nils-herrmann/clean_scirepeval huggingface dataset:
MIMO interference cancelation via network formation game

This paper considers the cooperative maximization of mutual information in the MIMO Gaussian interference channel in a fully distributed manner via game theory. Null shaping constraints are enforced in the design of transmit covariance matrices to enable interference mitigation among links. The transmit covariance matrices leading to the Nash Equilibrium (NE) are derived, and the existence and uniqueness of the NE is analyzed. The formation of the cooperative sets, that represent the cooperation relationship among links, is considered as network formation games. We prove that the proposed network formation (NF) algorithm converges to a Nash Equilibrium. Simulation results show that the proposed NF algorithm enhances the sum rate of the system apparently even at low signal-to-noise ratio region and/or with small number of transmit antennas.
Software radio architecture with smart antennas: a tutorial on algorithms and complexity

There has been considerable interest in using antenna arrays in wireless communication networks to increase the capacity and decrease the cochannel interference. Adaptive beamforming with smart antennas at the receiver increases the carrier-to-interference ratio (CIR) in a wireless link. This paper considers a wireless network with beamforming capabilities at the receiver which allows two or more transmitters to share the same channel to communicate with the base station. The concrete computational complexity and algorithm structure of a base station are considered in terms of a software radio system model, initially with an omnidirectional antenna. The software radio computational model is then expanded to characterize a network with smart antennas. The application of the software radio smart antenna is demonstrated through two examples. First, traffic improvement in a network with a smart antenna is considered, and the implementation of a hand-off algorithm in the software radio is presented. The blocking probabilities of the calls and total carried traffic in the system under different traffic policies are derived. The analytical and numerical results show that adaptive beamforming at the receiver reduces the probability of blocking and forced termination of the calls and increases the total carried traffic in the system. Then, a joint beamforming and power control algorithm is implemented in a software radio smart antenna in a CDMA network. This shows that, by using smart antennas, each user can transmit with much lower power, and therefore the system capacity increases significantly.
Unified VLSI lattice architectures for discrete sinusoidal transforms

The problems of unified efficient computations of the discrete cosine transform (DCT), discrete sine transform (DST), discrete Hartley transform (DHT), and their inverse transforms are considered. A new scheme employing the time-recursive approach to compute these transforms is presented. Unified parallel lattice structures that can dually generate the DCT and DST simultaneously as well as the DHT are developed using such an approach. These structures can obtain the transformed data for sequential input time-recursively with a throughput rate of one per clock cycle. The total number of multipliers required is a linear function of the transform size N. There is no constraint on N. It is also shown that the DCT, DST, DHT and their inverse transforms share an almost identical lattice structure. Two methods, the single-input single-output (SISO) and double-lattice approaches, are developed to reduce the number of multipliers in the parallel lattice structure by 2N and N, respectively. The tradeoff between time and area for the block data processing is considered. The concept of filter bank interpretation of the time-recursive sinusoidal transforms is discussed.<<ETX>>
Rate control for DS-CDMA wireless systems using power control and orthogonally coded substreams

There is an increase of multimedia applications in wireless networks. The increase in data transmission requirements for some multimedia applications poses a problem for the service providers who must overcome the high interference environment to provide this higher transmission rate. One method to service multimedia users is by splitting their data streams into separately coded substreams. We propose an algorithm to choose the optimal number of substreams for each multimedia user and to use power control techniques to control the rate of each substream.
A renewal-theoretical framework for dynamic spectrum access with unknown primary behavior

Dynamic spectrum access in cognitive radio networks can greatly improve the spectrum utilization efficiency. Nevertheless, interference may be introduced to the Primary User (PU) when the Secondary Users (SUs) dynamically utilize the licensed channel. If the SUs can be synchronous with the PUs, the interference is mainly due to their imperfect spectrum sensing of the primary channel. However, if the SUs have no knowledge about the PU's communication mechanism, additional interference may occur. In this paper, we propose a renewal theoretical framework to study the situation when SUs confronting with unknown primary behavior. We quantify the interference caused by the SUs and derive the corresponding close-form expressions. With the interference analysis, we study how to optimize the SUs' performance under the constraints of the PU's communication quality of service (QoS). Finally, simulation results are shown to verify the effectiveness of our analysis.
Scalable hierarchical access control in secure group communications

