Fifth Generation (5G) wireless communication technologies play a crucial role in supporting the pervasive implementation of the Campus Internet of Things (IoT). The application of 5G wireless communication in Campus IoT will introduce unique channel characteristics that need to be fully explored through channel measurement and channel modeling in various campus scenarios. In this paper, a channel sounding system based on the Universal Software-defined Radio Peripheral (USRP) is designed, which can efficiently collect channel measuring data in diverse settings. Based on this system, channel measurements with omnidirectional and directional antennas at the 4.9, 5.2, and 5.8 GHz bands for multi-case are conducted. The measurement cases include the path loss measurements for both outdoor and indoor scenarios, the penetration loss measurements for indoor and outdoor materials, the outdoor to indoor (O2I) measurements, and the blockage effect measurements. The channel characteristics, involving path loss, shadow fading, penetration loss, and blockage effect, are extracted and analyzed. The path loss models, penetration loss models, O2I path loss models, and models for blockage effects at measured frequency bands are proposed to predict and validate channel characteristics. The channel measurement and modeling results not only demonstrate the practicality of the proposed sounding system but also provide realistic channel characteristics for the research on 5G wireless communication systems in Campus IoT scenarios.

Cardiac arrhythmia is a common cardiovascular disease that can cause sudden death in severe cases. Electro-cardiography (ECG) is the most well-known and widely applied method for heart diseases detection. Computer-aided diagnosis of ECG can help improve physician efficiency and reduce the rate of misdiagnosis of ECG. In this paper, we propose a method for arrhythmia classification based on the dense convolutional network (DenseNet) and efficient channel attention (ECA). Evaluation experiments were performed using the ECG records from the MIT-BIH database. The accuracy, sensitivity, specificity, and F1 values of 99.69%, 97.55%, 99.81%, and 97.72% were achieved for the six types of heartbeats classification, respectively. The experimental results demonstrate the validity and feasibility of the method, which can be used for ECG screening.

With the development of multiple-input-multiple-output (MIMO) technology, the over-the-air (OTA) testing of MIMO capable devices with different sizes needs to be conducted for performance evaluation. The device under test (DUT) should be within a tridimensional test volume created by multiprobe configurations. Thus, determining the maximum size of test volume could be vital to test the DUT of different size and larger test volumes should be adopted to evaluate larger DUTs. All types of probe configurations including the fixed and the flexible probe configurations are investigated in this paper to address this issue. The maximum of test volume size (MTVS) is determined within the given error threshold of spatial correlation for a given probe configuration. Simultaneously, the impact of different probe configurations on MTVS is studied in order to obtain larger MTVSs. Simulation results show that larger MTVSs can be obtained by utilizing the optimal probe configuration with any given 3D channel model for 3D MIMO OTA testing.

Crucial to the successful deployment of cognitive radio networks, security issues have begun to receive research interests recently. In this paper, we focus on defending against the jamming attack, one of the major threats to cognitive radio networks. Secondary users can exploit the flexible access to multiple channels as the means of anti-jamming defense. We first investigate the situation where a secondary user can access only one channel at a time and hop among different channels, and model it as an anti-jamming game. Analyzing the interaction between the secondary user and attackers, we derive a channel hopping defense strategy using the Markov decision process approach with the assumption of perfect knowledge, and then propose two learning schemes for secondary users to gain knowledge of adversaries to handle cases without perfect knowledge. In addition, we extend to the scenario where secondary users can access all available channels simultaneously, and redefine the anti-jamming game with randomized power allocation as the defense strategy. We derive the Nash equilibrium for this Colonel Blotto game which minimizes the worst-case damage. Finally, simulation results are presented to verify the performance.

The multi-path effect makes high speed broadband communications a very challenging task due to the severe inter-symbol interference (ISI). By concentrating energy in both the spatial and temporal domains, time-reversal (TR) transmission technique provides a great potential of low-complexity energy-efficient communications. In this paper, a novel concept of time-reversal division multiple access (TRDMA) is proposed as a wireless channel access method based on its high-resolution spatial focusing effect. It is proposed to use TR structure in multi-user downlink systems over multi-path channels, where signals of different users are separated solely by TRDMA. Both the single-transmit-antenna scheme and its enhanced version with multiple transmit antennas are developed and evaluated in this paper. The system performance is investigated in terms of its effective signal-to-interference-plus-noise ratio (SINR), the achievable sum rate and the achievable rates with outage. And some further discussions regarding its advantage over conventional rake receivers and the impact of spatial correlations between users are given at the end of this paper. It is shown in both analytical and simulation results that desirable properties and satisfying performances can be achieved in the proposed TRDMA multi-user downlink system, which makes TRDMA a promising candidate for future energy-efficient low-complexity broadband wireless communications.

