| 1. |
- Chu, Thi My Chinh, et al.
(författare)
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Adaptive Modulation and Coding with Queue Awareness in Cognitive Incremental Decode-and-Forward Relay Networks
- 2014
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Konferensbidrag (refereegranskat)abstract
- This paper studies the performance of adaptive modulation and coding in a cognitive incremental decode-and-forward relaying network where a secondary source can directly communicate with a secondary destination or via an intermediate relay. To maximize transmission efficiency, a policy which flexibly switches between the relaying and direct transmission is proposed. In particular, the transmission, which gives higher average transmission efficiency, will be selected for the communication. Specifically, the direct transmission will be chosen if its instantaneous signal-to-noise ratio (SNR) is higher than one half of that of the relaying transmission. In this case, the appropriate modulation and coding scheme (MCS) of the direct transmission is selected only based on its instantaneous SNR. In the relaying transmission, since the MCS of the transmissions from the source to the relay and from the relay to the destination are implemented independently to each other, buffering of packets at the relay is necessary. To avoid buffer overflow at the relay, the MCS for the relaying transmission is selected by considering both the queue state and the respective instantaneous SNR. Finally, a finite-state Markov chain is modeled to analyze key performance indicators such as outage probability and average transmission efficiency of the cognitive relay network.
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| 2. |
- Knorn, Steffi, et al.
(författare)
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Multi-sensor estimation using energy harvesting and energy sharing
- 2015
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Konferensbidrag (refereegranskat)abstract
- This paper investigates an optimal energy allocation problem for multi sensor estimation of a random source where sensors communicate their measurements to a remote fusion centre (FC) over orthogonal fading wireless channels using uncoded analog transmissions. The FC reconstructs the source using the best linear unbiased estimator (BLUE). The sensors have limited batteries but can harvest energy and also transfer energy to other sensors in the network. A distortion minimization problem over a finite-time horizon with causal and non-causal information is studied and the optimal energy allocation policy for transmission and sharing is derived. Several structural necessary conditions for optimality are presented for the two sensor problem with non-causal information and a horizon of two time steps. Numerical simulations are included to illustrate the theoretical results.
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| 3. |
- Mahmoudi, Afsaneh, 1993-, et al.
(författare)
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Cost-efficient Distributed Optimization In Machine Learning Over Wireless Networks
- 2020
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Konferensbidrag (refereegranskat)abstract
- This paper addresses the problem of distributed training of a machine learning model over the nodes of a wireless communication network. Existing distributed training methods are not explicitly designed for these networks, which usually have physical limitations on bandwidth, delay, or computation, thus hindering or even blocking the training tasks. To address such a problem, we consider a general class of algorithms where the training is performed by iterative distributed computations across the nodes. We assume that the nodes have some background traffic and communicate using the slotted-ALOHA protocol. We propose an iteration-termination criterion to investigate the trade-off between achievable training performance and the overall cost of running the algorithms. We show that, given a total running budget, the training performance becomes worse as either the background communication traffic or the dimension of the training problem increases. We conclude that a co-design of distributed optimization algorithms and communication protocols is essential for the success of machine learning over wireless networks and edge computing.
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| 4. |
- Shirazinia, Amirpasha, et al.
(författare)
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Optimized compressed sensing matrix design for noisy communication channels
- 2015
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Konferensbidrag (refereegranskat)abstract
- We investigate a power-constrained sensing matrix design problem for a compressed sensing framework. We adopt a mean square error (MSE) performance criterion for sparse source reconstruction in a system where the source-to-sensor channel and the sensor-to-decoder communication channel are noisy. Our proposed sensing matrix design procedure relies upon minimizing a lower-bound on the MSE. Under certain conditions, we derive closed-form solutions to the optimization problem. Through numerical experiments, by applying practical sparse reconstruction algorithms, we show the strength of the proposed scheme by comparing it with other relevant methods. We discuss the computational complexity of our design method, and develop an equivalent stochastic optimization method to the problem of interest that can be solved approximately with a significantly less computational burden. We illustrate that the low-complexity method still outperforms the popular competing methods.
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| 5. |
- Huang, Shaocheng, 1990-, et al.
(författare)
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Achievable Rate Analysis of Millimeter Wave Channels with Random Coding Error Exponent
- 2019
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Ingår i: IEEE International Conference on Communications. - : IEEE. - 9781538680889
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Konferensbidrag (refereegranskat)abstract
- Millimeter Wave (mmWave) communication has attracted massive attention, since the abundant available bandwidth can potentially provide reliable communication with orders of magnitude capacity improvements relative to microwave. However, the achievable rate of mmWave channels under latency and reliability constraints is still not quite clear. We investigate the achievable rates of mmWave channels by random coding error exponent (RCEE) with finite blocklength. With imperfect channel state information at the receiver, the exact and approximate analytical expressions of the training based maximum achievable rate are derived to capture the relationship among rate-latency-reliability. Additionally, the relationship between the training based maximum achievable rate and bandwidth is investigated. We show that there exists critical bandwidth to maximize the training based maximum achievable rate for the non-line-of-sight (NLoS) propagation. Numerical results show that the approximate expression of the training based maximum achievable rate are tight and can capture the tendency at low SNRs. In addition, results show that for a given rate, one can reduce both packet duration and decoding error probability by increasing bandwidth. Results also suggest that in some mmWave bands, e.g. 57-64 GHz band, the performance, i.e., Gallager function, is significantly affected by frequency selective power absorption.
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