. The impact of various system parameters on the attainable EE and SE of the system employing both EE maximization (EEM) and SE maximization (SEM) algorithms is characterized. In particular, it is observed that increasing the number of relays for a range of cell sizes, although marginally increases the attainable SE, reduces the EE significantly. It is noted that the highest SE and EE are achieved, when the relays are placed closer to the BS to take advantage of the resultant line-of-sight link. Furthermore, increasing both the number of available subcarriers and the number of active user equipment (UE) increases both the EE and the total SE of the system as a benefit of the increased frequency and multi-user diversity, respectively. Finally, it is demonstrated that as expected, increasing the available power tends to improve the SE, when using the SEM algorithm. By contrast, given a sufficiently high available power, the EEM algorithm attains the maximum achievable EE and a suboptimal SE.