51 research outputs found
Design of Joint Spatial and Power Domain Multiplexing Scheme for Massive MIMO Systems
Massive Multiple-Input Multiple-Output (MIMO) is one of the key techniques in 5th generation wireless systems (5G) due to its potential ability to improve spectral efficiency. Most of the existing works on massive MIMO only consider Time Division Duplex (TDD) operation that relies on channel reciprocity between uplink and downlink channels. For Frequency Division Duplex (FDD) systems, with continued efforts, some downlink multiuser MIMO scheme was recently proposed in order to enable “massive MIMO” gains and simplified system operations with limited number of radio frequency (RF) chains in FDD system. However these schemes, such as Joint Spatial Division and Multiplexing (JSDM) scheme and hybrid precoding scheme, only focus on multiuser transmission in spatial domain. Different from most of the existing works, this paper proposes Joint Spatial and Power Multiplexing (JSPM) scheme in FDD systems. It extends existing FDD schemes from spatial division and multiplexing to joint spatial and power domain to achieve more multiplexing gain. The user grouping and scheduling scheme of JSPM is studied and the asymptotic expression for the sum capacity is derived as well. Finally, simulations are conducted to illustrate the effectiveness of the proposed scheme
Cognitive Non-Orthogonal Multiple Access with Cooperative Relaying:A New Wireless Frontier for 5G Spectrum Sharing
Two emerging technologies toward 5G wireless networks, namely non-orthogonal multiple access (NOMA) and cognitive radio (CR), will provide more efficient utilization of wireless spectrum in the future. In this article, we investigate the integration of NOMA with CR into a holistic system, namely a cognitive NOMA network, for more intelligent spectrum sharing. Design principles of cognitive NOMA networks are perfectly aligned to functionality requirements of 5G wireless networks, such as high spectrum efficiency, massive connectivity, low latency, and better fairness. Three different cognitive NOMA architectures are presented, including underlay NOMA networks, overlay NOMA networks, and CR-inspired NOMA networks. To address inter-network and intra-network interference, which largely degrade the performance of cognitive NOMA networks, cooperative relaying strategies are proposed. For each cognitive NOMA architecture, our proposed cooperative relaying strategy shows its potential to significantly lower outage probabilities. We discuss open challenges and future research directions on implementation of cognitive NOMA networks
Statistical priority-based uplink scheduling for M2M communications
Currently, the worldwide network is witnessing major efforts to transform it from being the Internet of humans only to becoming the Internet of Things (IoT). It is expected that Machine Type Communication Devices (MTCDs) will overwhelm the cellular networks with huge traffic of data that they collect from their environments to be sent to other remote MTCDs for processing thus forming what is known as Machine-to-Machine (M2M) communications. Long Term Evolution (LTE) and LTE-Advanced (LTE-A) appear as the best technology to support M2M communications due to their native IP support. LTE can provide high capacity, flexible radio resource allocation and scalability, which are the required pillars for supporting the expected large numbers of deployed MTCDs. Supporting M2M communications over LTE faces many challenges. These challenges include medium access control and the allocation of radio resources among MTCDs. The problem of radio resources allocation, or scheduling, originates from the nature of M2M traffic. This traffic consists of a large number of small data packets, with specific deadlines, generated by a potentially massive number of MTCDs. M2M traffic is therefore mostly in the uplink direction, i.e. from MTCDs to the base station (known as eNB in LTE terminology). These characteristics impose some design requirements on M2M scheduling techniques such as the need to use insufficient radio resources to transmit a huge amount of traffic within certain deadlines. This presents the main motivation behind this thesis work. In this thesis, we introduce a novel M2M scheduling scheme that utilizes what we term the “statistical priority” in determining the importance of information carried by data packets. Statistical priority is calculated based on the statistical features of the data such as value similarity, trend similarity and auto-correlation. These calculations are made and then reported by the MTCDs to the serving eNBs along with other reports such as channel state. Statistical priority is then used to assign priorities to data packets so that the scarce radio resources are allocated to the MTCDs that are sending statistically important information. This would help avoid exploiting limited radio resources to carry redundant or repetitive data which is a common situation in M2M communications. In order to validate our technique, we perform a simulation-based comparison among the main scheduling techniques and our proposed statistical priority-based scheduling technique. This comparison was conducted in a network that includes different types of MTCDs, such as environmental monitoring sensors, surveillance cameras and alarms. The results show that our proposed statistical priority-based scheduler outperforms the other schedulers in terms of having the least losses of alarm data packets and the highest rate in sending critical data packets that carry non-redundant information for both environmental monitoring and video traffic. This indicates that the proposed technique is the most efficient in the utilization of limited radio resources as compared to the other techniques
