Achieving ultra-reliable low-latency communications (URLLC) is critical for the operation of data-intensive applications and for ensuring seamless connectivity. Millimeter-wave (mmWave) technology is expected to support URLLC by expanding the available spectrum and providing multi-gigabit services. However, a well-recognized challenge is that mmWave communication links are susceptible to blockage, which may lead to communication disruptions. Conventional approaches, such as interleaving and feedback mechanisms provide resilience against such blockages at the cost of incurring additional delay, which may be too large to support URLLC effectively. This calls for novel techniques to develop resilient transmission mechanisms that can support URLLC. This paper develops gracefully resilient transmission mechanisms by deploying multilevel codes over space and over time. These codes allow the control of the received information and they accommodate different quality of service requirements of different information streams. Our evaluations, carried out also within the ns-3 network simulator, show that deploying these codes leads to attractive trade-offs between rate, delay, and outage probability.

Millimeter-wave (mmWave) spectrum is expected to support data-intensive applications that require ultra-reliable low-latency communications (URLLC). However, mmWave links are highly sensitive to blockage, which may lead to disruptions in the communication. Traditional techniques that build resilience against such blockages (among which are interleaving and feed-back mechanisms) incur delays that are too large to effectively support URLLC. This calls for novel techniques that ensure resilient URLLC. In this paper, we propose to deploy multilevel codes over space and over time. These codes offer several benefits, such as they allow to control what information is received and they provide different reliability guarantees for different information streams based on their priority. We also show that deploying these codes leads to attractive trade-offs between rate, delay, and outage probability. A practically-relevant aspect of the proposed technique is that it offers resilience while incurring a low operational complexity.

Industrial Internet of Things (IIoT) use cases have stringent reliability and latency requirements to enable real-time wireless control systems, which are supported by the 5G ultra-reliable low-latency communications (URLLC). However, extremely high quality-of-service (QoS) requirements in 5G URLLC causes huge radio resource consumption and low spectral efficiency, thus limiting network capacity in terms of the number of supported devices. Industrial control applications typically incorporate redundancy in their design and may not always require extreme QoS to achieve the expected control performance. Therefore, we propose both communication-control co-design and dynamic QoS to address the capacity issue for robotic manipulation use cases in 5G-based IIoT. We have developed an advanced co-simulation framework that includes a network simulator, physics simulator, and compute emulator, for realistic performance evaluation of the proposed methods. Through simulations, we show significant improvements in network capacity (i.e., the number of supported URLLC devices), and about 2x gain for the robotic manipulation use case.

Efficient radio resource allocation is a fundamental optimization problem for wireless networks, and has been widely studied in the past. However, wireless systems are evolving to have a much larger parameter space along with richer set of applications and user requirements leading to significant increase in complexity. This paper draws from recent breakthroughs in applying deep reinforcement learning (RL) for control problems containing large state space dimensionality. In particular, a deep RL approach is explored for the problem of allocating time and frequency resources in OFDMA wireless systems to optimize different objective functions using per-station channel quality and traffic information as inputs. Such approaches hold the potential for agents to learn resource allocation and scheduling policies directly from experience rather than using carefully crafted heuristic algorithms based upon models of the environment and stations. Learning directly from experience also means that the policies that result from the online learning should be more robust to imperfect inputs such as noisy, delayed or missing information compared to model-based heuristic approaches. The results in this paper show promise for a deep RL agent using a policy gradient algorithm to learn policies that approach or exceed the performance of well-known model-based approaches such as max-weight and proportional fair policies. The online adaptation algorithms used for the deep RL agent also demonstrate reasonable adaptability and robustness to varying traffic conditions.

In this paper, we propose a learning-based low-overhead channel estimation method for coordinated beamforming in ultra-dense networks. We first show through simulation that the channel state information (CSI) of geographically separated base stations (BSs) exhibits strong non-linear correlations in terms of mutual information. This finding enables us to adopt a novel learning-based approach to remotely infer the quality of different beamforming patterns at a dense-layer BS based on the CSI of an umbrella control-layer BS. The proposed scheme can reduce channel acquisition overhead by replacing pilot-aided channel estimation with the online inference from an artificial neural network, which is fitted offline. Moreover, we propose to use more anchor points and more candidate beam patterns to obtain better performance. Simulation results based on stochastic ray-tracing channel models show that the proposed scheme can reach an accuracy of 99.74\% in settings with 20 beamforming patterns.

