The increasing demands of computationally intensive device applications are driving advancements in edge technologies and the need for improved computation offloading policies. This paper focuses on “adaptive” offloading and computation, i.e., adapting the amount of offload data and, consequently, the associated compute adaptive job's quality to the wireless channel quality, network congestion, and the compute adaptive job's computational options. For example, when the channel quality is poor and a job has a tight deadline, the amount of offloaded data can be reduced in exchange for a loss in the associated compute adaptive job's quality. In this paper, we show the substantial advantages of adapting the amount of offloaded data to channel quality and network congestion. We begin by defining a reward model for compute adaptive jobs based on the amount of offloaded data and resulting computation quality. We then develop an upper bound on the achievable revenue rate and propose/compare various offloading policies: Greedy, Predictive Abandonment (PA), Probabilistic Admission Control and Layer Assignment (PACLA), and combinations thereof. We evaluate our policies via simulation and observe that the combination of PACLA + PA provides the best offloading performance for homogeneous or heterogeneous compute adaptive jobs for devices with varied channel qualities.

Increasing demand for computationally intensive jobs on mobile devices is driving interest in computation offloading to the edge/cloud servers. This paper presents a comprehensive framework for managing offloading of stochastic and heterogeneous user(s)-generated jobs while considering job deadlines and congestion on wireless channels and edge/cloud servers. The goal of offloading is to maximize either the net computational work offloaded or power savings. We propose a class of policies called Predictive Abandonment (PA), where users opportunistically cut and offload jobs but abandon offloading if they predict that communication and computation delays will preclude on-time completion. Although these user-driven policies are desirable from an implementation perspective and achieve relatively good performance, they cannot coordinate tradeoffs amongst users with heterogeneous job types. To address this, we propose a complementary approach to coordinate offloading based on Probabilistic Admission Control and Cut Assignment (PACCA). When combined with PA, it delivers significant offloading benefits. We also develop an upper bound on the benefits of offloading, which can serve as a baseline for evaluating the additional gains of more complex offloading policies. We evaluate these policies via simulation for a range of loads and job profiles, demonstrating robust gains over a naive greedy offloading policy and near-optimal performance in some settings. Furthermore, we assess the robustness of PACCA + PA to imperfect knowledge of offered job rates.

Millimetre wave (mmWave) communication is a promising technology which can fulfil the growing demands for spectrum for future wireless networks. One of the key areas for the development of the mmWave networks is the Internet of Things (IoT) communications within fifth generation (5G) and beyond 5G networks. For significant analysis and development of the compliant IoT systems through testbed implementation, current mmWave spectrum transceivers are too expensive when substantial number of the nodes is required by the IoT applications. Considering all the above, it is suggested to use Software Defined Radio (SDR) transceivers with a lower frequency band and with an increased distance between the nodes. The idea is to scale observation time and distance to emulate mmWave radio without actual mmWave hardware. Using scaling factors for the certain system parameters to keep the signal characteristics in accordance with the mmWave band makes it possible. This approach allows to develop mmWave IoT testbeds with significant improvement in the system scalability and cost-effectiveness without the need to transmit and receive the signal in the mmWave band. In this paper, the concept of SDR-based Hardware-in-the-loop (HIL) system combined with the observation time and distance scaling approach is proposed. As an example, a testbed with a simple Wireless Physical Network Coding scheme is implemented and demonstrated.

Modern mobile handheld devices, such as smartphones and tablets, feature multiple wireless interfaces, some of which can support device-to-device communications, which enable mesh networks on even when the infrastructure is unavailable. One of the key technological challenges hampering the use of multi-hop mesh networks is the extremely high communication overhead of route discovery and maintenance algorithms. The problem is especially pronounced under dynamic network conditions caused by user mobility and nodes joining and leaving the network. In this paper, we propose a fully distributed algorithm for constructing a virtual coordinate system used for geo-like routing by approximating the physical network nodes coordinate. The proposed algorithm, called gradient assisted routing (GAR), builds upon two-hop neighbors’ information exchanged in beacons in contrast to conventional geographic routing protocols which rely on external positioning information. We evaluate the proposed solution using algorithmic, topological, and routing-related metrics of interest. We further numerically quantify how the node mobility increases the time needed for topology stabilization, and how network size affects the route discovery success rate. Our comparison also shows that for small to mid-size mesh networks (up to 60 nodes), the performance of the proposed routing procedure is similar to the conventional geographic routing protocols that exploit external positioning information. The proposed solution may efficiently supplement the traditional on-demand routing in small to mid-size mesh systems by independently establishing 50 to 70% of paths and thereby reducing the discovery overheads.