Multi-path effect makes high speed broadband communications a very challenging task due to the severe inter-symbol interference (ISI). By concentrating energy in both spatial and temporal domains, time-reversal (TR) transmission technique provides a great potential of low-complexity energy-efficient communications. In this paper, we develop a new concept of time-reversal division multiple access (TRDMA) as a wireless channel access method based on its high-resolution spatial focusing effect. We propose to use TR structure in a multi-user downlink system over large delay spread channels, where the signals of different users are separated solely by TRDMA. Both the single-transmit-antenna scheme and its enhanced version with multiple-transmit-antenna are developed and evaluated in this paper. We investigate the system performance in terms of the effective SINR and the achievable sum rate of the multi-user system. It is shown in both analytical and simulation results that satisfying performances can be achieved in the proposed TRDMA multi-user downlink system.

Green wireless communications have received considerable attention recently in hope of finding novel solutions to improve energy efficiency for the ubiquity of wireless applications. In this paper, we argue and show that the time-reversal (TR) signal transmission is an ideal paradigm for green wireless communications because of its inherent nature to fully harvest energy from the surrounding environment by exploiting the multi-path propagation to re-collect all the signal energy that would have otherwise been lost in most existing communication paradigms. A green wireless technology must ensure low energy consumption and low radio pollution to others than the intended user. In this paper, we show through theoretical analysis, numerical simulations and experiment measurements that the TR wireless communications, compared to the conventional direct transmission using a Rake receiver, reveals significant transmission power reduction, achieves high interference alleviation ratio, and exhibits large multi-path diversity gain. As such it is an ideal paradigm for the development of green wireless systems. The theoretical analysis and numerical simulations show an order of magnitude improvement in terms of transmit power reduction and interference alleviation. Experimental measurements in a typical indoor environment also demonstrate that the transmit power with TR based transmission can be as low as 20% of that without TR, and the average radio interference (thus radio pollution) even in a nearby area can be up to 6dB lower. A strong time correlation is found to be maintained in the multi-path channel even when the environment is varying, which indicates high bandwidth efficiency can be achieved in TR radio communications.

Various spectrum management schemes have been proposed in recent years to improve the spectrum utilization in cognitive radio networks. However, few of them have considered the existence of cognitive attackers who can adapt their attacking strategy to the time-varying spectrum environment and the secondary users' strategy. In this paper, we investigate the security mechanism when secondary users are facing the jamming attack, and propose a stochastic game framework for anti-jamming defense. At each stage of the game, secondary users observe the spectrum availability, the channel quality, and the attackers' strategy from the status of jammed channels. According to this observation, they will decide how many channels they should reserve for transmitting control and data messages and how to switch between the different channels. Using the minimax-Q learning, secondary users can gradually learn the optimal policy, which maximizes the expected sum of discounted payoffs defined as the spectrum-efficient throughput. The proposed stationary policy in the anti-jamming game is shown to achieve much better performance than the policy obtained from myopic learning, which only maximizes each stage's payoff, and a random defense strategy, since it successfully accommodates the environment dynamics and the strategic behavior of the cognitive attackers.

Although cognitive radio technology improves efficiency of spectrum utilization, primary users usually do not gain from opening up the spectrum in the opportunistic spectrum access, and sometimes even suffer from collisions due to secondary users' imperfect spectrum sensing. However, in this paper, we show that if information secrecy is a concern, primary users could actually be better off by allowing secondary users to cooperatively share the spectrum. Specifically, we propose a new cooperation paradigm in cognitive radio networks that primary users improve secrecy with the help of trustworthy secondary users, in the presence of an intelligent and passive eavesdropper attempting to decode primary users' messages. After deriving the achievable pair of primary users' secrecy rate and secondary users' transmission rate under various circumstances, we model the interaction between primary users and secondary users as a Stackelberg game in which transmission power levels are the key to maximize data rates. Moreover, based on a 2-D representation of how achievable rates depend on power-level regions, we apply equilibrium analysis to understand the optimal strategy of primary and secondary users. Finally, simulation results are presented to verify the performance.

