Cooperative Wireless Powered Communication Networks With Interference Harvesting

Shin, Wonjae,Vaezi, Mojtaba,Lee, Jungwoo,Poor, H. Vincent IEEE 2018 IEEE Transactions on Vehicular Technology VT Vol.67 No.4

<P>A cooperative wireless-powered communication network protocol is proposed, in which user far away from a hybrid access point (H-AP) is capable of harvesting wireless powers by overhearing the uplink signals of users that are relatively nearer to the H-AP, in addition to downlink signal broadcast by the H-AP. In this setting, time allocations for the downlink transmission of the H-AP and the uplink transmission for the users are jointly optimized for two different purposes. First, the <I>weighted sum-rate maximization</I> problem is solved for a given total transmission time. Then, the <I>total transmission time</I> is minimized under a minimum rate constraint, and an efficient algorithm is also presented to solve the optimal solution by a line search strategy. Numerical results demonstrate that the proposed schemes significantly increase the far user's rate, which in turn improves user fairness and transmission delay.</P>

State Encoding of Hidden Markov Linear Prediction Models

Krishnamurthy, Vikram,Poor, H.Vincent The Korean Institute of Communications and Informa 1999 Journal of communications and networks Vol.1 No.3

In this paper, we derive finite-dimensional non-linear fil-ters for optimally reconstructing speech signals in Switched Predic-tion vocoders, Code Excited Linear Prediction(CELP) and Differ-ential Pulse Code Modulation (DPCM). Our filter is an extension of the Hidden Markov filter.

Scheduling Algorithms for Downlink Rate Allocation in Heterogeneous CDMA Networks

Varsou, Aikaterini C.,Poor, H. Vincent The Korea Institute of Information and Commucation 2002 Journal of communications and networks Vol.4 No.3

The downlink rate scheduling problem is considered for CDMA networks with multiple users carrying packets of heterogeneous traffic (voice/audio only, bursty data only or mixed traffic), with each type having its own distinct quality of service requirements. Several rate scheduling algorithms are developed, the common factor of which is that part of the decision on which users to serve is based on a function of the deadline of their head-ofline packets. An approach of Andrews et al., in which the basic Earliest-Deadline-First algorithm is studied for similar systems, is extended to result in better performance by considering a more efficient power usage and by allowing service of more than one user per timeslot if the power resources permit it. Finally, the performance of the proposed schemes is compared through simulations.

Cognitive Hierarchy Theory for Distributed Resource Allocation in the Internet of Things

Abuzainab, Nof,Saad, Walid,Hong, Choong Seon,Poor, H. Vincent IEEE 2017 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS Vol.16 No.12

<P>In this paper, the problem of distributed resource allocation is studied for an Internet of Things (IoT) system, composed of a heterogeneous group of nodes compromising both machine-type devices (MTDs) and human-type devices (HTDs). The problem is formulated as a noncooperative game between the heterogeneous IoT devices which seek to find the optimal time allocation so as to meet their quality-of-service (QoS) requirements in terms of energy, rate, and latency. Since the strategy space of each device is dependent on the actions of the other devices, the generalized Nash equilibrium (GNE) solution is first characterized, and the conditions for uniqueness of the GNE are derived. Then, to explicitly capture the heterogeneity of the devices, in terms of resource constraints and QoS needs, a novel and more realistic game-theoretic approach, based on the behavioral framework of cognitive hierarchy (CH) theory, is proposed. This approach is then shown to enable the IoT devices to reach a CH equilibrium (CHE), a concept that takes into account the various levels of rationality corresponding to the heterogeneous computational capabilities and the information accessible for each one of the MTDs and HTDs. Simulation results show that the CHE solution maintains a stable performance. In particular, the proposed CHE solution keeps the percentage of devices with satisfied QoS constraints above 96% for IoT networks containing up to 10000 devices without considerably degrading the overall system performance in terms of the total utility. Simulation results also show that the proposed CHE solution brings a two-fold increase in the total rate of HTDs and deceases the total energy consumed by MTDs by 78% compared with the equal time policy.</P>

Sensor Configuration and Activation for Field Detection in Large Sensor Arrays

Sung, Youngchul,Zhang, Xin,Tong, Lang,Poor, H. Vincent IEEE 2008 IEEE transactions on signal processing Vol.56 No.2

<P> The problem of sensor configuration for the detection of correlated random fields using large sensor arrays is considered. Using error exponents that characterize the asymptotic behavior of the optimal detector, the detection performance of different sensor configurations is analyzed and compared. The dependence of the optimal configuration on parameters such as sensor signal-to-noise ratio (SNR), field correlation, etc., is examined, yielding insights into the most effective choices for sensor selection in various operating conditions. Simulation results validate the analysis based on asymptotic results for finite sample cases. </P>

An Auctioning Mechanism for Green Radio

Comaniciu, Cristina,Mandayam, Narayan B.,Poor, H. Vincent,Gorce, Jean-Marie The Korea Institute of Information and Commucation 2010 Journal of communications and networks Vol.12 No.2

In this paper, an auctioning strategy is proposed for cellular networks that ensures net energy savings. The pricing scheme, in conjunction with a two dimensional bid structure, incentivizes cooperation at the terminal nodes for better interference management at receivers and for cooperative relaying. It is shown that, for the proposed auctioning strategy, network operators are guaranteed revenue gains, mobile nodes' dominant strategy is to bid their true valuation of their energy resources, and overall effective energy gains occur under the assumption of a reserve price for bidding. Simulation results show that significant energy savings can be achieved by employing this auctioning mechanism for a 3G cellular set-up.