Millimeter wave (mmWave) communication is a promising technology to fulfill the requirements of future wireless networks. It provides very large spectrum and a large number of antennas can be practicable due to the small wavelength to exploit the array gain. However, there are several challenges, restricting the utilization of mmWave, such as hardware complexity and power consumption. To overcome these challenges, hybrid analog/digital architecture providing lower dimensional beamspace multiple input multiple output (MIMO) system is used. For the hybrid architecture, beam selection techniques exploiting the sparse nature of the mmWave channel become significant. In this paper, we consider a downlink mmWave communication when the large number of antenna is utilized at the base station. For that system, we propose a beam selection and a correlation based user selection algorithms to maximize the sum data rate.

A diversity of wireless technologies will collaborate to support the fifth‐generation (5G) communication networks with their demanding applications and services. Despite decisive progress in many enabling solutions, next‐generation cellular deployments may still suffer from a glaring lack of bandwidth due to inefficient utilization of radio spectrum, which calls for immediate action. To this end, several capable frameworks have recently emerged to all help the mobile network operators (MNOs) leverage the abundant frequency bands that are utilized lightly by other incumbents. Along these lines, the recent Licensed Shared Access (LSA) regulatory framework allows for controlled sharing of spectrum between an incumbent and a licensee, such as the MNO, which coexist geographically. This powerful concept has been subject to several early technology demonstrations that confirm its implementation feasibility. However, the full potential of LSA‐based spectrum management can only become available if it is empowered to operate dynamically and at high space‐time‐frequency granularity. Complementing the prior efforts, we in this work outline the functionality that is required by the LSA system to achieve the much needed flexible operation as well as report on the results of our respective live trial that employs a full‐fledged commercial‐grade cellular network deployment. Our practical results become instrumental to facilitate more dynamic bandwidth sharing and thus promise to advance on the degrees of spectrum utilization in future 5G systems without compromising the service quality of their users.

As next-generation mobile networks are rapidly taking shape driven by the target standardization requirements and initial trial implementations, a range of accompanying technologies prepare to support them with more reliable wireless access and improved service provisioning. Among these are more advanced spectrum sharing options enabled by the emerging Licensed Shared Access (LSA) regulatory framework, which aims to efficiently employ the capacity of underutilized frequency bands in a controlled manner. The concept of LSA promises to equip network operators with the much needed additional spectrum on the secondary basis and thus brings changes to the existing cellular network management. Hence, additional research is in prompt demand to determine the required levels of Quality of Service (QoS) and service provisioning reliability, especially in cases of dynamic geographical and temporal LSA sharing. Motivated by this recent urge and having at our disposal a fully-functional 3GPP LTE cellular deployment, we have committed to implement and trial the principles of dynamic LSA-compatible spectrum management. This paper is our first disclosure on the comprehensive experimental evaluation of this promising technology. We expect that these unprecedented practical results together with the key lessons learned will become a valuable reference point for the subsequent integration of flexible LSA-based services, suitable for inter-operator and multi-tenant spectrum sharing.

