Spectral precoding is a promising technique to suppress out-of-band emissions and comply with leakage constraints over adjacent frequency channels and with mask requirements on the unwanted emissions. However, spectral precoding may distort the original data vector, which is formally expressed as the error vector magnitude (EVM) between the precoded and original data vectors. Notably, EVM has a deleterious impact on the performance of multiple-input multiple-output orthogonal frequency division multiplexing-based systems. In this paper we propose a novel spectral precoding approach which constrains the EVM while complying with the mask requirements. We first formulate and solve the EVM-unconstrained mask-compliant spectral precoding problem, which serves as a springboard to the design of two EVM-constrained spectral precoding schemes. The first scheme takes into account a wideband EVM-constraint which limits the average in-band distortion. The second scheme takes into account frequency-selective EVM-constraints, and consequently, limits the signal distortion at the subcarrier level. Numerical examples illustrate that both proposed schemes outperform previously developed schemes in terms of important performance indicators such as block error rate and system-wide throughput while complying with spectral mask and EVM constraints.
Although spectral precoding is a propitious technique to suppress out-of-band emissions, it has a detrimental impact on the system-wide throughput performance, notably, in high data-rate multiple-input multiple-output (MIMO) systems with orthogonal frequency division multiplexing (OFDM), because of (spatially-coloured) transmit error vector magnitude (TxEVM) emanating from spectral precoding. The first contribution of this paper is to propose two mask-compliant spectral precoding schemes, which mitigate the resulting TxEVM seen at the receiver by capitalizing on the immanent degrees-of-freedom in (massive) MIMO systems and consequently improve the system-wide throughput. Our second contribution is an introduction to a new and simple three-operator consensus alternating direction method of multipliers (ADMM) algorithm, referred to as TOP-ADMM, which decomposes a large-scale problem into easy-to-solve subproblems. We employ the proposed TOP-ADMM-based algorithm to solve the spectral precoding problems, which offer computational efficiency. Our third contribution presents substantial numerical results by using an NR release 15 compliant simulator. In case of perfect channel knowledge at the transmitter, the proposed methods render similar block error rate and throughput performance as without spectral precoding yet meeting out-of-band emission (OOBE) requirements at the transmitter. Further, no loss on the OOBE performance with a graceful degradation on the throughput is observed under channel uncertainty.
This paper deals with a distortion-based non-convex peak-to-average power ratio (PAPR) problem for large-scale multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Our work is motivated by the observation that the distortion stemming from the PAPR reduction schemes has a deleterious impact on the data rates of MIMO-OFDM systems. Recently, some approaches have been proposed to either null or mitigate such distortion seen at the receiver(s) side by exploiting the extra degrees of freedom when the downlink channel is perfectly known at the transmitter. Unfortunately, most of these proposed methods are not robust against channel uncertainty, since perfect channel knowledge is practically infeasible at the transmitter. Although some recent works utilize semidefinite programming to cope with channel uncertainty and non-convex PAPR problem, they have formidable computational complexity. Additionally, some prior-art techniques tackle the non-convex PAPR problem by minimizing the peak power, which renders a suboptimal solution. In this work, we showcase the application of powerful first-order optimization schemes, namely the three-operator alternating direction method of multipliers (ADMM)-type techniques, notably 1) three-operator ADMM, 2) Bregman ADMM, and 3) Davis-Yin splitting, to solve the non-convex and robust PAPR problem, yielding a near-optimal solution in a computationally efficient manner.
This paper proposes a new large-scale mask compliant spectral precoder (LS-MSP) for orthogonal frequency division multiplexing systems. In this paper, we first consider a previously proposed mask-compliant spectral precoding scheme that utilizes a generic convex optimization solver which suffers from high computational complexity, notably in large-scale systems. To mitigate the complexity of computing the LS-MSP, we propose a divide-and-conquer approach that breaks the original problem into smaller rank 1 quadratic-constraint problems and each small problem yields closed-form solution. Based on these solutions, we develop three specialized first-order low-complexity algorithms, based on 1) projection on convex sets and 2) the alternating direction method of multipliers. We also develop an algorithm that capitalizes on the closed-form solutions for the rank 1 quadratic constraints, which is referred to as 3) semianalytical spectral precoding. Numerical results show that the proposed LS-MSP techniques outperform previously proposed techniques in terms of the computational burden while complying with the spectrum mask. The results also indicate that 3) typically needs 3 iterations to achieve similar results as 1) and 2) at the expense of a slightly increased computational complexity.