Cognitive radio technology has become a promising approach to increase the efficiency of spectrum utilization. Since cognitive radio users are vulnerable to malicious attacks, security countermeasures are crucial to the successful deployment of cognitive radio networks in the future. In this paper, we focus on defending against the jamming attack, one of the major threats to cognitive radio networks, where several malicious attackers intend to jam the secondary user's communication link by injecting interference. We model this scenario into a jamming game, and derive the optimal strategy through the Markov decision process approach. Furthermore, a learning scheme is proposed for the secondary user to observe the wireless environment and estimate parameters such as primary users' access pattern and the number of attackers. Finally, simulation results are presented to verify the performance.

Recently, many works have been proposed in the area of cognitive radio to efficiently utilize the spectrum for data communication. However, little effort has been made in content-aware multimedia applications over cognitive radio networks. In this paper, we study the multimedia streaming problem over cognitive radio networks. The uniquely scalable and delay-sensitive characteristics of multimedia data and the resulting impact on users' viewing experiences of multimedia content are explicitly involved in the utility functions, due to which the primary user and the secondary users can seamlessly switch among different quality levels to achieve the greatest utilities. Then, we formulate the spectrum allocation problem as an auction game and propose a distributively auction-based spectrum allocation scheme, which is spectrum allocation using Alternative Ascending Clock Auction (ACA-A). We prove that ACA-A is cheat-proof and can maximize the social welfare. Finally, simulation results are presented to demonstrate the efficiency of the proposed algorithms.

The wide-spread use of P2P video streaming systems have introduced a large number of unnecessary traverse links leading to substantial network inefficiency. To address this problem and achieve better streaming performance, we propose to enable cooperation among group peers, which are geographically neighboring peers with large intra-group upload and download bandwidths. Considering the peers' selfish nature, we formulate the cooperative streaming problem as an evolutionary game and derive the evolutionarily stable strategy (ESS) for every peer. Moreover, we propose a simple and distributed learning algorithm for the peers to converge to the ESSs. Compared to the traditional non-cooperative P2P schemes, the proposed cooperative scheme achieves much better performance in terms of social welfare and probability of real-time streaming.

Cognitive radio technologies have become a promising approach to efficiently utilize the spectrum. Although many works have been proposed recently in the area of cognitive radio for data communications, little effort has been made in content-aware multimedia applications over cognitive radio networks. In this paper, we study the multimedia streaming problem over cognitive radio networks, where there is one primary user and N secondary users. The uniquely scalable and delay-sensitive characteristics of multimedia data and the resulting impact on users' viewing experiences of multimedia content are explicitly involved in the utility functions, due to which the primary user and the secondary users can seamlessly switch among different quality levels to achieve the largest utilities. Then, we formulate the spectrum allocation problem as an auction game and propose three distributively auction-based spectrum allocation schemes, which are spectrum allocation using Single object pay-as-bid Ascending Clock Auction (ACA-S), spectrum allocation using Traditional Ascending Clock Auction (ACA-T), and spectrum allocation using Alternative Ascending Clock Auction (ACA-A). We prove that all three algorithms converge in a finite number of clocks. We also prove that ACA-S and ACA-A are cheat-proof while ACA-T is not. Moreover, we show that ACA-T and ACA-A can maximize the social welfare while ACA-S may not. Therefore, ACA-A is a good solution to multimedia cognitive radio networks since it can achieve maximal social welfare in a cheat-proof way. Finally, simulation results are presented to demonstrate the efficiency of the proposed algorithms.

While peer-to-peer (P2P) video streaming systems have achieved promising results, they introduce a large number of unnecessary traverse links, which consequently leads to substantial network inefficiency. To address this problem and achieve better streaming performance, we propose to enable cooperation among “group peers,” which are geographically neighboring peers with large intra-group upload and download bandwidths. Considering the peers' selfish nature, we formulate the cooperative streaming problem as an evolutionary game and derive, for every peer, the evolutionarily stable strategy (ESS), which is the stable Nash equilibrium and no one will deviate from. Moreover, we propose a simple and distributed learning algorithm for the peers to converge to the ESSs. With the proposed algorithm, each peer decides whether to be an agent who downloads data from the peers outside the group or a free-rider who downloads data from the agents by simply tossing a coin, where the probability of being a head for the coin is learned from the peer's own past payoff history. Simulation results show that the strategy of a peer converges to the ESS. Compared to the traditional non-cooperative P2P schemes, the proposed cooperative scheme achieves much better performance in terms of social welfare, probability of real-time streaming, and video quality (source rate).

