Throughput Optimal Multi-user Scheduling via Hierarchical Modulation

We investigate the network stability problem when two users are scheduled simultaneously. The key idea is to simultaneously transmit to more than one users experiencing different channel conditions by employing hierarchical modulation. For two-user scheduling problem, we develop a throughput-optimal algorithm which can stabilize the network whenever this is possible. In addition, we analytically prove that the proposed algorithm achieves larger achievable rate region compared to the conventional Max-Weight algorithm which employs uniform modulation and transmits a single user. We demonstrate the efficacy of the algorithm on a realistic simulation environment using the parameters of High Data Rate protocol in a Code Division Multiple Access system. Simulation results show that with the proposed algorithm, the network can carry higher user traffic with lower delays.Comment: 4 pages, 2 figures, submitte

Reliable multi-hop routing with cooperative transmissions in energy-constrained networks

We present a novel approach in characterizing the optimal reliable multi-hop virtual multiple-input single-output (vMISO) routing in ad hoc networks. Under a high node density regime, we determine the optimal cardinality of the cooperation sets at each hop on a path minimizing the total energy cost per transmitted bit. Optimal cooperating set cardinality curves are derived, and they can be used to determine the optimal routing strategy based on the required reliability, transmission power, and path loss coefficient. We design a new greedy geographical routing algorithm suitable for vMISO transmissions, and demonstrate the applicability of our results for more general networks

Finite Horizon Throughput Maximization for a Wirelessly Powered Device over a Time Varying Channel

In this work, we consider an energy harvesting device (EHD) served by an access point with a single antenna that is used for both wireless power transfer (WPT) and data transfer. The objective is to maximize the expected throughput of the EHD over a finite horizon when the channel state information is only available causally. The EHD is energized by WPT for a certain duration, which is subject to optimization, and then, EHD transmits its information bits to the AP until the end of the time horizon by employing optimal dynamic power allocation. The joint optimization problem is modeled as a dynamic programming problem. Based on the characteristic of the problem, we prove that a time dependent threshold type structure exists for the optimal WPT duration, and we obtain closed form solution to the dynamic power allocation in the uplink period.Comment: arXiv admin note: substantial text overlap with arXiv:1804.0183

Energy efficient random sleep-awake schedule design

This letter presents a simple model for determining energy efficient random sleep-awake schedules. Random sleepawake schedules are more appropriate for sensor networks, where the time of occurrence of an event being monitored, e.g., the detection of an intruder, is unknown a priori, and the coordination among nodes is costly. We model the random sleepawake schedule as a two state Markov process, and maximize the probability of the transmission of sensed data by a given deadline. Our results indicate that for a given duty cycle, the optimal policy is to have infrequent transitions between sleep and awake modes, if the average number of packets sent is greater than the mean number of slots the node is awake

Throughput analysis of ALOHA with cooperative diversity

Cooperative transmissions emulate multi-antenna systems and can improve the quality of signal reception. In this paper, we propose and analyze a cross layer random access scheme, C-ALOHA, that enables cooperative transmissions in the context of ALOHA system. Our analysis shows that over a fading channel C-ALOHA can improve the throughput by 30%, as compared to standard ALOHA protocol

Energy distribution control in wireless sensor networks through range optimization

A major objective in wireless sensor networks is to find optimum routing strategies for energy efficient use of nodes. Routing decision and transmission power selection are intrinsically connected since the transmission power of a node is adjusted depending on the location of the next hop. In this paper, we propose a location-based routing framework to control the energy distribution in a network where transmission ranges, hence powers, of nodes are determined based on their locations. We show that the proposed framework is sufficiently general to investigate the minimum-energy and maximum-lifetime routing problems. It is shown that via the location based strategy the network lifetime can be improved by 70% and the total energy consumption can be decreased to three-fourths to one-third of the constant transmission range strategy depending on the propagation medium and the size of the network

Energy-Optimal Scheduling in Low Duty Cycle Sensor Networks

Energy consumption of a wireless sensor node mainly depends on the amount of time the node spends in each of the high power active (e.g., transmit, receive) and low power sleep modes. It has been well established that in order to prolong node's lifetime the duty-cycle of the node should be low. However, low power sleep modes usually have low current draw but high energy cost while switching to the active mode with a higher current draw. In this work, we investigate a MaxWeightlike opportunistic sleep-active scheduling algorithm that takes into account time- varying channel and traffic conditions. We show that our algorithm is energy optimal in the sense that the proposed ESS algorithm can achieve an energy consumption which is arbitrarily close to the global minimum solution. Simulation studies are provided to confirm the theoretical results

UAV data collection over NOMA backscatter networks: UAV altitude and trajectory optimization

The recent evolution of ambient backscattering technology has the potential to provide long-range and low-power wireless communications. In this work, we study the unmanned aerial vehicle (UAV)-assisted backscatter networks where the UAV acts both as a mobile power transmitter and as an information collector. We aim to maximize the number of successfully decoded bits in the uplink while minimizing the UAV's flight time by optimizing its altitude. Power-domain NOMA scheme is employed in the uplink. An optimization framework is presented to identify the trade-off between numerous network parameters, such as UAV's altitude, number of backscatter devices, and backscatter coefficients. Numerical results show that an optimal altitude is computable for various network setups and that the impact of backscattering reflection coefficients on the maximum network throughput is significant. Based on this optimal altitude, we also show that an optimal trajectory plan is achievable

QoE based random sleep-awake scheduling in heterogeneous cellular networks

In this paper, we investigate an optimal resource on-off switching framework that minimizes the energy consumption of a heterogeneous cellular network. Specifically, our goal is to minimize the energy consumption of the cellular network while satisfying a desired level of buffer starvation probability, which can be considered as a quality of experience (QoE) term. For an ON/OFF bursty arrival process, we introduce recursive equations to obtain the buffer starvation probability of a mobile device (MD) for streaming services. The MD is in the coverage area of a femtocell base station (FBS) which is implemented at the cell edge of a macrocell base station (MBS), and when its buffer gets empty, the media player of the MD restarts the service after a certain amount of packets are prefetched (this event is known as start-up delay in the literature). Numerical simulations illustrate how our system significantly reduces the overall energy consumption of the network while guaranteeing a target starvation probability in comparison to the case where the MD is covered only by one MBS

QoS based aggregation in high speed IEEE802.11 wireless networks

We propose a novel frame aggregation algorithm with statistical delay guarantee for high speed IEEE802.11 networks considering link quality fluctuations. We use the concept of effective capacity to formulate frame aggregation with QoS guarantee as an optimization problem. The QoS guarantee is in the form of a target delay bound and violation probability. We apply proper approximations to derive a simple formulation, which is solved using a Proportional-Integral-Derivative (PID) controller. The proposed PID aggregation algorithm independently adapts the amount of time allowance for each link, while it needs to be implemented only at the Access Point (AP), without requiring any change to the 802.11 Medium Access Control (MAC). More importantly, the aggregator does not consider any physical layer or channel information, as it only makes use of queue level metrics, such as average queue length and link utilization, for tuning the amount of time allowance. NS-3 simulations show that our proposed scheme outperforms Earliest Deadline First (EDF) scheduling with maximum aggregation size and pure deadlinebased aggregation, both in terms of maximum number of stations and channel efficiency