2,726 research outputs found
Power Allocation for Conventional and Buffer-Aided Link Adaptive Relaying Systems with Energy Harvesting Nodes
Energy harvesting (EH) nodes can play an important role in cooperative
communication systems which do not have a continuous power supply. In this
paper, we consider the optimization of conventional and buffer-aided link
adaptive EH relaying systems, where an EH source communicates with the
destination via an EH decode-and-forward relay. In conventional relaying,
source and relay transmit signals in consecutive time slots whereas in
buffer-aided link adaptive relaying, the state of the source-relay and
relay-destination channels determines whether the source or the relay is
selected for transmission. Our objective is to maximize the system throughput
over a finite number of transmission time slots for both relaying protocols. In
case of conventional relaying, we propose an offline and several online joint
source and relay transmit power allocation schemes. For offline power
allocation, we formulate an optimization problem which can be solved optimally.
For the online case, we propose a dynamic programming (DP) approach to compute
the optimal online transmit power. To alleviate the complexity inherent to DP,
we also propose several suboptimal online power allocation schemes. For
buffer-aided link adaptive relaying, we show that the joint offline
optimization of the source and relay transmit powers along with the link
selection results in a mixed integer non-linear program which we solve
optimally using the spatial branch-and-bound method. We also propose an
efficient online power allocation scheme and a naive online power allocation
scheme for buffer-aided link adaptive relaying. Our results show that link
adaptive relaying provides performance improvement over conventional relaying
at the expense of a higher computational complexity.Comment: Submitted to IEEE Transactions on Wireless Communication
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
HARQ Buffer Management: An Information-Theoretic View
A key practical constraint on the design of Hybrid automatic repeat request
(HARQ) schemes is the size of the on-chip buffer that is available at the
receiver to store previously received packets. In fact, in modern wireless
standards such as LTE and LTE-A, the HARQ buffer size is one of the main
drivers of the modem area and power consumption. This has recently highlighted
the importance of HARQ buffer management, that is, of the use of buffer-aware
transmission schemes and of advanced compression policies for the storage of
received data. This work investigates HARQ buffer management by leveraging
information-theoretic achievability arguments based on random coding.
Specifically, standard HARQ schemes, namely Type-I, Chase Combining and
Incremental Redundancy, are first studied under the assumption of a
finite-capacity HARQ buffer by considering both coded modulation, via Gaussian
signaling, and Bit Interleaved Coded Modulation (BICM). The analysis sheds
light on the impact of different compression strategies, namely the
conventional compression log-likelihood ratios and the direct digitization of
baseband signals, on the throughput. Then, coding strategies based on layered
modulation and optimized coding blocklength are investigated, highlighting the
benefits of HARQ buffer-aware transmission schemes. The optimization of
baseband compression for multiple-antenna links is also studied, demonstrating
the optimality of a transform coding approach.Comment: submitted to IEEE International Symposium on Information Theory
(ISIT) 2015. 29 pages, 12 figures, submitted to journal publicatio
End-to-End Simulation of 5G mmWave Networks
Due to its potential for multi-gigabit and low latency wireless links,
millimeter wave (mmWave) technology is expected to play a central role in 5th
generation cellular systems. While there has been considerable progress in
understanding the mmWave physical layer, innovations will be required at all
layers of the protocol stack, in both the access and the core network.
Discrete-event network simulation is essential for end-to-end, cross-layer
research and development. This paper provides a tutorial on a recently
developed full-stack mmWave module integrated into the widely used open-source
ns--3 simulator. The module includes a number of detailed statistical channel
models as well as the ability to incorporate real measurements or ray-tracing
data. The Physical (PHY) and Medium Access Control (MAC) layers are modular and
highly customizable, making it easy to integrate algorithms or compare
Orthogonal Frequency Division Multiplexing (OFDM) numerologies, for example.
The module is interfaced with the core network of the ns--3 Long Term Evolution
(LTE) module for full-stack simulations of end-to-end connectivity, and
advanced architectural features, such as dual-connectivity, are also available.
To facilitate the understanding of the module, and verify its correct
functioning, we provide several examples that show the performance of the
custom mmWave stack as well as custom congestion control algorithms designed
specifically for efficient utilization of the mmWave channel.Comment: 25 pages, 16 figures, submitted to IEEE Communications Surveys and
Tutorials (revised Jan. 2018
Wireless industrial monitoring and control networks: the journey so far and the road ahead
While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks
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