Many group communications require a security infrastructure that ensures multiple levels of access privilege for group members. Access control in hierarchy is prevalent in multimedia applications, which consist of users that subscribe to different quality levels or different sets of data streams. We present a multi-group key management scheme that achieves such a hierarchical access control by employing an integrated key graph and by managing group keys for all users with various access privileges. Compared with applying existing tree-based group key management schemes directly to the hierarchical access control problem, the proposed scheme significantly reduces the communication, computation and storage overhead associated with key management and achieves better scalability when the number of access levels increases. In addition, the proposed key graph is suitable for both centralized and contributory environments.
Combined joint source-channel coding and channel estimation for image transmissions over wireless channels

and channel coding (JSCC), multicarrier modulation (MCM) and diversity are some key techniques for multimedia transmission over wireless channels. We investigate a joint source channel matching (JSCM) scheme for progressive image transmission in the MCM system using multiple antennas. The focus of this work is on the effect of the practical channel estimation schemes on the JSCM algorithm. This is different from other research on JSCC assuming perfectly known channel information. We propose a model-based channel estimation scheme and use it.
Accurate carrier frequency offset estimation in time-reversal communications

Time-reversal (TR) wideband communication could harvest the energy from the rich-scattering environment and enjoy the unique spatial and temporal focusing effect. However, the performance degrades in the presence of carrier frequency offset (CFO), which introduces an additional phase linear in time. CFO estimators could mitigate its effect. Yet, conventional CFO estimators cannot work well regarding the tiny CFO due to the high sampling rate in wideband TR systems. To address this issue, we propose four CFO estimators which are capable to estimate very small CFO with very high accuracy. Theoretical performance analyses of the proposed estimators are derived. Realizing that phase wrapping could introduce a large bias into estimation, we also derive the condition for phase wrapping avoidance. Extensive experimental results in real environment demonstrate the superiority and applicability of the proposed methods.
Differential unitary space-time signal design using matrix rotation structure

We consider the design of matrix rotation based space-time signals based on the design criterion of minimizing the union bound on block error probability. We further propose to design the signal parameters via noninteger searching to get better signals. Superior performance of our improved design over the previous design are demonstrated through numerical calculations and performance simulations. With our proposed design for two transmit antennas and one or two receive antennas, we achieve the coding gain of about 1 dB over that of the previous design.
Two-Way Network-Coded Relaying With Delay Constraint

Random channel fading may cause serious channel outage, and automatic repeat-request protocol has been widely used to mitigate packet loss by retransmitting the packet when the receiver fails to decode that packet. To restrict the transmission delay, a single packet might be retransmitted up to a limited number of times. For wireless two-way relay channels, the packet could be retransmitted by the original source node or the relay nodes, and the delay constraint might be imposed in a per-hop manner or end-to-end manner. For single-relay networks, we study the throughput of several relaying strategies including pure relaying and network-coded relaying subject to the delay constraint. We demonstrate that the binary xor-based network coding can greatly improve the system throughput, but the throughput gain is upper bounded. We also develop a near-optimum power allocation scheme to maximize the system throughput. For multirelay networks, we show that using digital network coding alone may cause some throughput loss when the frame length is much smaller than the number of relays, and we develop a hybrid network coding scheme to recover such throughput loss.
DCT-based motion estimation

We propose novel discrete cosine transform (DCT) pseudophase techniques to estimate shift/delay between two one-dimensional(1-D) signals directly from their DCT coefficients by computing the pseudophase shift hidden in DCT and then employing the sinusoidal orthogonal principles, applicable to signal delay estimation remote sensing. Under the two-dimensional (2-D) translational motion model, we further extend the pseudophase techniques to the DCT-based motion estimation (DXT-ME) algorithm for 2-D signals/images. The DXT-ME algorithm has certain advantages over the commonly used full search block-matching approach (BKM-ME) for application to video coding despite certain limitations. In addition to its robustness in a noisy environment and low computational complexity, O(M(2)) for an MxM search range in comparison to the O(N(2) . M(2)) complexity of BKM-ME for an NxN block, its ability to estimate motion completely in DCT domain makes possible the fully DCT-based motion-compensated video coder structure, which has only one major component in the feedback loop instead of three as in the conventional hybrid video coder design, and thus results in a higher system throughput. Furthermore, combination of the DCT and motion estimation units can provide space for further optimization of the overall coder. In addition, the DXT-ME algorithm has solely highly parallel local operations and this property makes feasible parallel implementation suitable for very large scale integration (VLSI) design. Simulation on a number of video sequences is presented with comparison to BKM-ME and other fast block search algorithms for video coding applications even though DXT-ME is completely different from any block search algorithms.
Cooperative Multiple Access for Wireless Networks: Protocols Design and Stability Analysis