A radio base station generates a congestion status flag, based on measured resource usage in its cell, and based on performance of sessions in the cell. The flag may be a one bit, or a small number of bits, indicating whether the base station is congested. The flag can be sent to neighboring radio base stations, for use in determining whether to perform handovers to that radio base station. The flag generated in a radio base station, and the flags generated in neighboring radio base stations, can also be sent to user equipment in a cell.
A method, User Equipment (UE), and network node in an ad-hoc network. The UE determines a node in the ad-hoc network that is able to provide a reference signal comprising a pattern that can be used for synchronization purposes when the UE is in DRX mode in the ad-hoc network. The node is determined by requesting the node to indicate whether the node is able to provide the reference signal, and receiving an accept signal or message from the node. The UE then receives the reference signal from the determined node, enters DRX mode, and uses the received reference signal to maintain synchronization while in the DRX mode.
A method for controlling uplink transmissions from a user device (3) to an access point (5) in a wireless telecommunications system is described. Each access point defines a communications cell, and the method comprises monitoring interference in an uplink channel at an access point (5), performing interference control actions at the access point when monitored interference exceeds a first predetermined level, monitoring occurrences of such control actions at the access point (5), and if a number of such occurrences exceeds a predetermined level, performing interference control actions with reference to a plurality of cells at a central controller (11) of the telecommunications system, which central controller is operable to control a plurality of access points (5).
The invention discloses a method for a cellular communications system, in which there is a first plurality of cells and a second plurality of base stations, each base station controlling the traffic to and from user terminals in a cell. User terminals can assume an idle mode, where a user terminal when in an idle mode performs cell reselection, comprising an evaluation of the cells which are available to the user terminal. The base stations of a number of cells in the system transmit a set of reselection probabilities, each probability in said set being the probability with which a terminal when in idle mode may carry out a reselection from its present cell to the cell to which the probability refers.
Embodiments herein include a method in a base station serving a cell for assisting a user equipment to select a cell. The method comprises the step of sending a message comprising a reference to a service class and a priority level associated with a radio access technology used by the cell that the base station serves. Embodiments herein also include a corresponding arrangement in a base station. Embodiments herein further include a method in a core network node for configuring service classes in a network. The method comprises associating a radio access technology with a service class and a priority level. The method further comprises sending to a base station a reference to the service class and the priority level associated with the radio access technology used by the base station. Embodiments herein finally include a corresponding arrangement in a core network node.
Methods and apparatus for scheduling link resources in a wireless communication system (100) are disclosed. In an exemplary method, a first scheduling policy vector (210), or SPV (210), is generated, the SPV (210) including scheduling elements (220) that prescribe a probability of use for each of several corresponding quantities of link resources. In some embodiments the link resources are LTE resource blocks. The SPV (210) is transmitted to a mobile terminal (150) for use in determining a quantity of link resource units to be scheduled in at least a first transmission time interval. The SPV (210) may be transmitted along with a scheduling window parameter that specifies a period of applicability for SPV (210).
The present invention generally relates to wireless communication systems, and particularly relates to scheduling of resources in such systems.
User equipment, UEs, (306 a,d) being interfered by direct D2D traffic, and UEs (306 b,c) involved in D2D communication being interfered by a UE (306 a,d), instead of passively reporting that they are interfered to their serving base station (305), intervene and communicate directly with the pair of D2D communicating UEs or the UE that are causing the interference without involving any of the serving base stations.
While several previous works have considered the problem of resource (including subcarrier and power) allocation in multicell orthogonal frequency division multiple access networks, only a few contributions have explicitly taken into account the elastic nature of data applications. In this work, each user is associated with a minimum and maximum resource block requirement and the resource allocation problem consists of maximizing the overall throughput such that these requirements are met. We propose a hybrid method that partitions this problem into a centralized and a distributed algorithm that balances between maximizing the overall throughput and being feasible in real systems. By means of simulations we compare four resource allocation strategies that represent various degrees of multi- cell coordination and taking advantage of multi-user diversity. We find that a feasible dynamic coordination combined with intra-cell multi-user diversity provides large throughput gains compared with non-coordinated schemes or schemes that would limit the degree of freedom of multi-user diversity.
