26 research outputs found
On the Delay-Throughput Tradeoff in Distributed Wireless Networks
This paper deals with the delay-throughput analysis of a single-hop wireless
network with transmitter/receiver pairs. All channels are assumed to be
block Rayleigh fading with shadowing, described by parameters
, where denotes the probability of shadowing and
represents the average cross-link gains. The analysis relies on the
distributed on-off power allocation strategy (i.e., links with a direct channel
gain above a certain threshold transmit at full power and the rest remain
silent) for the deterministic and stochastic packet arrival processes. It is
also assumed that each transmitter has a buffer size of one packet and dropping
occurs once a packet arrives in the buffer while the previous packet has not
been served. In the first part of the paper, we define a new notion of
performance in the network, called effective throughput, which captures the
effect of arrival process in the network throughput, and maximize it for
different cases of packet arrival process. It is proved that the effective
throughput of the network asymptotically scales as , with , regardless of
the packet arrival process. In the second part of the paper, we present the
delay characteristics of the underlying network in terms of the packet dropping
probability. We derive the sufficient conditions in the asymptotic case of such that the packet dropping probability tend to zero, while
achieving the maximum effective throughput of the network. Finally, we study
the trade-off between the effective throughput, delay, and packet dropping
probability of the network for different packet arrival processes.Comment: Submitted to IEEE Transactions on Information Theory (34 pages
Two-Dimensional Drone Base Station Placement in Cellular Networks Using MINLP Model
Utilization of drones is going to become predominated in cellular networks as aerial base stations in order to temporary cover areas where stationary base stations cannot serve the users. Detecting optimal location and efficient number of drone-Base Stations (DBSs) are the targets we tackle in this paper. Toward this goal, we first model the problem using mixed integer non-linear programming. The output of the proposed method is the number and the optimal location of DBSs in a two-dimension area, and the object is to maximize the number of covered users. In the second step, since the proposed method is not solvable using conventional methods, we use a proposed method to solve the optimization problem. Simulation results illustrate that the proposed method has achieved its goals
Delay-Throughput Analysis in Distributed Wireless Networks
A primary challenge in wireless networks is to use available resources efficiently so
that the Quality of Service (QoS) is satisfied while maximizing the throughput of the
network. Among different resource allocation strategies, power and spectrum allocations
have long been regarded as efficient tools to mitigate interference and improve the
throughput of the network. Also, achieving a low transmission delay is an important
QoS requirement in buffer-limited networks, particularly for users with real-time
services. For these networks, too much delay results in dropping some packets. Therefore, the main challenge
in networks with real-time services is to utilize an efficient power allocation scheme
so that the delay is minimized while achieving a high throughput. This dissertation
deals with these problems in distributed wireless networks
On the Throughput Maximization in Dencentralized Wireless Networks
A distributed single-hop wireless network with links is considered, where
the links are partitioned into a fixed number () of clusters each operating
in a subchannel with bandwidth . The subchannels are assumed to be
orthogonal to each other. A general shadow-fading model, described by
parameters , is considered where denotes the
probability of shadowing and () represents the average
cross-link gains. The main goal of this paper is to find the maximum network
throughput in the asymptotic regime of , which is achieved by: i)
proposing a distributed and non-iterative power allocation strategy, where the
objective of each user is to maximize its best estimate (based on its local
information, i.e., direct channel gain) of the average network throughput, and
ii) choosing the optimum value for . In the first part of the paper, the
network hroughput is defined as the \textit{average sum-rate} of the network,
which is shown to scale as . Moreover, it is proved that in
the strong interference scenario, the optimum power allocation strategy for
each user is a threshold-based on-off scheme. In the second part, the network
throughput is defined as the \textit{guaranteed sum-rate}, when the outage
probability approaches zero. In this scenario, it is demonstrated that the
on-off power allocation scheme maximizes the throughput, which scales as
. Moreover, the optimum spectrum sharing for
maximizing the average sum-rate and the guaranteed sum-rate is achieved at M=1.Comment: Submitted to IEEE Transactions on Information Theor
On the Energy Efficiency of LT Codes in Proactive Wireless Sensor Networks
This paper presents an in-depth analysis on the energy efficiency of Luby
Transform (LT) codes with Frequency Shift Keying (FSK) modulation in a Wireless
Sensor Network (WSN) over Rayleigh fading channels with pathloss. We describe a
proactive system model according to a flexible duty-cycling mechanism utilized
in practical sensor apparatus. The present analysis is based on realistic
parameters including the effect of channel bandwidth used in the IEEE 802.15.4
standard, active mode duration and computation energy. A comprehensive
analysis, supported by some simulation studies on the probability mass function
of the LT code rate and coding gain, shows that among uncoded FSK and various
classical channel coding schemes, the optimized LT coded FSK is the most
energy-efficient scheme for distance d greater than the pre-determined
threshold level d_T , where the optimization is performed over coding and
modulation parameters. In addition, although the optimized uncoded FSK
outperforms coded schemes for d < d_T , the energy gap between LT coded and
uncoded FSK is negligible for d < d_T compared to the other coded schemes.