A new cooperative multiple-access protocol is proposed in which a relay utilizes the empty time slots available in a TDMA frame. In particular, the relay helps the users in the network forwarding their unsuccessfully transmitted packets during the empty time slots. This will better utilize the channel resources that are otherwise wasted, and will introduce on-demand spatial diversity into the network. The proposed cooperation protocol is also different from those proposed in the literature as it does not result in any bandwidth loss. Two different protocols are proposed to implement this new multiple-access scheme, and their stability regions are characterized. The stability regions of the proposed protocols are shown to contain that of TDMA without relaying, hence, relay deployment in wireless networks can increase the network throughput capacity. Moreover, the analysis and numerical results reveal that the proposed cooperative multiple access protocols can simultaneously achieve higher stable throughput and less energy expenditure compared to TDMA without relaying.
Interference Alleviation for Time-Reversal Cloud Radio Access Network

Due to the unique spatial and temporal focusing effects, time-reversal (TR) communication can be utilized in the cloud radio access network, where it creates a tunneling effect such that the traffic load in the front-haul links can be alleviated in both downlink and uplink. Although the basic TR waveforms are simple to use, they cannot provide the optimal performance in some cases. While the cloud radio access network (C- RAN) is usually expected to serve massive wireless devices, the severe inter-user interference (IUI) might limit the performance of the system. In this paper, we propose to optimize both downlink and uplink transmissions so as to alleviate the interference. In the downlink transmission, optimal content-aware waveform design is proposed so that the baseband units (BBUs) are able to combine both the channel information and the symbol information to suppress the interference. In the uplink transmission, an optimal receiver design algorithm is proposed such that the BBUs can detect the symbols transmitted by the terminal devices (TDs) more accurately by leveraging the channel information. We study the BER performance of the proposed algorithm based on extensive measurements of the wireless channel in a real- world environment. Numerical results demonstrate the significant performance improvement over basic TR transmission techniques.
On the achievable sum rate for two-way relay networks with stochastic energy harvesting

In this paper, an optimal transmission policy for two-way relay networks is investigated by using a stochastic energy harvesting (EH) model. Considering the channel and finite battery conditions, we propose an optimal relay transmission policy to maximize the long-term achievable sum rate of the network. The design problem is formulated as a Markov decision process (MDP), and the well-known value iteration approach is used to find the optimal policy. Based on the optimal transmission policy, we analyze the expected achievable sum rate and point out a spreading structure for the optimal relay power with respect to the solar panel size. Simulation results demonstrate that our proposed optimal transmission policy outperforms other policies.
SPC12-5: Relay Selection in Multi-Node Cooperative Communications: When to Cooperate and Whom to Cooperate with?

In this paper, we propose a new cooperative communication protocol, which achieves high bandwidth efficiency while guaranteeing full diversity order. The proposed scheme considers relay selection via the available partial channel state information (CSI) at the source and the relays. More precisely, the source determines when it needs to cooperate with one relay only among arbitrary N relays and which relay to cooperate with in case of cooperation, i.e., "When to cooperate?" and "Whom to cooperate with?". In case of cooperation, the source employs the optimal relay, which has the maximum instantaneous scaled harmonic mean function of its source-relay and relay-destination channels' gains. For the symmetric scenario, we prove that full diversity is guaranteed and that a significant increase of the bandwidth efficiency is achieved. Furthermore, we show the tradeoff between the achievable bandwidth efficiency and the corresponding error rate. Finally, the obtained analytical results are verified through computer simulations.
Cooperation Stimulation Strategies for Peer-to-Peer Wireless Live Video-Sharing Social Networks

Human behavior analysis in video sharing social networks is an emerging research area, which analyzes the behavior of users who share multimedia content and investigates the impact of human dynamics on video sharing systems. Users watching live streaming in the same wireless network share the same limited bandwidth of backbone connection to the Internet, thus, they might want to cooperate with each other to obtain better video quality. These users form a wireless live-streaming social network. Every user wishes to watch video with high quality while paying as little as possible cost to help others. This paper focuses on providing incentives for user cooperation. We propose a game-theoretic framework to model user behavior and to analyze the optimal strategies for user cooperation simulation in wireless live streaming. We first analyze the Pareto optimality and the time-sensitive bargaining equilibrium of the two-person game. We then extend the solution to the multiuser scenario. We also consider potential selfish users' cheating behavior and malicious users' attacking behavior and analyze the performance of the proposed strategies with the existence of cheating users and malicious attackers. Both our analytical and simulation results show that the proposed strategies can effectively stimulate user cooperation, achieve cheat free and attack resistance, and help provide reliable services for wireless live streaming applications.
Anti-collusion fingerprinting for multimedia