Next-Generation Full Duplex Networking System Empowered by Reconfigurable Intelligent Surfaces
Full duplex (FD) radio has attracted extensive attention due to its co-time
and co-frequency transceiving capability. {However, the potential gain brought
by FD radios is closely related to the management of self-interference (SI),
which imposes high or even stringent requirements on SI cancellation (SIC)
techniques. When the FD deployment evolves into next-generation mobile
networking, the SI problem becomes more complicated, significantly limiting its
potential gains.} In this paper, we conceive a multi-cell FD networking scheme
by deploying a reconfigurable intelligent surface (RIS) at the cell boundary to
configure the radio environment proactively. To achieve the full potential of
the system, we aim to maximize the sum rate (SR) of multiple cells by jointly
optimizing the transmit precoding (TPC) matrices at FD base stations (BSs) and
users and the phase shift matrix at RIS. Since the original problem is
non-convex, we reformulate and decouple it into a pair of subproblems by
utilizing the relationship between the SR and minimum mean square error (MMSE).
The optimal solutions of TPC matrices are obtained in closed form, while both
complex circle manifold (CCM) and successive convex approximation (SCA) based
algorithms are developed to resolve the phase shift matrix suboptimally. Our
simulation results show that introducing an RIS into an FD networking system
not only improves the overall SR significantly but also enhances the cell edge
performance prominently. More importantly, we validate that the RIS deployment
with optimized phase shifts can reduce the requirement for SIC and the number
of BS antennas, which further reduces the hardware cost and power consumption,
especially with a sufficient number of reflecting elements. As a result, the
utilization of an RIS enables the originally cumbersome FD networking system to
become efficient and practical.Comment: 15 pages, 14 figure
On the Feasibility of Utilizing Commercial 4G LTE Systems for Misson-Critical IoT Applications
Emerging Internet of Things (IoT) applications and services including e-healthcare, intelligent transportation systems, smart grid, and smart homes to smart cities to smart workplace, are poised to become part of every aspect of our daily lives. The IoT will enable billions of sensors, actuators, and smart devices to be interconnected and managed remotely via the Internet. Cellular-based Machine-to-Machine (M2M) communications is one of the key IoT enabling technologies with huge market potential for cellular service providers deploying Long Term Evolution (LTE) networks. There is an emerging consensus that Fourth Generation (4G) and 5G cellular technologies will enable and support these applications, as they will provide the global mobile connectivity to the anticipated tens of billions of things/devices that will be attached to the Internet.
Many vital utilities and service industries are considering the use of commercially available LTE cellular networks to provide critical connections to users, sensors, and smart M2M devices on their networks, due to its low cost and availability. Many of these emerging IoT applications are mission-critical with stringent requirements in terms of reliability and end-to-end (E2E) delay bound. The delay bound specified for each application refers to the device-to-device latencies, which is defined as the combined delay resulting from both application level processing time and communication latency. Each IoT application has its own distinct performance requirements in terms of latency, availability, and reliability. Typically, uplink (UL) traffic of most of these IoT applications is the dominant network traffic (much higher than total downlink (DL) traffic).
Thus, efficient LTE UL scheduling algorithms at the base station (“Evolved NodeB (eNB)” per 3GPP standards) are more critical for M2M applications. LTE, however, was not originally intended for IoT applications, where traffic generated by M2M devices (running IoT applications) has totally different characteristics than those from traditional Human-to-Human (H2H)-based voice/video and data communications. In addition, due to the anticipated massive deployment of M2M devices and the limited available radio spectrum, the problem of efficient radio resources management (RRM) and UL scheduling poses a serious challenge in adopting LTE for M2M communications.