According to a first aspect of embodiments herein, the object is achieved by a method in a base station for handling a process of discovering a candidate user equipment for Device to Device, D2D, communication in a cell. The cell is served by the base station. The base station divides (200) the cell into a number of regions. The base station then assigns (201) to each one out of the number of regions, a channel resource for use in the region. The channel resource is for sending beacon signals in the process of discovering the D2D candidate user equipment.
Analysis of Markov Reward Models (MRM) with preemptive resume (prs) policy results in a double transform expression, whose solution is based on the inverse transformations both in time and reward variable domain. We present a symbolic expression of moments of the completion time, from which a computationally effective recursive numerical method can be obtained. (C) 1998 Elsevier Science Ltd. All rights reserved.
While acquiring channel state information at the transmitter (CSIT) in time division duplexing systems can exploit channel reciprocity, acquiring accurate CSIT in frequency division duplexing massive multiple-input multiple-output systems is not trivial. The two main difficulties in these systems are the scalability of the downlink reference signals and the overhead associated with the required uplink feedback. Although several approaches for ensuring scalability and reducing overhead by leveraging some presumed channel properties have been studied, existing schemes do not offer a fully satisfactory solution. In this work, we propose a novel cooperative method which exploits low-rate beam-related information exchange between the mobile terminals, reduces the overhead under the assumption of the so-called grid-of-beams design, and strikes a balance between CSIT acquisition overhead, user spatial separability and coordination complexity.
Massive multiple-input multiple-output (mMIMO) communications are one of the enabling technologies of 5G and beyond networks. While prior work indicates that mMIMO networks employing time division duplexing have a significant capacity growth potential, deploying mMIMO in frequency division duplexing (FDD) networks remains problematic. The two main difficulties in FDD networks are the scalability of the downlink reference signals and the overhead associated with the required uplink feedback for channel state information (CSI) acquisition. To address these difficulties, most existing methods utilize assumptions on the radio environment such as channel sparsity or angular reciprocity. In this work, we propose a novel cooperative method for a scalable and low-overhead approach to FDD mMIMO under the so-called grid-of-beams architecture. The key idea behind our scheme lies in the exploitation of the near-common signal propagation paths that are often found across several mobile users located in nearby regions, through a coordination mechanism. In doing so, we leverage the recently specified device-to-device communications capability in 5G networks. Specifically, we design beam selection algorithms capable of striking a balance between CSI acquisition overhead and multi-user interference mitigation. The selection exploits statistical information, through so-called covariance shaping. Simulation results demonstrate the effectiveness of the proposed algorithms, which prove particularly well-suited to rapidly-varying channels with short coherence time.
In multicell wireless networks the resource allocation task includes the selection of the serving cell and the allocation of channels and transmission powers. While all of these tasks have been studied in the past, all three jointly are seldom addressed. In this paper we formulate the joint cell, channel and power allocation problem as an optimization task, whose purpose is to maximize the total user throughput. The joint problem is decomposed into separate subproblems of cell, channel and power allocation. We propose heuristic and optimization based algorithms to solve each of these tasks and present numerical results that give new and valuable insights into a sum throughput optimal joint resource allocation strategy.
A method in a first user equipment (110) and a first user equipment (110) for providing information about at least one of a first and a second connection state are provided. Moreover, a corresponding method in a second user equipment (120) and a second user equipment (120) are provided. The first connection state is related to a first connection between the first user equipment (110) and a radio network node (140). The second connection state is related to a second connection between the first user equipment (110) and the second user equipment (120). The first user equipment (110) encodes (220) information about at least one of the first and second connection states into a synchronization signal for synchronizing the second user equipment (120) to the first user equipment (110). The first user equipment (110) sends (230) the synchronization signal to at least the second user equipment (120), thereby providing information about at least one of the first and second connection states. The second user equipment (120) decodes (250) the synchronization signal.