These results come from the flexibility of the LT code to adjust its rate to
suit instantaneous channel conditions, and suggest that LT codes are beneficial
in practical low-power WSNs with dynamic position sensor nodes.Comment: accepted for publication in IEEE Transactions on Signal Processin
Adaptive Demodulation in Differentially Coherent Phase Systems: Design and Performance Analysis
Adaptive Demodulation (ADM) is a newly proposed rate-adaptive system which
operates without requiring Channel State Information (CSI) at the transmitter
(unlike adaptive modulation) by using adaptive decision region boundaries at
the receiver and encoding the data with a rateless code. This paper addresses
the design and performance of an ADM scheme for two common differentially
coherent schemes: M-DPSK (M-ary Differential Phase Shift Keying) and M-DAPSK
(M-ary Differential Amplitude and Phase Shift Keying) operating over AWGN and
Rayleigh fading channels. The optimal method for determining the most reliable
bits for a given differential detection scheme is presented. In addition,
simple (near-optimal) implementations are provided for recovering the most
reliable bits from a received pair of differentially encoded symbols for
systems using 16-DPSK and 16- DAPSK. The new receivers offer the advantages of
a rate-adaptive system, without requiring CSI at the transmitter and a coherent
phase reference at the receiver. Bit error analysis for the ADM system in both
cases is presented along with numerical results of the spectral efficiency for
the rate-adaptive systems operating over a Rayleigh fading channel.Comment: 25 pages, 11 Figures, submitted to IEEE Transactions on
Communications, June 1, 201
ViT-CAT: Parallel Vision Transformers with Cross Attention Fusion for Popularity Prediction in MEC Networks
Mobile Edge Caching (MEC) is a revolutionary technology for the Sixth
Generation (6G) of wireless networks with the promise to significantly reduce
users' latency via offering storage capacities at the edge of the network. The
efficiency of the MEC network, however, critically depends on its ability to
dynamically predict/update the storage of caching nodes with the top-K popular
contents. Conventional statistical caching schemes are not robust to the
time-variant nature of the underlying pattern of content requests, resulting in
a surge of interest in using Deep Neural Networks (DNNs) for time-series
popularity prediction in MEC networks. However, existing DNN models within the
context of MEC fail to simultaneously capture both temporal correlations of
historical request patterns and the dependencies between multiple contents.
This necessitates an urgent quest to develop and design a new and innovative
popularity prediction architecture to tackle this critical challenge. The paper
addresses this gap by proposing a novel hybrid caching framework based on the
attention mechanism. Referred to as the parallel Vision Transformers with Cross
Attention (ViT-CAT) Fusion, the proposed architecture consists of two parallel
ViT networks, one for collecting temporal correlation, and the other for
capturing dependencies between different contents. Followed by a Cross
Attention (CA) module as the Fusion Center (FC), the proposed ViT-CAT is
capable of learning the mutual information between temporal and spatial
correlations, as well, resulting in improving the classification accuracy, and
decreasing the model's complexity about 8 times. Based on the simulation
results, the proposed ViT-CAT architecture outperforms its counterparts across
the classification accuracy, complexity, and cache-hit ratio
Interference Aware Routing Game for Cognitive Radio Ad-hoc Networks, Journal of Telecommunications and Information Technology, 2018, nr 3
Cognitive radio is a new communication paradigm that is able to solve the problem of spectrum scarcity in wireless networks. In this paper, interference aware routing game, (IRG), is proposed that connects the flow initiators to the destinations. A network formation game among secondary users (SUs) is formulated in which each secondary user aims to maximize its utility, while it reduces the aggregate interference on the primary users (PUs) and the end-to-end delay. In order to reduce the end-to-end delay and the accumulated interference, the IRG algorithm selects upstream neighbors in a view point of the sender. To model the interference between SUs, IRG uses the signal-to-interference-plus noise (SINR) model. The effectiveness of the proposed algorithm is validated by evaluating the aggregate interference from SUs to the PUs and end-to-end delay. A comprehensive numerical evaluation is performed, which shows that the performance of the proposed algorithm is significantly better than the Interference Aware Routing (IAR) using network formation game in cognitive radio mesh networks