Christian Ibars

Distributed Demand Management in Smart Grid with a Congestion Game

In this paper we propose distributed load management in smart grid infrastructures to control the power demand at peak hours, by means of dynamic pricing strategies. The distributed solution that we propose is based on a network congestion game, which can be demonstrated to converge in a finite number of steps to a pure Nash equilibrium solution. We take advantage of the remarkable property of congestion games, according to which they are equivalent to potential games. We define a potential function characterized by a meaningful physical interpretation, so that we obtain the favorable result that the optimal local solution of each selfish consumer is also the solution of a global objective. We evaluate this approach for managing both the demand and the grid load and we show that load control can be effectively achieved implementing a distributed solution, which significantly reduce the signaling burden over the network.

Distributed cooperation among cognitive radios with complete and incomplete information

This paper proposes that secondary unlicensed users are allowed to opportunistically use the radio spectrum allocated to the primary licensed users, as long as they agree on facilitating the primary user communications by cooperating with them. The proposal is characterized by feasibility since the half-duplex option is considered, and incomplete knowledge of channel state information can be assumed. In particular, we consider two situations, where the users in the scenario have complete or incomplete knowledge of the surrounding environment. In the first case, we make the hypothesis of the existence of a Common Control Channel (CCC) where users share this information. In the second case, the hypothesis of the CCC is avoided, which improves the robustness and feasibility of the cognitive radio network. To model these schemes we make use of theory of exact and Bayesian potential games. We analyze the convergence properties of the proposed games, and we evaluate the outputs in terms of quality of service perceived by both primary and secondary users, showing that cooperation for cognitive radios is a promising framework and that the lack of complete information in the decision process only slightly reduces system performance.

Distributed Cooperation in Cognitive Radio Networks: Overlay Versus Underlay Paradigm

This paper studies the benefits that cooperation brings to a cognitive radio network. The proposal in this paper considers that secondary unlicensed users are allowed to opportunistically use the radio spectrum allocated to the primary licensed users, as long as they agree on facilitating the primary user communications by cooperating with them. We refer to this approach as overlay paradigm for cognitive radio and we compare this to the underlay paradigm, according to which cooperation techniques among primary and secondary users are not exploited. To model these schemes we make use of theory of exact potential games. We analyze the convergence properties of the proposed games and we evaluate the outputs in terms of quality of service perceived by both primary and secondary users, outage probability and interference temperature, showing that the overlay paradigm for cognitive radio is a promising framework.

Full length article: MIMO channel modeling and transmission techniques for multi-satellite and hybrid satellite-terrestrial mobile networks

The Quality of Service (QoS) in land mobile satellite (LMS) communications drops drastically in the presence of shadowing and multipath fading. This paper studies two promising multiple-input multiple-output (MIMO) schemes, along with specific transmission techniques, aimed at overcoming this problem. First, specific proposals for a dual-satellite distributed MIMO scheme are studied based upon delay-tolerant and spectral-efficient schemes. As a second alternative, a hybrid satellite-terrestrial scheme is studied with specific proposals for MIMO processing. In order to carry out a performance assessment the paper addresses related MIMO satellite propagation channel modeling issues which lead to a new mathematical model to accommodate the multi-satellite transmission. In both cases, we quantify and conclude the MIMO gains in terms of bit error rate (BER) and spectral efficiency for urban and suburban environments. The transmitted air-interfaces in both proposed MIMO schemes are DVB-SH standard compatible. The analytical results have been validated by means of Monte Carlo simulations.

Medium access design for LTE in unlicensed band

In this paper, a medium access protocol suitably adapted for the operation of Long term evolution (LTE) in unlicensed band (LTE-U) is proposed. The MAC design considers the impact of LTE-U on the devices operating in unlicensed band, such as WiFi and legacy LTE. The LTE-U design differences from the legacy LTE system, an inherently a synchronized, tightly controlled system are explored. The performance of LTE-U is studied via a detailed system level simulator implementation and 3GPP simulation test scenarios. We show that our proposed MAC design enables high throughput in unlicensed band and achieves co-existence with the incumbent systems. Moreover, the use of channel reservation mechanisms is shown to improve LTE-U cell edge performance.