As new iterations of more powerful and better connected smartphones emerge, their limited battery life remains a leading factor adversely affecting the mobile experience of millions of smartphone users. While it is well-known that many apps can drain battery even while running in background, there has not been any study that quantifies the extent and severity of such background energy drain for users in the wild. To extend battery life, various new features are being incorporated within the phone, one of them being preventing applications from running in background, i.e., when the screen is off, but their impact is largely unknown. This paper makes several contributions. First, we present a large-scale measurement study that performs an in-depth analysis of the activities of various apps running in background on thousands of phones in the wild. Second, we quantify the amount of battery drain by all such background activities and possible energy saving. Third, we develop a metric to measure the usefulness of background activities that is personalized to each user. Finally, we present a system called HUSH (screen-off optimizer) that monitors the metric online and automatically identifies and suppresses background activities during screen-off periods that are not useful to the user experience. In doing so, our proposed HUSH saves screen-off energy of smartphones by 15.7% on average while incurring minimal impact on the user experience with the apps.

The limited battery life of modern smartphones remains a leading factor adversely affecting the mobile experience of millions of smartphone users. In order to extend battery life, it is critical to understand where and how is energy drain happening on users' phones under normal usage, for example, in a one-day cycle.

Mobile data traffic has witnessed tremendous growth over the last few years. A key application driving that growth is Over-The-Top (OTT) applications. Yet very little is known about the OTT traffic characteristics. In this paper, we focus on delay-sensitive real-time Internet video call applications such as Skype. We propose a novel intra-flow prioritization packet dropping (IPPD) scheme for efficient congestion mitigation of OTT Internet applications in Mobile Broadband Networks, e.g. 3G, LTE, LTE-A, etc. Simulation results show a great increase of video call capacity in a LTE network. The necessary protocol enhancements for LTE networks are also discussed.

To explore the energy efficient Machine-Type Communication (MTC) for 5G cellular systems, we developed a simulation platform to investigate the complete uplink procedures of energy-harvesting MTC devices in LTE-A (Long Term Evolution Advanced) system. Though the 3rd Generation Partnership (3GPP) has worked on LTE-A cellular standards in support of MTC transmission, the standards have not taken energy-harvesting MTC devices into their scope. Energy-harvesting technology can be the candidate to support the MTC features by allowing the devices to harvest ambient energy and support their own power usage without manual upgrade. The proposed Energy-Aware LTE-A scheme, serving as power control and admission control, prevents the devices from building the network connections greedily but ending up with energy shortage and packet loss. This scheme not only can reduce the contention level of control channels but also can decrease energy wastage on network entry procedures, thereby improving the overall energy efficiency.

Discontinuous reception (DRX) saves battery power of user equipment (UE) usually at the expense of potential increase in latency in the Long Term Evolution (LTE) networks. Therefore, an optimization is needed to find the best tradeoff between latency and power saving. In this paper, we first develop an analytical model to estimate power saving achieved and latency incurred by DRX mechanism for active and background mobile traffic. A tradeoff scheme is then formulated to maintain a balance between these two performance parameters based on operator's preference for power saving and latency requirement of traffic. The analytical model is validated using system level simulation results obtained from OPNET Modeler. The results show that the proposed tradeoff scheme is efficient in keeping a balance between power saving and latency. The results also indicate that DRX short cycles are very effective in reducing latency for active traffic, while shorter inactivity timer is desirable for background traffic to enhance power saving. We also proposed a mechanism to switch DRX configuration based on traffic running at UE, using UE assistance procedure recently adopted by 3GPP in Release 11. DRX configuration switching increases the power saving significantly without any noticeable increase in latency of active traffic.

Discontinuous reception (DRX) can be configured as a power saving mechanism for user equipment (UE) in connected mode in the long term evolution advanced (LTE-A) network. Since DRX saves UE's battery power usually at the cost of increased latency, a tradeoff between these two conflicting performance metrics are inevitable. DRX parameters can be optimized for either maximizing power saving or minimizing latency based on the applications running at the UE. In this paper, we first develop an analytical model to estimate power saving achieved and latency incurred by DRX operation. We then propose a scheme to tune DRX parameters in order to keep a balance between these conflicting performance metrics by formulating a multi-objective optimization problem. The tradeoff between power saving and latency is achieved based on the operator's relative preferences for these metrics. We also validate our analytical model by system level simulation results from OPNET Modeler. OPNET simulation results are well aligned with the MATLAB results based on analytical model and the results show that proposed scheme efficiently optimizes the DRX configuration for the battery power saving and latency requirements of various diverse data applications based on the preferences determined by operator.

