nils-herrmann/clean_scirepeval huggingface dataset:
Distributed Linearized ADMM for Network Cost Minimization

In this paper, we study a generic network cost minimization problem, in which every node has a local decision vector to determine. Each node incurs a cost depending on its decision vector and each link also incurs a cost depending on the decision vectors of its two end nodes. All nodes cooperate to minimize the overall network cost. The formulated network cost minimization problem has broad applications in distributed signal processing and control over multiagent systems. To obtain a decentralized algorithm for the formulated problem, we resort to the distributed alternating direction method of multipliers (DADMM). However, each iteration of the DADMM involves solving a local optimization problem at each node, leading to intractable computational burden in many circumstances. As such, inspired by recent works on approximated ADMM for consensus optimization problem, we propose a distributed linearized ADMM (DLADMM) algorithm for network cost minimization. In the DLADMM, each iteration only involves closed-form computations and avoids local optimization problems, which greatly reduces the computational complexity compared to the DADMM. We prove that the DLADMM converges to an optimal point when the local cost functions are convex and have Lipschitz continuous gradients. Linear convergence rate of the DLADMM is also established if the local cost functions are further strongly convex. Numerical experiments are conducted to corroborate the effectiveness of the DLADMM and we observe that the DLADMM has similar convergence performance as DADMM does while the former enjoys much lower computational overhead. The impact of network topology, connectivity, and algorithm parameters are also investigated through simulations.
Distributed energy-efficient cooperative routing in wireless networks

Recently, the merits of cooperative communication in the physical layer have been explored. However, the impact of cooperative communication on the design of the higher layers has not been well-understood yet. Cooperative routing in wireless networks has gained much interest due to its ability to exploit the broadcast nature of the wireless medium in designing power efficient routing algorithms. Most of the existing cooperation based routing algorithms are implemented by finding a shortest path route first and then improving the route using cooperative communication. As such, these routing algorithms do not fully exploit the merits of cooperative communications, since the optimal cooperative route might not be similar to the shortest path route. In this paper, we propose a cooperation-based routing algorithm, namely, the minimum power cooperative routing (MPCR) algorithm, which makes full use of the cooperative communications while constructing the minimum-power route. The MPCR algorithm constructs the minimum-power route, which guarantees certain throughput, as a cascade of the minimum-power single-relay building blocks from the source to the destination. Thus, any distributed shortest path algorithm can be utilized to find the optimal cooperative route with polynomial complexity. Using analysis, we show that the MPCR algorithm can achieve power saving of 65.61% in regular linear networks and 29.8% in regular grid networks compared to the existing cooperation-based routing algorithms, where the cooperative routes are constructed based on the shortest-path routes. From simulation results, MPCR algorithm can have 37.64% power saving in random networks compared to those cooperation-based routing algorithms.
Adaptive Pilot-Embedded Data-Bearing Approach Channel Estimation in Space-Frequency Coded MIMO-OFDM Systems

In this paper, we study the effects of model mismatch error inherently in the FFT-based channel estimation approach when considering the multipath delay profiles with non-integer delays. We propose an adaptive FFT-based channel estimator that employs the optimum number of significant taps such that the average total energy of the channels dissipating in each tap is completely captured in order to compensate the model mismatch error. Furthermore, our proposed pilot-embedded data-bearing approach is employed for joint channel estimation and data detection. Simulation results reveal that the adaptive FFT-based channel estimator is superior to the FFT-based and LS channel estimators; however, in nonquasi-static fading channels under high Doppler's shift regimes, the performances of all three channel estimators are quite close resulting from the influence of the channel mismatch error that dominates all factors causing the detection error
Downlink MAC Scheduler for 5G Communications With Spatial Focusing Effects

Driven by the demand for supporting the rapidly increasing wireless traffic, the next-generation communication system, i.e., the 5G system, needs to accommodate a massive number of users and judiciously manage the interference. One promising candidate, the time reversal (TR) system, uses a large bandwidth and designs transmitting waveforms, such that the environment acts as a matched filter and the transmitted signal adds up coherently at the intended users. Therefore, the energy is focused only at the intended users with reduced interference to others. The other candidate, massive MIMO system, utilizes a large number of antennas to focus on the energy to the users and reduce the mutual interference. However, the massive number of users poses a limit on system performance due to increasing interuser interference, and the system has to make a judicial selection of transmitting users. In this paper, we propose a scheduler that maximizes the system weighted sum rate while satisfying the minimum rate requirements of the transmitting users. The optimization problem is transformed into a mixed integer quadratically constrained quadratic programming with linear time complexity. We also investigate the impact of imperfect channel information on the proposed scheduler algorithm and reveal similar channel estimation error distribution between the TR and massive MIMO system. We evaluate the performance of the proposed scheduler in different scenarios and the results show that the proposed scheduler has several desirable characteristics, including low time complexity, suitable on versatile system structure, and robustness against imperfect channel information.
Eavesdropping-Resistant Space-Time Network Coding for Cooperative Communications