Network‐coded diversity protocol for collision recovery in slotted ALOHA networks

SUMMARY We propose a collision recovery scheme for symbol-synchronous slotted ALOHA based on physical layer network coding over extended Galois fields. Information is extracted from colliding bursts allowing to achieve higher maximum throughput with respect to previously proposed collision recovery schemes. An energy efficiency analysis is also performed, and it is shown that by adjusting the transmission probability, high energy efficiency can be achieved. A performance evaluation is carried out using the proposed algorithms, revealing remarkable performance in terms of normalized throughput. Copyright

Performance analysis of LTE and Wi-Fi in unlicensed band using stochastic geometry

In this paper, the multi-channel performance of large scale deployment of Long Term Evolution (LTE) in Unlicensed (LTE-U) band and WiFi using stochastic geometry is studied. LTE-U and WiFi cell placement is modeled as a Poisson Point Process (PPP), while transmission activity is modeled as hardcore simple sequential inhibition (SSI) point processes, which have been shown to accurately model Carrier sense multiple access (CSMA) access. This stochastic geometry based framework is used to analyze the co-existence of LTE-U and WiFi systems operating in the same set of available channels in unlicensed band. Several interesting results are derived. First, it is shown that fair coexistence can be achieved by LTE-U implementing a Listen-Before-Talk (LBT) protocol. Different variations of LBT are explored to improve the co-existence. Secondly, it is shown that the classical hidden node problem can severely affect performance, and that channel selection mechanisms can significantly alleviate the problem.

On the throughput analysis of LTE and WiFi in unlicensed band

In this paper, the co-channel performance of large scale deployment of LTE in Unlicensed (LTE-U) band and WiFi is studied using stochastic geometry. Analytical expressions of LTE-U throughput in presence of WiFi are presented and are partly validated by the simulation results. The LTE-U Low Power Nodes (LPNs) are deployed as Poisson Point Process (PPP), and, the WiFi transmissions are modeled as hardcore Matérn point process. Using this analytical approach the impact of various parameters such as sensing threshold and transmission power on the co-existence of LTE-U and WiFi is studied.

Radio Resource Allocation for a High Capacity Vehicular Access Network

Vehicular networks will enable a high number of services in intelligent transportation systems, and are also expected to improve the availability of wireless services to vehicles. In this paper we address the problem of establishing a vehicular network with high capacity using 802.11 and/or DSRC, and in particular we focus on frequency allocation and power control. We advocate a regular frequency reuse pattern that guarantees SINR requirements of the air interface. Resulting co-channel interference is then reduced using an adaptive power control algorithm. Simulation results for a highway scenario reveal that high capacities are possible with moderate infrastructure access point density.

Potential Game for Energy-Efficient RSS-Based Positioning in Wireless Sensor Networks

Positioning is a key aspect for many applications in wireless sensor networks. In order to design practical positioning algorithms, employment of efficient algorithms that maximize the battery lifetime while achieving a high degree of accuracy is crucial. The number of participating anchor nodes and their transmit power have an important impact on the energy consumption of positoning a node. This paper proposes a game theoretical algorithm to optimize resource usage in obtaining location information in a wireless sensor network. The proposed method provides positioning and tracking of nodes using RSS measurements. We use the Geometric Dilution of Precision as an optimization metric for our algorithm, with the aim of minimizing the number and power of anchor nodes that collaborate in positioning, thus saving energy. The algorithm is shown to be a potential game, therefore convergence is guaranteed. A distributed low complexity solution for the implementation is presented. The game is applied to WSN and results show the trade-off between power saving and positioning error.