Digital fingerprinting is a technique for identifying users who use multimedia content for unintended purposes, such as redistribution. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cost-effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are combined to disrupt the underlying fingerprints. We investigate the problem of designing fingerprints that can withstand collusion and allow for the identification of colluders. We begin by introducing the collusion problem for additive embedding. We then study the effect that averaging collusion has on orthogonal modulation. We introduce a tree-structured detection algorithm for identifying the fingerprints associated with K colluders that requires O(Klog(n/K)) correlations for a group of n users. We next develop a fingerprinting scheme based on code modulation that does not require as many basis signals as orthogonal modulation. We propose a new class of codes, called anti-collusion codes (ACCs), which have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we can therefore identify groups of K or fewer colluders. We present a construction of binary-valued ACC under the logical AND operation that uses the theory of combinatorial designs and is suitable for both the on-off keying and antipodal form of binary code modulation. In order to accommodate n users, our code construction requires only O(/spl radic/n) orthogonal signals for a given number of colluders. We introduce three different detection strategies that can be used with our ACC for identifying a suspect set of colluders. We demonstrate the performance of our ACC for fingerprinting multimedia and identifying colluders through experiments using Gaussian signals and real images.
Self-Learning Repeated Game Framework for Distributed Primary-Prioritized Dynamic Spectrum Access

Dynamic spectrum access has become a promising approach to fully utilize the scarce spectrum resources. In a dynamically changing spectrum environment, it is very important to design a distributed access scheme that can coordinate different users' access adapt to spectrum dynamics with only local information. In this paper, we propose a self-learning repeated game framework for distributed primary-prioritized dynamic spectrum access through modeling the interactions between secondary users as a noncooperative game. With the proposed framework, the inefficiency due to users' selfish behavior can be highly improved, and the secondary users can distributively obtain their optimal access probabilities with only local observations. The simulation results show that the proposed framework can achieve comparable performances with those of the centralized primary-prioritized dynamic spectrum aess sheme.
Indirect Reciprocity Game Modelling for Cooperation Stimulation in Cognitive Networks

In cognitive networks, since nodes generally belong to different authorities and pursue different goals, they will not cooperate with others unless cooperation can improve their own performance. Thus, how to stimulate cooperation among nodes in cognitive networks is very important. However, most of existing game-theoretic cooperation stimulation approaches rely on the assumption that the interactions between any pair of players are long-lasting. When this assumption is not true, according to the well-known Prisoner's Dilemma and the backward induction principle, the unique Nash equilibrium (NE) is to always play non-cooperatively. In this paper, we propose a cooperation stimulation scheme for the scenario where the number of interactions between any pair of players are finite. The proposed algorithm is based on indirect reciprocity game modelling where the key concept is "I help you not because you have helped me but because you have helped others". We formulate the problem of finding the optimal action rule as a Markov Decision Process (MDP) and propose a modified value iteration algorithm to find the optimal action rule. Using the packet forwarding game as an example, we show that with an appropriate cost-to-gain ratio, the strategy of forwarding the number of packets that is equal to the reputation level of the receiver is an evolutionarily stable strategy (ESS). Finally, simulations are shown to verify the efficiency and effectiveness of the proposed algorithm.
Parallel transmission framework for layered coded multimedia data over spectrally shaped channels

This paper presents a new parallel transmission framework for reliable multimedia data transmission over spectrally shaped channels using multicarrier modulation. We propose to transmit source data layers of different perceptual importance in parallel, each occupying a number of subchannels. New loading algorithms are developed to efficiently allocate the available resources, e.g. transmitted power and bit rate, to the subchannels according to the source layers they transmit. Instead of making the bit error rate of all the subchannels equal as in most existing loading algorithms, the proposed algorithm assigns different error performance to the subchannels as to achieve unequal error protection for different layers. The channel induced distortion in mean-square sense is minimized. We show that the proposed system can be applied nicely to both fixed length coding and variable length coding. Numerical examples show that the proposed algorithm achieves significant performance improvement comparing to the existing work for spectrally shaped channels commonly used in in ADSL.