A home base station receives from a wireless user equipment an identification of a selected Public Land Mobile Network, PLMN, among multiple available PLMNs to which the wireless user equipment is to be connected. The home base station identifies a communication path to a home base station gateway is associated with the selected PLMN and communicates with the selected PLMN that was identified over the communication path that was identified. The home base station may thereby be shared among multiple PLMNs. Related networks, methods and home base stations are described.
The exemplary embodiments relate to a method for use in a user equipment (UE), and a cellular infrastructure, for achieving synchronization between UEs for a peer-to-peer or device-to-device (D2D) communication. The method comprising: receiving at a UE a synchronization message from a cell or a RAT or a source of the cellular infrastructure; assembling a message including a list comprising information on the source or cell or RAT, sending the assembled message to a another UE and initiate synchronization between involved UEs based on the information in the assembled message.
Embodiments herein relate to a first radio base station (12) for handling radio interference in a radio communications network, which first radio base station (12) provides radio coverage over a geographical area forming a first cell (14). In the first cell (14) a first user equipment (10) and a second user equipment (11) are served, which first radio base station (12), the first user equipment (10) and the second user equipment (11) are comprised in the radio communications network. The first radio base station (12) determines that a first radio resource is allocated to the first user equipment (10) for communicating over a device-to-device, D2D, connection with the second user equipment (11) within the first cell (14), The first radio base station then transfers information to an arrangement serving a second cell (15), which information identifies the first radio resource and indicates that the first radio resource is allocated to the first user equipment (10) for communicating over the D2D connection with the second user equipment (11) within the first cell (14). The information is to be taken into account by the arrangement serving the second cell (15) for scheduling a second radio resource to a third user equipment (16) in the second cell.
Multiple-input multiple-output (MIMO) millimeter-wave (mm-wave) systems are vulnerable to hardware impairments due to operating at high frequencies and employing a large number of radio-frequency hardware components. In particular, nonlinear power amplifiers (PAs) employed at the transmitter distort the signal when operated close to saturation due to energy efficiency considerations. In this paper, we study the performance of an MIMO mm-wave hybrid beamforming scheme in the presence of nonlinear PAs. First, we develop a statistical model for the transmitted signal in such systems and show that the spatial direction of the inband distortion is shaped by the beamforming filter. This suggests that even in the large antenna regime, where narrow beams can be steered toward the receiver, the impact of nonlinear PAs should not be ignored. Then, by employing a realistic power consumption model for the PAs, we investigate the tradeoff between spectral and energy efficiency in such systems. Our results show that increasing the transmit power level when the number of transmit antennas grows large can be counter-effective in terms of energy efficiency. Furthermore, using numerical simulation, we show that when the transmit power is large, analog beamforming leads to higher spectral and energy efficiency compared to digital and hybrid beamforming schemes.
Although the benefits of precoding and combining of data streams are widely recognized, the potential of precoding the pilot signals at the user equipment (UE) side and combining them at the base station (BS) side has not received adequate attention. This paper considers a multiuser multiple input multiple output (MU-MIMO) cellular system in which the BS acquires channel state information (CSI) by means of uplink pilot signals and proposes pilot precoding and combining to improve the CSI quality. We first evaluate the channel estimation performance of a baseline scenario in which CSI is acquired with no pilot precoding. Next, we characterize the channel estimation error when the pilot signals are precoded by spatial filters that asymptotically maximize the channel estimation quality. Finally, we study the case when, in addition to pilot precoding at the UE side, the BS utilizes the second order statistics of the channels to further improve the channel estimation performance. The analytical and numerical results show that, specially in scenarios with large number of antennas at the BS and UEs, pilot precoding and combining has a great potential to improve the channel estimation quality in MU-MIMO systems.
