Maximum Euclidean distance network coded modulation for asymmetric decode-and-forward two-way relaying

Network coding (NC) compresses two traffic flows with the aid of low-complexity algebraic operations, hence holds the potential of significantly improving both the efficiency of wireless two-way relaying, where each receiver is collocated with a transmitter and hence has prior knowledge of the message intended for the distant receiver. In this contribution, network coded modulation (NCM) is proposed for jointly performing NC and modulation. As in classic coded modulation, the Euclidean distance between the symbols is maximised, hence the symbol error probability is minimised. Specifically, the authors first propose set-partitioning-based NCM as an universal concept which can be combined with arbitrary constellations. Then the authors conceive practical phase-shift keying/quadrature amplitude modulation (PSK/QAM) NCM schemes, referred to as network coded PSK/QAM, based on modulo addition of the normalised phase/amplitude. To achieve a spatial diversity gain at a low complexity, a NC oriented maximum ratio combining scheme is proposed for combining the network coded signal and the original signal of the source. An adaptive NCM is also proposed to maximise the throughput while guaranteeing a target bit error probability (BEP). Both theoretical performance analysis and simulations demonstrate that the proposed NCM can achieve at least 3 dB signal-to-noise ratio gain and two times diversity gain

Network coded modulation for two-way relaying

Network coding compresses multiple traffic flows with the aid low-complexity algebraic operations, hence holds the potential of significantly improving both the power and bandwidth efficiency of wireless networks. In this contribution, the novel concept of Network Coded Modulation (NCM) is proposed for jointly performing network coding and modulation in bi-directional/duplex relaying. Each receiver is colocated with a transmitter and hence has prior knowledge of the message intended for the distant receiver. As in classic coded modulation, the Euclidian distance between the symbols is maximized, hence the Symbol Error Ratio (SER) is minimized. Specifically, we conceive NCM methods for PSK, PAM and QAM based on modulo addition of the normalized phase or amplitude. Furthermore, we propose low complexity decoding algorithms based on the corresponding conditional minimum distance criteria. Our performance analysis and simulations demonstrate that NCM relying on PSK is capable of achieving a SER at both receivers of the NCM scheme as if the relay transmitted exclusively to a single receiver only. By contrast, when our NCM concept is combined with PAM/QAM, an SNR loss (<1.25dB) is imposed at one of the receivers, usually at the one having a lower data rate in a realistic different rate scenario. Finally, we will demonstrate that the proposed NCM is compatible with existing physical layer designs

Coalitional Game Theoretic Approach for Cooperative Transmission in Vehicular Networks

Cooperative transmission in vehicular networks is studied by using coalitional game and pricing in this paper. There are several vehicles and roadside units (RSUs) in the networks. Each vehicle has a desire to transmit with a certain probability, which represents its data burtiness. The RSUs can enhance the vehicles' transmissions by cooperatively relaying the vehicles' data. We consider two kinds of cooperations: cooperation among the vehicles and cooperation between the vehicle and RSU. First, vehicles cooperate to avoid interfering transmissions by scheduling the transmissions of the vehicles in each coalition. Second, a RSU can join some coalition to cooperate the transmissions of the vehicles in that coalition. Moreover, due to the mobility of the vehicles, we introduce the notion of encounter between the vehicle and RSU to indicate the availability of the relay in space. To stimulate the RSU's cooperative relaying for the vehicles, the pricing mechanism is applied. A non-transferable utility (NTU) game is developed to analyze the behaviors of the vehicles and RSUs. The stability of the formulated game is studied. Finally, we present and discuss the numerical results for the 2-vehicle and 2-RSU scenario, and the numerical results verify the theoretical analysis.Comment: accepted by IEEE ICC'1

A Cross-layer Perspective on Energy Harvesting Aided Green Communications over Fading Channels