The stochastic channel models typically abstract away the details of the paths that carry energy in the radio channel. While these have been universally acceptable for decades due to their ease of use and reasonable accuracy in most practical cases, the appearance of steerable, narrow-beam antennas in mmWave bands makes the exact path information very valuable, primarily for beam tracking algorithms. Currently, only deterministic channel modeling (e.g. ray tracing) provides the required level of details, but at prohibitive computing cost. This limits the study and design environments for such algorithms to the confines of existing ray tracing data, which is bulky and rarely available for free. In this paper, we consider an approach to stochastic channel modeling that allows to achieve the level of details equivalent to ray tracing, but at a fraction of the computing costs. The proposed approach may be immediately applied to any system operating at 20-100 GHz. It allows the researchers and engineers to perform quick testing of elaborate mmWave MAC and PHY algorithms with a system-level simulation, without having to obtain exhaustive measurement or ray tracing data.

The emerging fifth-generation (5G) wireless technology will need to harness the massively unused millimeter-wave (mmWave) spectrum to meet the projected acceleration in mobile traffic demand. Today, the available range of mmWave-based solutions is already represented by IEEE 802.11ad (WiGig), IEEE 802.15.3c, WirelessHD, and ECMA-387 standards, with more to come in the following years. As the key performance-related aspects of these enabling technologies are rapidly taking shape, the primary research challenge shifts to characterizing network energy efficiency, among other system-level parameters. This is particularly important in scenarios that are not handled by current 4G communication networks, including congested public places, homes, and offices. In these dense deployments, wireless wearable devices are increasingly proliferating to assist in diverse user needs. However, mmWave operation in crowded environments, and especially for multiple neighboring personal networks, is not nearly well-understood. Bridging this gap, we conduct a full-fledged energy efficiency assessment of mmWave-based “high-end” wearables that employ advanced antenna beamforming techniques. Our rigorous analytical results shed light on the underlying scaling laws for the interacting mmWave-based networks based on IEEE 802.11ad and quantify the impact of beamforming quality on system energy efficiency under various conditions. Furthermore, we look at the system optimization potential subject to realistic hardware capabilities.

For the past years, the analysts have been predicting a tremendous and continuous increase in mobile traffic, causing much of industry and academia to seek out any and all methods to increase wireless network capacity. In this paper, we investigate one such method, cellular data offloading onto direct connections between proximate user devices, which has been shown to provide significant wireless capacity gains. To do so, we formulate a new system model that couples a cellular network in licensed bands and a device-to-device (D2D) network in unlicensed bands. We propose that devices be continually associated with the cellular base station and use this connectivity to help manage their direct connections in unlicensed spectrum. In particular, we demonstrate that assisted offloading of cellular user sessions onto the D2D links improves the degree of spatial reuse and reduces the impact of interference. In this study, a session is a real-time flow of data from one user to another, which adheres to a Poisson point process (PPP). By contrast to a throughput- or capacity-centric system view, the application of PPP enables formulations where entire user sessions, rather than singular data packets, are arriving at random and leaving the system after being served. The proposed methodology is flexible enough to accommodate practical offloading scenarios, network selection algorithms, quality of service measures, and advanced wireless technologies. In this study, we are primarily interested in evaluating the data session blocking probability in dynamically loaded cellular and D2D networks, but given the importance of energy efficiency for mobile devices, we are also interested in characterizing the energy expenditure of a typical data session in these different networks. First with our advanced analytical methodology and then with our detailed system-level simulator, we evaluate the performance of network-assisted data session offloading from cellular to D2D connections under a variety of conditions. This analysis represents a useful tool in the development of practical offloading schemes and ongoing standardization efforts.

The ongoing densification of small cells yields an unprecedented paradigm shift in user experience and network design. The most notable change comes from cellular rates being comparable to next-generation WiFi systems. Cellular-to-WiFi offloading, the standard modus operandi of recent years, is therefore shifting towards a true integration of both technology families. Users in future 5G systems will thus likely be able to use 3GPP, IEEE, and other technologies simultaneously, so as to maximize their quality of experience. To advance this high-level vision, we perform a novel performance analysis specifically taking the system-level dynamics into account and thus giving a true account on the uplink performance gains of an integrated multi radio access technology (RAT) solution versus legacy approaches. Further, we advocate for an enabling architecture that embodies the tight interaction between the different RATs, as we lay out a standardization roadmap able to materialize the envisaged design. 3GPP-compliant simulations have also been carried out to corroborate the rigorous mathematical analysis and the superiority of the proposed approach.