Joint communication and sensing (JCAS) systems use the same spectrum, hardware and antenna resources to jointly provide spectrally efficient communication, localization and sensing services. While previous work has analyzed the performance of communication with connected objects and localization of unconnected (passive) objects, the joint positioning of both connected and passive objects is less studied. In this paper, we consider a JCAS cellular system using orthogonal frequency-division multiplexing, in which the uplink communication signal is scattered on a moving target towards multiple receiving base stations. In this setting, multistatic sensing by cooperating base stations makes it possible to position the moving target while also positioning the transmitting user equipment based on the received communication signal at the base stations. We propose a channel model that can characterize the propagation of both the communication and sensing signals, and algorithms that facilitate the estimation of direction of arrivals and range, which in turn enables the system to infer the positions of both the communicating user and the passive target. We also show some illustrative results from the algorithms that indicate what such joint positioning practically can look like.
The performance of Global Navigation Satellite System (GNSS)-based positioning techniques degrades in tunnels, urban canyons and other areas, in which GNSS coverage is poor. Recent advances indicate that radio-based positioning techniques have the potential of complementing GNSS-based positioning services in such problematic areas. In this work, we propose to combine range and angle measurements routinely exercised by fifth generation of mobile communication (5G) base stations with acceleration measurements by vehicles to generate position estimates. Specifically, we propose to utilize an extended Kalman filter to combine the range, angle and acceleration measurements. The accuracy of this positioning system is studied in millimeter-wave 5G cellular networks. Specifically, the proposed positioning system using 5G and sensor fusion is tested in a highway scenario in which 5G base stations provide cellular coverage. In this setting, we study the impact of certain parameters of the 5G network such as the available bandwidth and the propagation environment on the positioning accuracy. We find that the positioning accuracy is largely affected by the number of antennas in the base station and that the proposed scheme outperforms GNSS based schemes in the problematic areas.
Massive MIMO systems, while being a promising technology for 5G systems, face a number of practical challenges. Among those, pilot contamination stands out as a key bottleneck to design high-capacity beamforming methods. We propose and analyze a location-aided approach to reduce the pilot contamination effect in uplink channel estimation for massive MIMO systems. The proposed method exploits the location of user terminals, scatterers, and base stations. The approach removes the need for direct estimation of large covariance matrices and provides good channel estimation performance in the large antenna regime.
Multiple-input multiple-output (MIMO) millimeter wave (mmWave) systems are a promising candidate to support extremely high data rate services in future wireless communication networks. However, operating at high frequencies and employing a large number of radio frequency (RF) hardware components make MIMO mmWave systems vulnerable to hardware impairments. In particular, nonlinear power amplifiers (PAs) employed at the transmitter distort the signal when operated close to their saturation regions due to energy efficiency considerations. In this paper, we study the performance of a MIMO mmWave hybrid beamforming scheme in the presence of nonlinear PAs. First, distortion signal we develop a statistical model for the transmitted signal in such systems and show that the spatial distortion signal is shaped by the beamforming filter. This suggests thateven in the large antenna regime, where narrow beams can begenerated and steered toward the receiver, the impact of thenonlinear PAs should not be ignored. Then, by employing arealistic power consumption model for the PAs, we investigate thetrade-off between spectral and energy efficiency in such systems.For the special case, when the number of transmit RF-chains isone, closed forms for the achievable spectral efficiency as wellas the system energy efficiency is derived. Our results show thatwhen using hybrid beamforming, increasing the transmit powerlevel when the number of transmit antennas grows large can becounter-effective in terms of spectral and energy efficiency. Onthe other hand, with a moderate number of transmit antennas,increasing the transmit power up to a certain threshold isbeneficial for the spectral and energy efficiency of the system.
Although the benefits of precoding and combining data signals are widely recognized, the potential of these techniques for pilot transmission is not fully understood. This is particularly relevant for multiuser multiple-input multiple-output(MU-MIMO) cellular systems using millimeter-wave (mmWave)communications, where multiple antennas have to be used both at the transmitter and the receiver to overcome the severe path loss.In this paper, we characterize the gains of pilot precoding and combining in terms of channel estimation quality and achievable data rate. Specifically, we consider three uplink pilot transmission scenarios in a mmWave MU-MIMO cellular system: 1) non-precoded and uncombined, 2) precoded but uncombined, and3) precoded and combined. We show that a simple precoder that utilizes only the second-order statistics of the channel reduces the variance of the channel estimation error by a factor that is proportional to the number of user equipment (UE) antennas.We also show that using a linear combiner design based on the second-order statistics of the channel significantly reduces multiuser interference and provides the possibility of reusing some pilots. Specifically, in the large antenna regime, pilot preceding and combining help to accommodate a large number ofUEs in one cell, significantly improve channel estimation quality, boost the signal-to-noise ratio of the UEs located close to the cell edges, alleviate pilot contamination, and address the imbalanced coverage of pilot and data signals.
