We developed a cross-layer design which combines adaptive modulation and coding at the physical layer with truncated automatic repeat request protocol data link layer, in order to maximize spectral efficiency under prescribed delay error performance constraints. derive achieved closed-form for transmissions over Nakagami-m block fading channels. Numerical results reveal that retransmissions relieve stringent control requirements thereby enable considerable gain. This gain is comparable...

Consider a codebook containing N unit-norm complex vectors in K-dimensional space. In number of applications, the that minimizes maximal cross-correlation amplitude (I/sub max/) is often desirable. Relying on tools from combinatorial theory, we construct analytically optimal codebooks meeting, certain cases, Welch lower bound. When analytical constructions are not available, develop an efficient numerical search method based generalized Lloyd algorithm, which leads to considerable...

Merging mobile edge computing (MEC) functionality with the dense deployment of base stations (BSs) provides enormous benefits such as a real proximity, low latency access to resources. However, envisioned integration creates many new challenges, among which mobility management (MM) is critical one. Simply applying existing radio access-oriented MM schemes leads poor performance mainly due co-provisioning and services MEC-enabled BSs. In this paper, we develop novel user-centric energy-aware...

The (ultra-)dense deployment of small-cell base stations (SBSs) endowed with cloud-like computing functionalities paves the way for pervasive mobile edge computing, enabling ultra-low latency and location-awareness a variety emerging applications Internet Things. To handle spatially uneven computation workloads in network, cooperation among SBSs via workload peer offloading is essential to avoid large at overloaded provide high quality service end users. However, performing effective faces...

The vehicular edge computing system integrates the resources of vehicles, and provides services for other vehicles pedestrians with task offloading. However, offloading environment is dynamic uncertain, fast varying network topologies, wireless channel states, workloads. These uncertainties bring extra challenges to In this paper, we consider among propose a solution that enables learn delay performance their neighboring while computation tasks. We design an adaptive learning based (ALTO)...

In federated learning (FL), devices contribute to the global training by uploading their local model updates via wireless channels. Due limited computation and communication resources, device scheduling is crucial convergence rate of FL. this paper, we propose a joint resource allocation policy maximize accuracy within given total time budget for latency constrained A lower bound on reciprocal performance loss, in terms number rounds scheduled per round, derived. Based bound, maximization...

Modeling and simulation of a cellular network typically assumes that the target area is divided into regular hexagonal cells mobile stations (MSs) are uniformly scattered in each cell. This implies statistically uniform distribution traffic load over space, but reality spatial highly non-uniform across different cells, which calls for actual models. In this article, we first present analysis measurements collected from commercial networks China, demonstrate density (the per unit area) can be...

Owing to the increasing need for massive data analysis and model training at network edge, as well rising concerns about privacy, a new distributed framework called federated learning (FL) has emerged. In each iteration of FL (called round), edge devices update local models based on their own contribute global by uploading updates via wireless channels. Due limited spectrum resources, only portion can be scheduled in round. While most existing work scheduling focuses convergence w.r.t....

Relative to designs assuming no channel knowledge at the transmitter, considerably improved communications become possible when adapting transmitter intended propagation channel. As perfect is rarely available, based on partial (statistical) state information (CSI) are of paramount importance not only because they more practical but also encompass perfect- and no-knowledge paradigms. In this paper, we first provide a CSI model for orthogonal frequency division multiplexed (OFDM)...

Adaptive modulation has the potential to increase system throughput significantly by matching transmitter parameters time-varying channel conditions. However, adaptive schemes that rely on perfect state information (CSI) are sensitive CSI imperfections induced estimation errors and feedback delays. In this paper, we design for multiantenna transmissions based partial CSI, models spatial fading channels as Gaussian random variables with nonzero mean white covariance, conditioned information....

In this paper, a simple and elegant geometric water-filling (GWF) approach is proposed to solve the unweighted weighted radio resource allocation problems. Unlike conventional (CWF) algorithm, we eliminate step find water level through solving non-linear system from Karush-Kuhn-Tucker conditions of target problem. The GWF requires less computation than CWF under same memory requirement sorted parameters. Furthermore, avoids complicated derivation, such as derivative or gradient operations in...

We consider energy-efficient wireless resource management in cellular networks where BSs are equipped with energy harvesting devices, using statistical information for traffic intensity and harvested energy. The problem is formulated as adapting BSs' on-off states, active blocks (e.g. subcarriers) well power allocation to minimize the average grid consumption a given time period while satisfying users' quality of service (blocking probability) requirements. It transformed into an...