In next-generation wireless networks, device-to-device (D2D) communication represents a feasible way for mobile users to offload their cellular traffic demand without extra costs for deploying additional infrastructure from the network operators. Cellular (e.g., 3GPP LTE) network assistance can automate user/service discovery and connection establishment procedures, as well as enable secure D2D connectivity between proximate users. Currently, assisted direct connectivity is only available in the form of unlicensed-band protocols (e.g., WiFi Direct), which motivates research on understanding its practical limitations with realistic distributions of users and content. Whereas there are concerns that D2D communication alone may not be efficient due to limited content availability, in this paper, we advocate the use of network coding to upgrade assisted proximate communication and make it realize its full potential. In particular, we demonstrate that even simpler network coding techniques are capable to significantly improve the degrees of content availability for communicating users and thus enhance offloading performance under realistic constraints. Inspired by the recent popularity of wireless content distribution systems over D2D caches, we contribute a practical methodology for assisted data caching and distribution, mindful of the state-of-the-art D2D technology.

Currently, cellular operators are struggling to relieve congestion on their networks in the face of rapidly growing mobile data traffic. While deploying an increasing number of base stations is expected to mitigate the disproportion between user demand and available radio resources, this solution is costly and plagued with many practical challenges. An attractive alternative is to enable cellular traffic offloading onto device-to-device (D2D) connections in the unlicensed bands, as current multi-radio user devices are already capable of establishing concurrent LTE and WiFi links. However, WiFi lacks a fast, efficient method of device/service discovery, and it is not equipped to efficiently manage numerous D2D connections. In our research, we have found that a limited amount of network assistance for D2D communications can overcome these limitations; and in this paper we describe our network-assisted D2D technology prototype. Specifically, we outline a complete standards-compliant solution that provides a seamless D2D connectivity experience to the end user. Our solution utilizes WiFi Direct as the link-layer technology for proximal D2D connections. However, the challenges faced during the design phase are universal to all D2D link-layer protocols, thus the proposed solutions are applicable to other potential D2D technologies.

Analysts predict explosive growth in traffic demand on mobile broadband systems over the coming years due to the popularity of streaming video, gaming, and other social media services. While 4G wireless technologies are making a significant effort to keep up with this demand, the expectation is that cellular deployments will fall short of the required capacity unless there is a dramatic shift towards smaller cells. There is already significant interest in femto- and pico-cell deployments for this reason. However, there is another method of creating small cells that the wireless industry has yet to capitalize on, namely direct connectivity between clients in close proximity. 3GPP is currently working to enable device-to-device (D2D) communications within Release 12 of LTE-Advanced. By comparison, IEEE has already defined a D2D communications protocol, termed WiFi Direct, which is based on the 802.11 standards. WiFi Direct not only serves to offload user data onto direct links, but does so using the unlicensed bands. To benefit users further, WiFi Direct can be enhanced by enabling the LTE network to assist during peer discovery and direct connection establishment. In this paper, we discuss the network/client requirements and performance benefits of network-assisted WiFi Direct. We assume that clients are continuously under management by the LTE network, which assists them with service/peer discovery and direct connection establishment. We show that network-assisted WiFi Direct can significantly improve the performance of proximal applications and reduce the power consumed by the clients involved, while also improving capacity of the LTE network.

Growing demand for bandwidth dictates the use of smaller wireless cells, which results in increased inter-cell interference. In most contemporary cellular systems, the clients at the cell edge typically use higher transmission power to compensate for increasing path loss and fading and thus generate the most interference. Client relay is believed to be a promising technique to enhance the performance of cell-edge users by allowing them to exploit other users as relay nodes and thus transmit with less power. In this paper, authors conduct in-depth system-level evaluation of client relay technique in state-of-the-art wireless cellular networks. Several important scenarios are considered, including opportunistic client relay behavior and various channel models. It is demonstrated that client cooperation may considerably improve system performance in terms of cell-edge spectral efficiency for the cost of some increase in cell-center energy consumption.