Existing LTE quality of service (QoS) standard and UL scheduling algorithms were mainly optimized for H2H services and can’t accommodate such a wide range of diverging performance requirements of these M2M-based IoT applications. Though 4G LTE networks can support very low Packet Loss Ratio (PLR) at the physical layer, such reliability, however, comes at the expense of increased latency from tens to hundreds of ms due to the aggressive use of retransmission mechanisms. Current 4G LTE technologies may satisfy a single performance metric of these mission critical applications, but not the simultaneous support of ultra-high reliability and low latency as well as high data rates.
Numerous QoS aware LTE UL scheduling algorithms for supporting M2M applications as well as H2H services have been reported in the literature. Most of these algorithms, however, were not intended for the support of mission critical IoT applications, as they are not latency-aware. In addition, these algorithms are simplified and don’t fully conform to LTE’s signaling and QoS standards. For instance, a common practice is the assumption that the time domain UL scheduler located at the eNB prioritizes user equipment (UEs)/M2M devices connection requests based on the head-of-line (HOL) packet waiting time at the UE/device transmission buffer. However, as will be detailed below, LTE standard does not support a mechanism that enables the UEs/devices to inform the eNB uplink scheduler about the waiting time of uplink packets residing in their transmission buffers.
Ultra-Reliable Low-Latency Communication (URLLC) paradigm has recently emerged to enable a new range of mission-critical applications and services including industrial automation, real-time operation and control of the smart grid, inter-vehicular communications for improved safety and self-deriving vehicles. URLLC is one of the most innovative 5G New Radio (NR) features. URLLC and its supporting 5G NR technologies might become a commercial reality in the future, but it may be rather a distant future.
Thus, deploying viable mission critical IoT applications will have to be postponed until URLLC and 5G NR technologies are commercially feasible. Because IoT applications, specifically mission critical, will have a significant impact on the welfare of all humanity, the immediate or near-term deployments of these applications is of utmost importance. It is the purpose of this thesis to explore whether current commercial 4G LTE cellular networks have the potential to support some of the emerging mission critical IoT applications. Smart grid is selected in this work as an illustrative IoT example because it is one of the most demanding IoT applications, as it includes diverse use cases ranging from mission-critical applications that have stringent requirements in terms of E2E latency and reliability to those that require support of massive number of connected M2M devices with relaxed latency and reliability requirements.
The purpose of thesis is two fold: First, a user-friendly MATLAB-based open source software package to model commercial 4G LTE systems is developed. In contrast to mainstream commercial LTE software packages, the developed package is specifically tailored to accurately model mission critical IoT applications and above all fully conforms to commercial 4G LTE signaling and QoS standards. Second, utilizing the developed software package, we present a detailed realistic LTE UL performance analysis to assess the feasibility of commercial 4G LTE cellular networks when used to support such a diverse set of emerging IoT applications as well as typical H2H services
D4.3 Final Report on Network-Level Solutions
Research activities in METIS reported in this document focus on proposing solutions
to the network-level challenges of future wireless communication networks. Thereby, a large variety of scenarios is considered and a set of technical concepts is proposed to serve the needs envisioned for the 2020 and beyond.
This document provides the final findings on several network-level aspects and groups of
solutions that are considered essential for designing future 5G solutions. Specifically, it
elaborates on:
-Interference management and resource allocation schemes
-Mobility management and robustness enhancements
-Context aware approaches
-D2D and V2X mechanisms
-Technology components focused on clustering
-Dynamic reconfiguration enablers
These novel network-level technology concepts are evaluated against requirements defined
by METIS for future 5G systems. Moreover, functional enablers which can support the
solutions mentioned aboveare proposed.
We find that the network level solutions and technology components developed during the course of METIS complement the lower layer technology components and thereby effectively contribute to meeting 5G requirements and targets.Aydin, O.; Valentin, S.; Ren, Z.; Botsov, M.; Lakshmana, TR.; Sui, Y.; Sun, W.... (2015). D4.3 Final Report on Network-Level Solutions. http://hdl.handle.net/10251/7675
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Spectrally efficient Non-Orthogonal Multiple Access (NOMA) techniques for future generation mobile systems
With the expectation of over a 1000-fold increase in the number of connected devices by 2020, efficient utilization of the limited bandwidth has become ever more important in the design of mobile wireless systems. Furthermore, the ever-increasing demand for higher data rates has made it necessary for a new waveform design that satisfies not only throughput demands, but network capacity as well. One such technique recently proposed is the non-orthogonal multiple access (NOMA) which utilizes the distance-dependent power domain multiplexing, based on the principles of signal superposition.