We consider the power allocation of the physical layer and the buffer delay of the upper application layer in energy harvesting green networks. The total power required for reliable transmission includes the transmission power and the circuit power. The harvested power (which is stored in a battery) and the grid power constitute the power resource. The uncertainty of data generated from the upper layer, the intermittence of the harvested energy, and the variation of the fading channel are taken into account and described as independent Markov processes. In each transmission, the transmitter decides the transmission rate as well as the allocated power from the battery, and the rest of the required power will be supplied by the power grid. The objective is to find an allocation sequence of transmission rate and battery power to minimize the long-term average buffer delay under the average grid power constraint. A stochastic optimization problem is formulated accordingly to find such transmission rate and battery power sequence. Furthermore, the optimization problem is reformulated as a constrained MDP problem whose policy is a two-dimensional vector with the transmission rate and the power allocation of the battery as its elements. We prove that the optimal policy of the constrained MDP can be obtained by solving the unconstrained MDP. Then we focus on the analysis of the unconstrained average-cost MDP. The structural properties of the average optimal policy are derived. Moreover, we discuss the relations between elements of the two-dimensional policy. Next, based on the theoretical analysis, the algorithm to find the constrained optimal policy is presented for the finite state space scenario. In addition, heuristic policies with low-complexity are given for the general state space. Finally, simulations are performed under these policies to demonstrate the effectiveness

Rebels Lead to the Doctrine of the Mean: Opinion Dynamic in a Heterogeneous DeGroot Model

We study an extension of the DeGroot model where part of the players may be rebels. The updating rule for rebels is quite different with that of normal players (which are referred to as conformists): at each step a rebel first takes the opposite value of the weighted average of her neighbors' opinions, i.e. 1 minus that average (the opinion space is assumed to be [0,1] as usual), and then updates her opinion by taking another weighted average between that value and her own opinion in the last round. We find that the effect of rebels is rather significant: as long as there is at least one rebel in every closed and strongly connected group, under very weak conditions, the opinion of each player in the whole society will eventually tend to 0.5.Comment: 7 pages, Proceedings of The 6th International Conference on Knowledge, Information and Creativity Support Systems, Beijing, 201

Charging Scheduling of Electric Vehicles with Local Renewable Energy under Uncertain Electric Vehicle Arrival and Grid Power Price

In the paper, we consider delay-optimal charging scheduling of the electric vehicles (EVs) at a charging station with multiple charge points. The charging station is equipped with renewable energy generation devices and can also buy energy from power grid. The uncertainty of the EV arrival, the intermittence of the renewable energy, and the variation of the grid power price are taken into account and described as independent Markov processes. Meanwhile, the charging energy for each EV is random. The goal is to minimize the mean waiting time of EVs under the long term constraint on the cost. We propose queue mapping to convert the EV queue to the charge demand queue and prove the equivalence between the minimization of the two queues' average length. Then we focus on the minimization for the average length of the charge demand queue under long term cost constraint. We propose a framework of Markov decision process (MDP) to investigate this scheduling problem. The system state includes the charge demand queue length, the charge demand arrival, the energy level in the storage battery of the renewable energy, the renewable energy arrival, and the grid power price. Additionally the number of charging demands and the allocated energy from the storage battery compose the two-dimensional policy. We derive two necessary conditions of the optimal policy. Moreover, we discuss the reduction of the two-dimensional policy to be the number of charging demands only. We give the sets of system states for which charging no demand and charging as many demands as possible are optimal, respectively. Finally we investigate the proposed radical policy and conservative policy numerically

Applications and Study on Organophosphate Acids (Salts) for Oil Well Cement Retarder

AbstractA synthetic cement retarder SDH-2 which provides excellent retardation and compressive strength development has been synthesized to be used in deep oil well cementation. The response properties, temperature-resistant and anti-salt properties, additive distribution and compressive strength have been evaluated. It is showed SDH-2 has good retarding ability to oil well cement slurries at 40 to 204 ℃。It is compatible with dispersant, fluid loss additive and other additives to grade G oilwell cement of various manufactures and can be used in cementing process in the temperature of various depths in oil well