Due to the broadcast nature, wireless transmissions can be overheard by any receiver within the transmission range. A physical layer approach for secure wireless cooperative communications is proposed in this paper. Considering the asynchronous nature of cooperative communications, this paper proposes an eavesdropping-resistant space-time network coding (STNC) scheme for multinode cooperative communications to prevent eavesdropping and overcome the problem of imperfect synchronization. In the proposed scheme, training symbols are transmitted by the destination $D$ instead of the user nodes. Therefore, each user node can obtain the channel state information (CSI) between itself and $D$, which is unavailable to the eavesdropper $E$. By exploiting such CSI and the transmit information symbols, weighting coefficient is designed at each user node to prevent $E$ from interception and ensure successful decoding at $D$. Based on the pairwise error probability (PEP) analysis, STNC is designed to achieve full diversity at $D$ and improve the transmission efficiency of the asynchronous cooperative system. Simulation results are presented to verify the performance of the proposed eavesdropping-resistant STNC scheme.
Delay sensitive scheduling schemes for heterogeneous QoS over wireless networks

Future wireless networks will support the growing demands of heterogeneous and delay sensitive applications. In this paper, a users' satisfaction factor (USF) is defined to quantify quality of service (QoS) for different types of services such as voice, data, and multimedia, as well as for different delay constraints. This USF not only predicts the final delivered QoS during transmission, but also take advantages of the fact that different packets can be decoded at different time in the receivers. Based on this USF, four types of scheduling schemes considering tradeoffs between system performance and individual fairness are proposed. These schemes explore the time, channel, and multi-user diversity to guarantee quality of service and enhance the network performance. From the simulation results, the proposed scheduling schemes achieve different tradeoffs between individual fairness and high system performance for the heterogeneous and delay sensitive applications, compared with the weighted round-robin and the modified proportional fairness scheduling schemes
On Optimal and Cheat-Proof Packets Forwarding Strategies in Autonomous Ad Hoc Networks

This paper mathematically studies the cooperation and packet forwarding issues among selfish nodes in ad hoc networks under a game theoretic framework. Since in such packet forwarding games there usually exist an infinite number of Nash equilibria, a critical issue is how to perform equilibrium refinement, that is, how to apply extra optimality criteria to remove those equilibrium strategies that are less robust, less rational, or less likely. In this work, besides Pareto optimality and subgame perfection, other important optimality criteria, such as social welfare maximization, absolute fairness, and proportional fairness, have also been considered when performing equilibrium refinement. Combining with Pareto optimality and subgame perfection, each of these criteria can lead to a unique Nash equilibrium solution. Since nodes are selfish and will try to cheat whenever possible, the possible cheating behavior has also been fully exploited, and the analysis has shown that when cheating behaviors are considered, all these unique equilibrium solutions will converge to the same format, that is, a node should not help its opponent more than its opponent has helped it.
A transformation for computational latency reduction in turbo-MAP decoding

The SOVA and the log-MAP are commonly used in turbo decoding. In this paper, we propose to modify the sliding window MAP-algorithm to reduce the computational delay even further. We compare the simulation performance of this low latency log-MAP algorithm with the sliding window log-MAP. We also estimate the VLSI implementation complexities of the SOVA, the log-MAP and the proposed low latency log-MAP.
Distributed Space-Frequency Coding over Broadband Relay Channels

Designing diversity achieving schemes over the wireless broadband fading relay channels is crucial to achieve higher diversity gains. These gains are achieved by exploiting the multipath (frequency) and cooperative diversities to combat the fading nature of wireless channels. The challenge is how to design space frequency codes, distributed among randomly located nodes that can exploit the frequency diversity of the wireless broadband channels. In this paper, the design of distributed space-frequency codes (DSFCs) for wireless relay networks is considered. The proposed DSFCs are designed to achieve the frequency and cooperative diversities of the wireless relay channels. The use of DSFCs with the decode-and-forward (DAF) and amplify-and forward (AAF) protocols is considered. The code design criteria to achieve full diversity, based on the pairwise error probability (PEP) analysis, are derived. For DSFC with the DAF protocol, a two-stage coding scheme, with source node coding and relay nodes coding, is proposed. We derive sufficient conditions for the proposed code structures at the source and relay nodes to achieve full diversity of order NL, where N is the number of relay nodes and L is the number of paths per channel. For the case of DSFC with the AAF protocol, a structure for distributed space-frequency coding is proposed.
Low peak to average power ratio cyclic Golay sequences for OFDM systems