In LTE networks, mobile applications and their higher data rate requirements are the latest phenomenon causing a tremendous need in power saving for mobile devices. Discontinuous reception (DRX) is one of the key power saving mechanisms in LTE. Since DRX saves battery power of user equipment usually at the expense of potential increase in latency, an optimization is needed to find the best tradeoff between latency and power saving. In this paper, we first develop an analytical model to estimate power saving achieved and latency incurred by DRX operation. Then, a tradeoff scheme is formulated to maintain a balance between these two performance parameters based on operator's preference for power saving. We validate analytical model using system level simulation results obtained from OPNET Modeler. The results show that the proposed tradeoff scheme is highly efficient in keeping a balance between power saving and latency. We have shown that proposed scheme can achieve a significant delay improvement with a small decrease in power saving. The results also indicate that short DRX cycles are very effective in reducing latency for active traffic.

As future M2M (Machine-to-Machine) communications aim at supporting wireless networks which feature long range, long operating duration and large device number, the IEEE 802.11ah Task Group is going to specify a global WLAN standard that utilizes carrier frequencies below 1GHz. To power the M2M devices, harvesting energy from ambient environment has attracted attentions from researchers. Although applying the IEEE 802.11 PSM (Power-Saving Mode) scheme reduces energy consumption, devices go to sleep only when the traffic buffer is empty, staying awake unnecessarily, which wastes energy in overhearing the uplink traffic transmitted to the AP. In this paper, we propose DeepSleep, a novel energy-aware scheme, which grants higher channel access priority for low energy level devices dynamically. Moreover, applying DeepSleep scheme alleviates the channel congestion by randomly deferring the wake up time of the devices, thereby achieving higher energy-efficiency, which saves nearly 75 % of energy per delivered packet. Additionally, the overall performance improvement when DeepSleep devices co-exist with 802.11 devices is also verified.

In this paper, we introduce an app-radio cross-layer framework for improving Quality of user Experience (QoE) of Over-The-Top (OTT) Internet applications in Mobile Broadband Networks, e.g. WiMAX, 3G, LTE, etc. We apply methods similar to the well-known network layer techniques: Explicit Congestion Notification (ECN) and Differentiated Services (DiffServ) to application layer and wireless link layer. We focus on UDP based delay-sensitive real-time video call applications such as Skype, and propose to exchange cross-layer information, e.g. congestion, packet priority, etc., through API (application programming interface) based control signals instead of the existing ECN and DiffServ fields in IP data packet header. We built a prototype system with Microsoft Windows XP OS and Intel Mobile WiMAX network adapter, and use POLQA Mean Opinion Score (MOS) to measure the audio QoE for the video call. Empirical results show that immediate congestion indication effectively speeds up Skype response to bandwidth variation, and intra-flow prioritization further reduces the delay of audio packets. Both significantly improve the audio MOS of a video call.

Discontinuous reception (DRX) brings power saving at user equipment (UE) at the cost of increased delay in 3GPP long term evolution (LTE) network. While configuring DRX parameters, a tradeoff between power saving and delay is inevitable in practice. For example, delay is crucial factor for delay sensitive applications such as online gaming, while power saving becomes the main concern for social networking applications. In this paper, we propose an algorithm to efficiently select DRX parameters to ensure a balanced tradeoff between these two conflicting performance parameters depending on application's delay requirement and UE power constraint. The proposed scheme is capable of optimizing one of these performance parameters while satisfying a specified level of guarantee for the other. Simulation results show that proposed algorithm is able to increase the power saving significantly by efficiently selecting the DRX parameters. For example, smart selection of DRX cycle for given inactivity timer increases the power saving by more than 40% depending on the delay requirement. Simulation results further show that proposed algorithm provides higher flexibility in DRX parameter selection by allowing a DRX parameter to be relaxed with the adjustment in other DRX parameter without any performance degradation.

High demand for mobile voice puts forth the requirement of high VoIP capacity over WiMAX networks. Although WiMAX networks are well-known for high-speed internet access on the go, VoIP capacity over WiMAX is low due to large control overhead. In this paper, we propose Group Resource Allocation (GRA) mechanism that reduces the control overhead and hence increases VoIP Capacity over WiMAX. In GRA multiple users are provided allocation as a group. Grouping is based on common traffic and channel characteristics and uses bitmaps to signal resource allocation information to users. Grouping of users and use of bitmaps reduces control overhead. Simulation results show that a 40% gain in VoIP capacity over WiMAX can be achieved with Group Resource Allocation.