Driven by the unprecedented increase of mobile data traffic, D2D communications technology is rapidly moving into the mainstream of the 5G networking landscape. While D2D connectivity originally emerged as a technology enabler for public safety services, it is likely to remain at the heart of the 5G ecosystem by spawning a wide diversity of proximate applications and services. In this work, we argue that the widespread adoption of the direct communications paradigm is unlikely without embracing the concepts of trust and social-aware cooperation between end users and network operators. However, such adoption remains conditional on identifying adequate incentives that engage humans and their connected devices in a plethora of collective activities. To this end, the mission of our research is to advance the vision of social-aware and trusted D2D connectivity, as well as to facilitate its further adoption. We begin by reviewing the various types of underlying incentives with the emphasis on sociality and trust, discuss these factors specifically for humans and for networked devices (machines), and also propose a novel framework allowing construction of much needed incentive-aware D2D applications. Our supportive system-level performance evaluations suggest that trusted and social-aware direct connectivity has the potential to decisively augment network performance. We conclude by outlining the future perspectives of its development across the research and standardization sectors.
mcMTC is starting to play a central role in the industrial Internet of Things ecosystem and have the potential to create high-revenue businesses, including intelligent transportation systems, energy/ smart grid control, public safety services, and high-end wearable applications. Consequently, in the 5G of wireless networks, mcMTC have imposed a wide range of requirements on the enabling technology, such as low power, high reliability, and low latency connectivity. Recognizing these challenges, the recent and ongoing releases of LTE systems incorporate support for low-cost and enhanced coverage, reduced latency, and high reliability for devices at varying levels of mobility. In this article, we examine the effects of heterogeneous user and device mobility - produced by a mixture of various mobility patterns - on the performance of mcMTC across three representative scenarios within a multi-connectivity 5G network. We establish that the availability of alternative connectivity options, such as D2D links and drone-assisted access, helps meet the requirements of mcMTC applications in a wide range of scenarios, including industrial automation, vehicular connectivity, and urban communications. In particular, we confirm improvements of up to 40 percent in link availability and reliability with the use of proximate connections on top of the cellular-only baseline.
The spectrum of millimeter waves, when properly exploited, represents an important asset for achieving the high data rates and low latencies required by applications in vehicular communications. However, vehicle scenarios are characterized by high mobility, which results in frequent misalignment of beams. Therefore, in these types of scenarios, beam tracking algorithms are important because they can keep the beams aligned with a low training overhead. Kalman filters are strong candidates for the implementation of such algorithms, because they ensure high channel tracking performance over a wide range of signal-to-noise-ratios (SNR) and are easy to implement. This work evaluates the performance of channel tracking methods based on Kalman filters for high mobility. Our numerical results show that the proposed Kalman filter-based channel tracking method has high performance at low SNR regimes compared to least square-based methods, and improve the robustness when using planar instead of linear arrays. Moreover, the proposed channel tracking method is shown to perform well in multipath fading scenarios, while achieving high performance in the presence of strong line-of-sight components.
When UMTS is part of IP end-to-end communication, there must exist means for UMTS to be able to provide the required Quality of Service (QoS) for applications running over IP. Hence there is a need for a translation function for translation between IP QoS parameters and UMTS QoS attributes. This translation is not trivial because of several reasons. First, the number of QoS parameters in the IP level and the UMTS level are different. Second, definitions of parameters at the two levels are different. Keeping these factors in view, the present invention provides for a method for translation of IP QoS parameters to UMTS QoS attributes, and another method for translation of UMTS QoS attributes to IP QoS parameters. This translation will enable spectrum efficient UMTS bearers to be set up for applications running over IP. This will also make negotiation of services possible between an entity at the IP level and the UMTS network. These methods are placed in both the User Equipment as well as the Gateway of the UMTS network.