In this paper, the optimal BS (Base Station) density for both homogeneous and heterogeneous cellular networks to minimize network energy cost is analyzed with stochastic geometry theory. For networks, upper lower bounds of are derived. our analysis reveals best type BSs be deployed capacity extension, or switched off saving. Specifically, if ratio between micro macro than a threshold, which function path loss their transmit power, then strategy deploy extension switch (if possible) saving...

In this paper, traffic-aware sleeping control (SC) and power matching (PM) of a single base station (BS) in cellular networks are studied. The objective is to find the configurations that achieve Pareto optimal tradeoff between total consumption average delay. Two types schemes considered: BS goes sleep whenever there no active user, wakes up when N users assembled or after period multiple vacation time. We first discuss incorporate into energy efficiently. explicit relationship delay with...

With the proliferation of mobile applications, Mobile Cloud Computing (MCC) has been proposed to help devices save energy and improve computation performance. To further quality service (QoS) MCC, cloud servers can be deployed locally so that latency is decreased. However, computational resource local generally limited. In this paper, we design a threshold-based policy QoS MCC by cooperation Internet resources, which takes advantages low abundant resources simultaneously. This also applies...

The explosive growth of mobile multimedia traffic calls for scalable wireless access with high quality service and low energy cost. Motivated by the emerging harvesting communications, trend caching contents at edge user terminals, we propose a paradigm shifting framework, GreenDelivery, enabling efficient content delivery based small cells. To resolve two-dimensional randomness request arrivals, proactive push are jointly optimized, respect to popularity distribution battery states. We thus...

Space-air-ground integrated networks (SAGIN) extend the capability of wireless and will be essential building block for many advanced applications, like autonomous driving, earth monitoring, etc. However, coordinating heterogeneous physical resources is very challenging in such a large-scale dynamic network. In this paper, we propose reconfigurable service provisioning framework based on function chaining (SFC) SAGIN. SFC, network functions are virtualized data needs to flow through specific...

Federated learning (FL) enables workers to learn a model collaboratively by using their local data, with the help of parameter server (PS) for global aggregation. The high communication cost periodic updates and nonindependent identically distributed (i.i.d.) data become major bottlenecks FL. In this work, we consider analog aggregation scale down respect number workers, introduce redundancy system deal non-i.i.d. data. We propose an online energy-aware dynamic worker scheduling policy,...

Mobile edge computing is a novel technique in which mobile devices offload computation-intensive tasks with stringent delay requirements to the cloud. However, limited computational resource cloud may result Quality of Service degradation. In this paper, we address issue by coordinating heterogeneous includes and remote Considering offloading delay-bounded tasks, study into scheduling order maximize probability that can have met. The problem formulation proved be concave, an optimal...

This paper considers the power allocation of a single-link wireless communication with joint energy harvesting and grid supply. We formulate problem as minimizing consumption random data arrival in fading channel, analyze structure optimal policy some special cases. For case that all packets are arrived before transmission, it is dual throughput maximization, solution found by two-stage water filling (WF) policy, which allocates harvested first stage, then second stage. case, we assume or...

Timely status updates are crucial to enabling applications in the massive Internet of Things (IoT). This paper measures data-freshness performance a update system with an energy-harvesting transmitter, considering randomness information generation, transmission, and energy harvesting. The is evaluated by non-linear function age (AoI) that defined as time elapsed since generation most up-to-date at receiver. formulated two queues packet arrivals both assumed be Poisson processes. With...

In a typical Internet of Things (IoT) application where central controller collects status updates from multiple terminals, e.g., sensors and monitors, through wireless multiaccess uplink, an important problem is how to attain timely autonomously. this paper, the timeliness measured by recently proposed age-of-information (AoI) metric; both theoretical practical aspects are investigated: we aim obtain scheduling policy with minimum AoI and, meanwhile, requires little signaling exchange...

In an Internet-of-Things system where status data are collected from sensors and actuators for time-critical applications, the freshness of is vital can be quantified by recently proposed age-of-information (AoI) metric. this paper, we first consider a general scenario multiple terminals share common channel to transmit or receive randomly generated packets. The optimal scheduling problem minimize AoI formulated as restless multi-armed bandit problem. To solve efficiently, derive Whittle's...

We consider a star-topology wireless network for status update where central node collects data from large number of distributed machine-type terminals that share medium. The Age Information (AoI) minimization scheduling problem is formulated by the restless multi-armed bandit. A widely-proven near-optimal solution, i.e., Whittle's index, derived in closed-form and corresponding indexability established. index then generalized to incorporate stochastic, periodic packet arrivals unreliable...