In this paper, the cyclic shifts of low peak to average power ratio (PAPR) codes used in OFDM transmission is proposed. They comprise a superclass of Golay complementary codes (GCC) with the same level of PAPR (viewed by the discrete OFDM symbols). These codes achieve higher information rate with the expense of lower error correction capabilities. We have proposed a framework for constructing these codes out of GCC. The framework can be applied to obtain the cyclic shift of any code represented by Boolean algebraic functions. An efficient transmission scheme is proposed such that the coding scheme can be switched between the Golay and cyclic Golay codes, based on a feedback from the receiver to perform a better trade-off between the coding rate and bit error rate (BER).
Differential Space-Time Network Coding for Multi-Source Cooperative Communications

Due to the asynchronous nature of cooperative communications, simultaneous transmissions from two or more nodes are challenging in practice. The existing cooperative communications employing successive transmission from one user node to the other can avoid the synchronization problem but results in large transmission delay. In addition, channel estimation in multi-source cooperative communications is a challenging and costly task due to the amount of training, especially when the number of cooperative users is large. Considering these practical challenges in multi-source cooperative communications, this paper proposes a differential space-time network coding (DSTNC) scheme for narrowband multi-source cooperative communications to overcome the problems of imperfect synchronization and complex channel estimation without introducing large transmission delay. Each user in the network linearly combines the correctly decoded symbols via network coding and transmits its packet in time division multiple access (TDMA) mode. The pairwise error probability is analyzed and the design criteria of the DSTNC are derived to achieve full diversity. For broadband cooperative communications, distributed differential space-time-frequency network coding (DSTFNC), which is differentially encoded within each orthogonal frequency-division multiplexing (OFDM) block, is designed through mapping from the proposed DSTNC. When the statistical channel power-delay profile is known at the corresponding user node, each node can permutate its channel independently to improve the performance of the DSTFNC scheme. Simulation results are presented to verify the performance of the proposed schemes.
A complete pipelined parallel CORDIC architecture for motion estimation

We propose a novel fully-pipelined parallel CORDIC architecture (CORDIC-DXT-ME) employing the DCT Pseudo-Phase Techniques for Motion Estimation. Its low computational complexity, O(N/sup 2/) as compared with O(N/sup 4/) of BKM-ME, makes it fascinating in real time applications. In addition, the DCT-based nature enables us to replace all multipliers by CORDICs with simple shift-and-add operations and to incorporate its implementation with the DCT codec design to gain further savings in hardware complexity. The architecture is regular, modular, and has solely local connection and is suitable for MPEG2 compatible video codec design on a dedicated single chip.
Orthogonal space-time block codes with sphere packing

Orthogonal designs have received considerable attention in the development of efficient modulation and coding methods for future multi-antenna wireless communication systems due to their special properties. In this paper, we propose a class of space-time block codes constructed by combining orthogonal designs with sphere packing for an arbitrary number of transmit antennas. The structure of the orthogonal designs is exploited to guarantee full diversity, and sphere packing is used to improve the coding advantage. Space-time block code construction from block-orthogonal designs is also considered: the full-diversity property is ensured by rotating the sphere packing underlying the code, and the optimal rotation angle is determined for a class of sphere packing. Code design examples are provided for two and four transmit antennas and various transmission rates. The simulation results show that by jointly designing the symbols in the orthogonal designs, the performance of the block codes can be significantly increased.
Power Scheduling for Energy Harvesting Wireless Communications With Battery Capacity Constraint

Power scheduling is an important issue for energy harvesting systems. In this work, we study the power control policy for minimizing the weighted sum of the outage probabilities under a set of predetermined transmission rates over a finite horizon. This problem is challenging in that the objective function is non-convex. To make the analysis tractable, we apply the approximation at high signal-to-noise ratios and obtain a near-optimal offline solution. In the case of infinite battery capacity, we demonstrate that the allocated power has a piecewise structure, i.e., each power scheduling cycle should be divided into disjoint segments and the normalized power should remain constant within each segment. An iterative algorithm is developed to obtain the power solution. In the case of finite battery capacity, we show that the piecewise structure still holds true, and we develop a divide-and-conquer algorithm to recursively solve the power allocation problem. Finally, we obtain a simple online power control policy that is fairly robust to prediction errors of the harvested energy. Simulations demonstrate that the proposed power solution has better performance than other strategies such as best-effort, fixed-ratio and random allocation.
A joint channel estimation and unequal error protection scheme for image transmission in wireless OFDM systems