To meet the prospective demands of intelligent transportation systems (ITS), the Release 14 (Rel-14) and Rel-15 of the Long Term Evolution (LTE) specifications include solutions for enhanced vehicle-to-everything (V2X) communications. While the technical enablers of Rel-14 are suitable for delivering basic safety messages, Rel-15 supports more demanding ITS services with stringent latency and reliability. Starting in Rel-15 and continuing in Rel-16, the 3GPP was developing a novel radio interface for 5G systems, termed the New Radio (NR), which will enable ultra reliable and low latency communications suitable even for the most demanding ITS applications. In this paper, we overview the new V2X-specific features in Rel-15 and Rel-16. Further, we argue that future V2X and automotive radar systems may reuse common equipment, such as millimeter-wave antenna arrays. We finally discuss the vision of joint vehicular communications and radar sensing as well as characterize unified channel access for millimeter-wave vehicular communications and radar sensing.
Future smart vehicles will incorporate high-data-rate communications and high-resolution radar sensing capabilities operating in the millimeter-wave and higher frequencies. These two systems are preparing to share and reuse many common functionalities, such as steerable millimeter-wave antenna arrays. Motivated by this growing overlap, which is advanced further by space and cost constraints, the vehicular community is pursuing a vision of unified vehicular communications and radar sensing that represents a major paradigm shift for next-generation connected and self-driving cars. This article outlines a path to materialize this decisive transformation. We begin by reviewing the latest developments in hybrid vehicular communications and radar systems, and then propose a concept of unified channel access over millimeter-wave and higher frequencies. Our supporting system-level performance characterization relies upon real-life measurements and extensive ray-based modeling to confirm the significant improvements brought by our proposal to mitigating the interference and deafness effects. Since our results aim to open the door to unified vehicular communications and radar sensing, we conclude by outlining the potential research directions in this rapidly developing field.
While the IoT has made significant progress supporting individual machine-type applications, it is only recently that the importance of people as an integral component of the overall IoT infrastructure has started to be fully recognized. Several powerful concepts have emerged to facilitate this vision, whether involving the human context whenever required or directly impacting user behavior and decisions. As these become the stepping stones to develop the IoT into a novel people-centric utility, this article outlines a path to realize this decisive transformation. We begin by reviewing the latest progress in human-aware wireless networking, then classify the attractive human-machine applications and summarize the enabling IoT radio technologies. We continue with a unique system-level performance characterization of a representative urban IoT scenario and quantify the benefits of keeping people in the loop on various levels. Our comprehensive numerical results confirm the significant gains that have been made available with tighter user involvement, and also corroborate the development of efficient incentivization mechanisms, thereby opening the door to future commoditization of the global people-centric IoT utility.
In the paper, we consider the problem of routing and bandwidth allocation in networks that support elastic traffic. We assume that the bandwidth demand between each source-destination (S-D) pair is specified in terms of a minimum and maximum value, and a set of flows between each S-D pair is allowed to realize these demands. (We say that a set of flows realizes the demand associated with an S-D pair, if the sum of the bandwidths allocated to these flows is greater than the minimum value assumed for the demand of that S-D pair). In this setting, we show that routing and bandwidth allocation can be formulated as an optimization problem, where network utilization is to be maximized under capacity and the widely used max-min fairness constraints. We describe three different algorithms to solve variants of this problem. The most important one, an efficient, original algorithm assuming multipath routing is studied in detail and illustrated with a numerical example.
Device-to-device (D2D) communication has the potential of increasing the system capacity, energy efficiency and achievable peak rates while reducing the end-to-end latency. To realize these gains, recent works have proposed resource allocation (RA) and power control (PC) approaches that show near optimal performance in terms of spectral or energy efficiency. However, the proposed schemes either consider a single cell environment or assume instantaneous channel state information (CSI) and/or rely on iterative algorithms that require excessive inter-node message exchange and suffer from slow convergence time. For D2D user equipment (UE), we propose a distributed utility optimization based PC scheme that relies on locally available measurement data and is made practical by constraining the number of iterations and the interference caused to the cellular receiver, while legacy UEs employ the standard Long Term Evolution (LTE) PC. We investigate the performance of the proposed PC scheme when combined with two RA schemes that differ in terms of the required channel state information. We find that when properly tuned, this practical PC scheme combined with a RA algorithm that requires limited channel knowledge, not only shows near optimal performance, but it also constraints the impact of D2D communications on the cellular layer.