An Auctioning Mechanism for Green Radio

Cristina Comaniciu,Narayan B. Mandayam,H. Vincent Poor,Jean-Marie Gorce 한국통신학회 2010 Journal of communications and networks Vol.12 No.2

In this paper, an auctioning strategy is proposed for cellular networks that ensures net energy savings. The pricing scheme,in conjunction with a two dimensional bid structure, incentivizes cooperation at the terminal nodes for better interference management at receivers and for cooperative relaying. It is shown that, for the proposed auctioning strategy, network operators are guaranteed revenue gains, mobile nodes’ dominant strategy is to bid their true valuation of their energy resources, and overall effective energy gains occur under the assumption of a reserve price for bidding. Simulation results show that significant energy savings can be achieved by employing this auctioning mechanism for a 3G cellular set-up.

Relay-Aided Space-Time Beamforming for Interference Networks With Partial Channel Knowledge

Shin, Wonjae,Lee, Namyoon,Lee, Jungwoo,Poor, H. Vincent Institute of Electrical and Electronics Engineers 2016 IEEE transactions on signal processing Vol.64 No.19

<P>This paper proposes a novel multiantenna relay-aided interference management technique that requires limited channel knowledge for interference relay channels, which is referred to as <I>relay-aided space-time beamforming (r-STBF) </I>. Using the proposed method, it is shown that <TEX>$\frac{KM}{K+M-1}$</TEX> multiplexing gain is achievable in a <TEX>$K$</TEX>-user multiple-input single-output (MISO) interference relay channel when the relay has <TEX>$M$</TEX> antennas with a certain type of limited channel knowledge. By leveraging this result, it is demonstrated that the <I>interference-free</I> multiplexing gain of <TEX>$K$</TEX> is asymptotically achievable as <TEX>$M$</TEX> approaches infinity. Furthermore, the proposed r-STBF method is shown to achieve the <I>optimal</I> multiplexing gain of <TEX>$\frac{KL}{K+L-1}$</TEX> for a <TEX>$K\times L$</TEX> single-input single-output (SISO) <TEX>$X$</TEX> channel with an <TEX>$M$</TEX>-antenna relay. One major implication of these results is that the use of a relay is beneficial in obtaining the <I>optimal</I> multiplexing gains for relay-aided interference networks even with limited channel knowledge, which bridges the theory-practice gap by implementing advanced interference management methods with less overhead for practical wireless systems.</P>

High Capacity Relay Protocols for Wireless Networks (Invited Paper)

Yijia Fan,Ioannis Krikidis,Chao Wang,John S. Thompson,H. Vincent Poor 한국통신학회 2009 Journal of communications and networks Vol.11 No.2

Over the last five years, relaying or multihop techniques have been intensively researched as means for potentially improving link performance of wireless networks. However, the data rates of relays are often limited because they cannot transmit and receive on the same frequency simultaneously. This limitation has come to the attention of researchers, and recently a number of relay techniques have been proposed specifically to improve the data efficiency of relaying protocols. This paper surveys transmission protocols that employ first single relays, then multiple relays and finally multiple antenna relays. A common feature of these techniques is that novel signal processing techniques are required in the relay network to support increased data rates. This paper presents results and discussion that highlight the advantages of these approaches.

Modeling COVID-19 with Mean Field Evolutionary Dynamics: Social Distancing and Seasonality

Hao Gao,Wuchen Li,Miao Pan,Zhu Han,H. Vincent Poor 한국통신학회 2021 Journal of communications and networks Vol.23 No.5

The coronavirus pandemic has been declared a world health emergency by the World Health Organization, which has raised the importance of an accurate epidemiological model to predict the evolution of COVID-19. In this paper, we propose mean field evolutionary dynamics (MFEDs), inspired by optimal transport theory and mean field games on graphs, to model the evolution of COVID-19. In the MFEDs, we derive the payoff functions for different individual states from the commonly used replicator dynamics (RDs) and employ them to govern the evolution of epidemics. We also compare epidemic modeling based on MFEDs with that based on RDs through numerical experiments. Moreover, we show the efficiency of the proposed MFED-based model by fitting it to the COVID-19 statistics of Wuhan, China. Finally, we analyze the effects of one-time social distancing as well as the seasonality of COVID- 19 through the post-pandemic period.