Orthogonal frequency division multiplexing (OFDM) modulation, adopted by the digital video broadcasting (DVB-T) standard, has been recognized for its good performance for high data rate wireless communications. Therefore, the study of the robust transmission of multimedia data over OFDM systems has attracted extensive research interests. In the past, channel estimation, which is an important aspect in OFDM systems, has not been exploited for multimedia transmission. When using the block training based channel estimation, OFDM data blocks experience unequal decoding error rate due to the imprecision of channel estimation. We use this property to provide unequal error protection (UEP) for transmission of SPIHT coded images. Compared with the systems using pilot training channel estimation schemes, which are recommended in the DVB-T standard, the proposed scheme improves the PSNR of reconstructed images by up to 2 dB.
A Belief Evaluation Framework in Autonomous MANETs under Noisy and Imperfect Observation: Vulnerability Analysis and Cooperation Enforcement

In autonomous mobile ad hoc networks (MANETs) where each user is its own authority, the issue of cooperation enforcement must be solved first to enable networking functionalities such as packet forwarding, which becomes very difficult under noisy and imperfect monitoring. In this paper, we consider cooperation enforcement in autonomous mobile ad hoc networks under noisy and imperfect observation and study the basic packet forwarding among users through the repeated game models with imperfect information. A belief evaluation framework is proposed to obtain cooperation-enforcement packet forwarding strategies only based on each node's private information including its own past actions and imperfect observation of other nodes' information. More importantly, we not only show that the proposed strategy with belief system can maintain the cooperation paradigm but also establish its performance bounds. The simulation results illustrate that the proposed belief evaluation framework can enforce the cooperation with only a small performance degradation compared with the unconditionally cooperative outcomes when noisy and imperfect observation exist.
Optimal contract design for ancillary services in vehicle-to-grid networks

With the foreseeable large scale deployment of electric vehicles (EVs) and the development of vehicle-to-grid (V2G) technologies, it is possible to provide ancillary services to the power grid in a cost efficient way, i.e., through the bidirectional power flow of EVs. A key issue in such kind of schemes is how to stimulate a large number of EVs to act coordinately to achieve the service request. This is challenging since EVs are self-interested and generally have different preferences toward charging and discharging based on their own constraints. In this paper, we propose a contract-based mechanism to tackle this challenge. Through the design of an optimal contract, the aggregator can provide incentives for EVs to participate in ancillary services to power grid, match the aggregated energy rate with the service request and maximize its own utility. Simulation results are shown to verify the effectiveness of the proposed contract-based mechanism.
Data-Driven Auction Mechanism Design in IaaS Cloud Computing

With the emergence of big data computing and analysis, cloud computing services become more and more popular, which has recently drawn researchers’ great attentions to develop various new applications and mechanisms. In this paper, we consider the on-demand mechanism design in the infrastructure as a service (IaaS), including resource allocation and pricing issues under dynamic scenarios. Most of existing works on mechanism design assumed static and independent individual utility, while the cloud computing services are provided in a dynamic environment. To solve such problems, we start with analyzing the Google cluster-usage dataset to draw the statistical and stochastic characteristics of the IaaS consumers and providers. Based on the characteristics mined from real data, we propose a stochastic matching algorithm with Markov Decision Process (MDP), which aims at optimizing the long-term system efficiency, with its online version using Q-learning method to address the imperfect model estimation problem. We further design an efficient (EF), incentive compatible (IC), individual rational (IR) auction mechanism, which is an extension of traditional Vickrey-Clarke-Groves (VCG) mechanism. The proposed mechanism is studied under two application scenario: quality sensitive services, where unilateral MDP-VCG auction is implemented; and quality insensitive services, where MDP-VCG double auction is implemented. To verify the performance of our proposed mechanism, we conduct experiment using the Google dataset and show that the proposed MDP-based VCG auction mechanism can achieve EF, IC and IR properties simultaneously.
On the performance evaluation of TH and DS UWB MIMO systems

In this paper, we analyze the performance of ultra-wideband (UWB) multiple-input multiple-output (MIMO) systems employing various modulation and multiple access schemes, including time hopping (TH) M-ary pulse position modulation (MPPM), TH binary phase shift keying (BPSK), and direct sequence (DS) BPSK. We quantify the performance merits of UWB space-time (ST) systems regardless of the specific coding scheme. For each modulation scheme, we introduce a framework that enables us to compare UWB MIMO systems with conventional UWB single-antenna systems in terms of diversity and coding gain. Moreover, we adopt the real orthogonal design (ROD) as the engine code for UWB ST codes. We find the closed form expressions of the average pairwise error probability (PEP) bound for all of the schemes under the hypothesis of Nakagami flat fading channels. The extension to frequency-selective fading case is also briefly addressed. Finally, simulation results are presented to support the theoretical analysis.