Cellular network assisted Device-to-Device (D2D) communication has the potential to increase the network capacity, offload access and core network resources and reduce latency. To realize these potential gains and to ensure a win-win type of coexistence between the cellular and the D2D layer, there is a need to carefully design the procedures for radio resource management (RRM). This paper develops and evaluates low complexity radio resource management (RRM) algorithms that are based on practically feasible and well known measurements. These RRM algorithms include mode selection, power control, and resource allocation. First, the network assists D2D users on a coarse time scale to select D2D (direct) mode or cellular mode. Subsequently, the network informs the D2D users of tolerable power levels which cause minimal interference to the base station, and the possible resources that can be used for D2D communications. Based on this information, the D2D users act autonomously for executing the RRM functions. The simulation result shows that our approach to D2D RRM can harvest the offloading/proximity gain to the network.
Device-to-device (D2D) communications underlaying a cellular infrastructure has recently been proposed as a means of increasing the resource utilization, improving the user throughput and extending the battery lifetime of user equipments. In this article we propose a new distributed power control algorithm that iteratively determines the signal-to-noise-and-interference-ratio (SINR) targets in a mixed cellular and D2D environment and allocates transmit powers such that the overall power consumption is minimized subject to a sum-rate constraint. The performance of the distributed power control algorithm is benchmarked with respect to the optimal SINR target setting that we obtain using the Augmented Lagrangian Penalty Function method. The proposed scheme shows consistently near optimum performance both in a single-input-multiple-output and a multiple-input-multiple-output setting. We also propose a joint power control and mode selection algorithm that requires single cell information only and clearly outperforms the classical cellular mode operation.
Transmit antenna diversity and single user spatial multiplexing have become attractive in practical systems, because they achieve performance gains without requiring sophisticated channel state information (CSI) feedback mechanisms. On the other hand, when fast and accurate CSI at the transmitter is available, opportunistic power control (OPC) is an attractive alternative to signal-to-interference-and-noise ratio (SINR) target following approaches, because it maximizes throughput by taking advantage of fast channel variations. In this paper we examine the question whether OPC is worth the pain of obtaining fast CSI by evaluating the gains of OPC for the downlink of a system employing multiple input multiple output (MIMO) systems with Alamouti and open loop spatial multiplexing (SM). We formulate the OPC problem as a throughput maximization task subject to power budget and fairness constraints. We solve this task by the Augmented Lagrangian Penalty Function and find that without fairness constraints, OPC in concert with SM provides superior throughput. With increasingly tight fairness constraints, Alamouti along with equal power allocation becomes a viable alternative to the SM OPC scheme. Both from fairness and throughput perspectives, Alamouti along with OPC is particularly efficient when adaptive MCS is employed and users with large differences in channel qualities have to share the total transmit power.
Recently, tight network coordination in cellular systems has been demonstrated to improve the spectrum efficiency by means of signal processing methods. However, the performance of signal processing based multi-cell coordination is sensitive to backhaul delays, channel estimation errors and imperfections in fast link control. In this paper we consider tight network coordination for fast radio resource management (RRM) including packet scheduling, power control and modulation and coding scheme selection. We use a system level simulator to analyze the uplink performance of a multi-cell coordinated system that is built around a fast backhaul transport infrastructure for the purpose of enabling coordinated RRM rather than coordinated signal processing. We find that coordinated RRM alone can provide significant performance gains, up to 50% for cell edge and cell capacity as compared to traditional single-cell configurations and that multi-cell fast power control and modulation and coding scheme selection can significantly improve the accuracy of link adaptation in terms of signal-to-interference-and-noise (SINR) distribution, while imposing lower demands on the capacities of backhaul links compared to coordinated signal processing. Therefore RRM coordination can be an efficient complement to coordinated signal processing in multi-cell coordinated clusters.