Cognitive radio technologies have become a promising approach to increase the efficiency of spectrum utilization. Although cognitive radio has been intensively studied in recent years, only a few works have discussed security aspects. In this paper, we focus on the jamming attack, one of major threats to cognitive radio networks, where a malicious user wants to jam the communications of secondary users by injecting interference. Aware of the absence of several primary users and the presence of a malicious user, a secondary user can allocate power to those fallow bands with a randomized strategy, in hope of alleviating the damage caused by the malicious user. We model this scenario into a two-player zero-sum game, and derive its unique Nash Equilibrium under certain conditions using the Colonel Blotto game approach, which provides a minimax strategy that the secondary user should adopt in order to minimize the worst-case damage caused by the malicious user. Simulation results are presented to verify the performance.

Dynamic spectrum access (DSA), enabled by cognitive radio technologies, has become a promising approach to improve efficiency in spectrum utilization, and the spectrum auction is one important DSA approach, in which secondary users lease some unused bands from primary users. However, spectrum auctions are different from existing auctions studied by economists, because spectrum resources are interference-limited rather than quantity-limited, and it is possible to award one band to multiple secondary users with negligible mutual interference. To accommodate this special feature in wireless communications, in this paper, we present a novel multi-winner spectrum auction game not existing in auction literature. As secondary users may be selfish in nature and tend to be dishonest in pursuit of higher profits, we develop effective mechanisms to suppress their dishonest/collusive behaviors when secondary users distort their valuations about spectrum resources and interference relationships. Moreover, in order to make the proposed game scalable when the size of problem grows, the semi-definite programming (SDP) relaxation is applied to reduce the complexity significantly. Finally, simulation results are presented to evaluate the proposed auction mechanisms, and demonstrate the complexity reduction as well.

Dynamic spectrum access has become a promising approach to improve spectrum efficiency by adaptively coordinating different users' access according to spectrum dynamics. However, users who are competing with each other for spectrum may have no incentive to cooperate, and they may even exchange false private information about their channel conditions in order to get more access to the spectrum. In this paper, we propose a repeated spectrum sharing game with cheat-proof strategies. By using the punishment-based repeated game, users get the incentive to share the spectrum in a cooperative way; and through mechanism-design-based and statistics-based approaches, user honesty is further enforced. Specific cooperation rules have been proposed based on the maximum total throughput and proportional fairness criteria. Simulation results show that the proposed scheme can greatly improve the spectrum efficiency by alleviating mutual interference.

In order to fully utilize spectrum, auction-based dynamic spectrum allocation has become a promising approach which allows unlicensed wireless users to lease unused bands from spectrum license holders. Because spectrum resources are reusable by users far apart, in some scenarios, spectrum is more efficiently utilized by awarding one band to multiple secondary users simultaneously, which distinguishes it from traditional auctions where only one user can be the winner. However, the multi-winner auction is a new concept posing new challenges in the traditional auction mechanisms, because such mechanisms may yield low revenue and are not robust to some newly-emerging collusion. Therefore, in this paper, we propose an efficient mechanism for the multi-winner spectrum auction with collusion- resistant pricing strategies, in which the optimal spectrum allocation can be solved by binary linear programming and the pricing is formulated as a convex optimization problem. Furthermore, a greedy algorithm is proposed to reduce complexity for multi- band auctions. Simulation results are presented to evaluate our proposed auction mechanisms.

Dynamic spectrum access has become a promising approach that can coordinate different users' access to adapt to spectrum dynamics to improve spectrum efficiency. However, users competing for an open spectrum may have no incentive to cooperate with each other, and they may even exchange false private information about their channel conditions in order to get more access to the spectrum. Therefore, in this paper, we propose a self-enforcing truth-telling mechanism by modeling the distributed spectrum access as a repeated game. In this game, if any greedy user deviates from cooperation, punishment will be triggered. Through the Bayesian mechanism design, users have no incentive to reveal false channel conditions, and the competing users are enforced to cooperate with each other honestly. The simulation results show that the proposed scheme can greatly improve the spectrum efficiency by alleviating mutual interference; furthermore, the best strategy for each user is demonstrated to be reporting the actual channel condition.

In this paper, we aim to design a set of linear transmitter preceding vectors for the downlink of multiuser MIMO system, using the maximal signal to jamming and noise ratio (SJNR) criterion for each user, subject to a transmit power constraint. Unlike some conventional methods, the proposed scheme does not impose any restrictions on system configuration, i.e., the number of antennas at the transmitter and receivers. Furthermore, this new algorithm can mitigate the co-channel interference (CCI) and noise at the same time. Both analysis and simulation results have shown the superiority of the proposed method over conventional transmit precoders.