In this thesis, new spectrally efficient non-orthogonal signal techniques are proposed. The goal of the schemes is to allow simultaneous utilization of the same time frequency network resources. This is achieved by designing component signals in both power and phase domain such that users are precoded or preformed to form a single and uniquely decodable composite signal. The design criteria are based on maximizing either the sum rate or spectral efficiency, minimizing multi-user interference and detection ambiguity, and maximizing the minimum Euclidean distance between the composite constellation points. The design principles are applied in uplink, downlink and coordinated multipoint (CoMP) scenarios. We assume ideal channel state with perfect estimation, low mobility and synchronization scenarios so as to prove the concept and serve as a bound for any future work in non-ideal conditions. Extensive simulations and numerical analysis are carried to show the superiority and compatibility of the schemes.
First, a new NOMA signal design called uplink NOMA with constellation precoding is proposed. The precoding weights are generated at the eNB based on the number of users to be superposed. The eNB signals the precoding weights to be employed by the users to adjust their transmission. The adjustments utilize the channel state information estimated from common periodic pilots broadcasted by the eNB. The weights ensure the composite received signal at the eNB belongs to the pre-known constellation. Furthermore, the users precode to the eNB antenna that requires the least total transmit power from all the users. At the eNB, joint maximum likelihood (JML) detection is employed to recover the component signals. As the composite constellation is as that of a single user transmitting that same constellation, multiple access interference can be viewed as absent, which allows multiple users to transmit at their full rates. Furthermore, the power gain achieved by the sum of the component signals maximizes the sum rate.
Secondly, the constellation design principle is employed in the downlink scenario. In the scheme, called downlink NOMA with constellation preforming, the eNB preforms the users signal with power and phase weights prior to transmission. The preforming ensures multi-user interference is eliminated and the spectral efficiency maximized. The preformed composite constellation is broadcasted by the eNB which is received by all users. Subsequently, the users perform JML detection with the designed constellation to extract their individual component signals. Furthermore, improved signal reliability is achieved in transmit and receive diversity scenarios in the schemes called distributed transmit and receive diversity combining, respectively.
Thirdly, the constellation preforming on the downlink is extended to MIMO spatial multiplexing scenarios. The first MIMO scheme, called downlink NOMA with constellation preforming, each eNB antenna transmits a preformed composite signal composed of a set of multiple users’ streams. This achieves spatial multiplexing with diversity with less transmit antennas, reducing costs associated with multiple RF chains, while still maximizing the sum rate. In the second MIMO scheme, a highly spectrally efficient MIMO preforming scheme is proposed. The scheme, called group layer MIMO with constellation preforming, the eNB preforms to a specific group of users on each transmit antenna. In all the schemes, the users perform JML detection to recover their signals.
Finally, the adaptability of the constellation design is shown in CoMP. The scheme, called CoMP with joint constellation processing, the additional degrees of freedom, in form of interfering eNBs, are utilized to enable spatial multiplexing to a user with a single receive antenna. This is achieved by precoding each stream from the coordinating eNB with weights signalled by a central eNB. Consequently, the inter-cell interference is eliminated and the sum-rate maximized. To reduce the total power spent on precoding, an active cell selection scheme is proposed where the precoding is employed on the highest interferers to the user. Furthermore, a power control scheme is applied the design principle, where the objective is to reduce cross-layer interference by adapting the transmission power to the mean channel gain
D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies
This document provides the most recent updates on the technical contributions and research
challenges focused in WP3. Each Technology Component (TeC) has been evaluated
under possible uniform assessment framework of WP3 which is based on the simulation guidelines
of WP6. The performance assessment is supported by the simulation results which are in their
mature and stable state. An update on the Most Promising Technology Approaches (MPTAs)
and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission
technologies in 5G systems has also been provided. This consolidated view is further
supported in this document by the presentation of the impact of MPTAs on METIS scenarios
and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675
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