WiMAX networks are considered efficient for supporting data traffic. However, the VoIP capacity of IEEE 802.16e WiMAX system is not great due to the large MAP overhead caused by dynamic scheduling of VoIP traffic. Persistent scheduling was adopted as a mechanism in IEEE 802.16e Rev2 to reduce this MAP overhead and resulted in a 15% increase in VoIP capacity as compared to dynamic scheduling. While the MAP overhead is reduced, persistent scheduling may cause "resource holes" in the data allocation region of the frame thereby resulting in inefficient resource utilization. This paper proposes a group scheduling mechanism to overcome this problem. The flexibility in resource allocation achieved with group scheduling results in efficient resource utilization within the frame and yet takes advantage of persistence to reduce the MAP overhead. Our simulation results show that our proposal can achieve 22% unidirectional improvement in capacity as compared to dynamic scheduling and 6.5% higher capacity as compared to persistent scheduling.

Hop adaptive MAC-PDU (Protocol Data Unit) size optimization is proposed for Orthogonal Frequency Division Multiple Access (OFDMA) based wireless relay networks. Such optimization improves the end-to- end goodput via MAC-PDU size optimization. We provide design and evaluation for two hop cellular networks with fixed relays where the Base Station (BS) to Relay Station (RS) links are potentially robust and are Line of Sight (LOS). The proposal reduces the total overhead transmitted in the end-to-end path via transmitting longer length packets in the potentially robust BS-to-RS links. The link level simulations show that, the reductions in overhead that consists of header and tailer is 25% to 44%. The system level investigations in a multi-user environment with a total of 3 relays in the cell show an average end-to-end goodput gain of 13%.

This paper studies the downlink Orthogonal Frequency Division Multiplexing (OFDM) setup with a single Base Station (BS) serving many users. The BS is assumed to have limited Channel State Information (CSI) obtained by explicit feedback from the downlink users. Given that the feedback rate and the coherence time of the channel are fixed, the question asked in this paper is: how to allocate the feedback resources optimally? Specifically, what is the optimal number of tones grouped as a subchannel, the number of users that feedback for any subchannel and the number of bits used for quantization of CSI? Analytical expressions are derived for the i.i.d. Rayleigh fading case and it is shown that there is a definite hierarchy in the importance of the three design variables. Feedback resources are first allocated to create the maximum number of subchannels possible, then to allow for more users to feedback for any subchannel and lastly to increase the precision of the channel value. Monte-Carlo simulations are performed to verify the accuracy of the derived analytical expressions.

Optimal tone allocation in downlink OFDMA networks is a non-convex NP-hard problem that requires extensive feedback for channel information. In this paper, two constant complexity limited-feedback algorithms are proposed to achieve near-optimal performance. First, using opportunistic feedback, the proposed schemes are shown to reduce feedback overhead by requiring only users likely to be allocated resources to feedback. There are differences between the two proposed schemes for implementation of the feedback protocol. One scheme requires less feedback but is contention-based, while the other scheme is sequential and thus avoids possible collisions leading to slightly higher performance, but needs more feedback. Second, complexity is reduced for resource allocation by solving the optimization problem in a distributed manner, rather than centrally at the base station. As shown both analytically and through numerical results, these distributed algorithms reduce the required feedback overhead significantly, and achieve constant computational complexity with little performance loss compared to the optimal solution.

This paper presents an opportunistic feedback (OF) protocol that reduces the amount of channel-state-information (CSI) feedback for the OFDMA downlink system. The OF protocol associates a channel value instead of a user to each feedback slot. The users access the slots opportunistically based on their channel state measurement for each tone. This allows the base station (BS) to deduce the channel state from the slot index without explicit channel-state feedback, and also solve the resource allocation problem on the fly. The OF protocol is designed to support heterogeneous traffic, where users with deadline-sensitive (DS) applications are prioritized over best- effort (BE) users. The proposed OF protocol (a) requires finite number of feedback slots upper bounded by a small number, (b) is fully distributed, and (c) provides QoS to the DS applications.

We consider optimal allocation of resources to users in a downlink OFDMA system to support heterogeneous applications consisting of both deadline-sensitive (DS) and best-effort (BE) data in a cross-layer manner. Given the user queue-states and long-term channel statistics, the proposed persistent scheduling algorithm allocates the minimum resources to 'just' meet the deadlines for DS packets (QoS guarantee). The remaining resources are optimally split between the users for their BE data to maximize sum-rate, minimize buffer holding cost or any general utility function. We formulate the resource allocation problem as a single geometric program (GP) that can be solved using standard convex optimization software tools. Simulation results are presented to compare the performance of different objectives for the BE applications in presence of DS traffic.

This paper considers a wireless uplink, where some users have deadline-sensitive (DS) traffic and others have best- effort (BE) traffic. The objective is to meet the deadlines for DS packets a fixed percent of time (QoS guarantee), at the same time minimizing the sum-power used for transmission in a distributed manner without feedback fromallusers to the base station (BS). Given each user's channel state and rate requirement, the optimal user ordering that minimizes sum-power is shown to be independent of the rate requirements and depends solely on the channel conditions. Based on this, using a limited amount of feedback, the proposed opportunistic feedback (OF) protocol guarantees QoS to DS data and minimizes sum-power. Numerical results show that (i) the OF protocol provides deadline-meeting guarantees and (ii) minimizes sum-power with a greatly reduced feedback overhead as compared to that of a central scheduler.

This paper studies optimal allocation of resources to users in a fading broadcast channel (BC) to support heterogeneous traffic. Resource allocation is done in a cross-layer manner for both deadline-sensitive (DS) and best-effort (BE) data to provide users guaranteed Quality of Service (QoS). Given the user queue-states, the proposed algorithm allocates the minimum resource to 'just' meet the deadlines for DS packets a fixed % of time. The remaining resources are then optimally split between the users for their BE data to maximize sum-rate, minimize buffer holding cost or any general utility function. The resource allocation problem is formulated as a linear program (LP) followed by a geometric program (GP) which can be solved very efficiently. Simulation results are presented for Poisson packet arrivals and exponentially distributed packet lengths on a Rayleigh fading channel for both the DS and BE traffic.

The present suite of 3G wireless network standards make use of forward link channel quality reports to more efficiently schedule users on a forward time-shared packet data channel. As the feedback rate and precision of these reports is increased, the performance of the scheduling decision is also increased since it is based on more recent and accurate data. However, this also increases the reverse link resources needed for these reports. In order to reduce the mobile power required to make these reports, some standards (e.g., IxEV-DO (N. Bhushan et al., 2006) (2004)) take advantage of time diversity gains by repeating the report for a specified number of times but with an overall reduction in the power required. Naturally this reduces the maximum rate at which these reports can be made and increases the staleness of the information provided to the scheduler. The users with the poorest reverse link conditions dictate the number of repetitions. This means that reports made by users in good radio conditions will likely be received after a smaller number of repetitions. Presently the scheduler does not use these early terminated reports in making scheduling decisions. In this paper we show that if the scheduler uses this information then the forward link performance can be increased

We propose a channel allocation scheme called unified channel allocation (UCA) appropriate for both uniform and non-uniform traffic environment. The currently available channel allocation schemes such as fixed, dynamic and hybrid schemes are not suitable for all traffic conditions. The fixed channel allocation scheme does not perform well in non-uniform traffic environment and the dynamic scheme does not do well in uniform heavy traffic conditions. In real situations, however, the user traffic pattern changes with time and space. The UCA scheme adaptively changes its channel recommendation pattern for each cell to satisfy the current demand under all traffic conditions. We demonstrate through simulation that the proposed scheme, using the virtual channel set (VCS), performs better than the other schemes in all traffic conditions. Furthermore, the UCA scheme is a practical scheme, because it can be implemented without knowledge of the traffic fluctuations with time and space, since the underlying VCSs will adapt to traffic fluctuations.

We analytically derive the appropriate rates and optimum transmit power levels that need to be allocated for high data rate services in downlinks of a WCDMA system with a time-slotted structure consisting of variable-length time slots and frames. It is shown that the average throughput decreases by 90% and average delay increases ten-fold in a severe shadowing environment (/spl sigma/=8 dB) compared to no shadowing. However, by introducing an outage probability of 0.05 as opposed to serving all the mobiles, the average system throughput can be increased six-fold and the average delay can be reduced by about 80% in such channel conditions. We analyze the trade-off between the throughput and delay performance of the system and the operating point of the outage. We consider two modes of transmission: a uni-access mode in which only one user is allowed to access the channel at a time, and a multi-access mode in which multiple users are allowed. We compare the performance of four scheduling schemes such as round-robin and fastest-first schemes that are appropriate for the uni-access mode, and equal-rate and equal-weight schemes that are for multi-access mode transmission. Simulation results show that the system employing the uni-access mode schemes performs better than one with multi-access mode schemes in terms of the average delay, and performs worse in terms of fair allocation of data rates.