In this paper, we propose a consensus protocol by considering the ledger as Directed Acyclic Graph (DAG) called blockDAG instead of chain of blocks. We propose a two-step strategy for making the system robust to double-spend attacks. The first step is the graph clustering algorithm based on spectral graph theory for separating the blocks created by the non-cooperating miners (attacker) in the blockchain network followed by the second step-the ordering algorithm based on the topological ordering of the blockDAG using the references included in block header. The first step is an unsupervised learning classification of the vertices of a graph into two classes. The simulation results show that the proposed clustering Algorithm based consensus protocol counter-attack the attacker's double-spending strategy by eliminating the attacker blocks created during attacking phase from the confirmed list of the blocks. In bitcoin's longest chain rule protocol, the ledger takes the chain of blocks and it operates with the overestimation of the network's end-to-end propagation delay which results in a low transaction throughput. Bitcoin protocol guarantees the security through longest chain rule but it suffers from the limited transaction scalability. The proposed consensus protocol works better for higher block creation rates in turn improves the transaction throughput without compromising the security of the blocks from double-spending attack.

In this paper, exact statistics for the linear combination of gamma conditionally Gaussian random variables (CGRVs) are obtained. In particular, the probability density function (PDF), the cumulative distribution function (CDF) and the moment generating function (MGF) are derived. Closed form expressions are obtained for both integer and noninteger parameters, using the Mellin-Barnes integral representation of the extended Fox-H function. The significance of these results is then explained by obtaining performance metrics for decode and forward (DF) cooperation in Nakagami-m fading.

This demo describes the implementation of a peer to peer message chatting application in the android platform over Wireless Sensor Networks (WSNs). Using the IIT-H Zigbee motes we show how to interface the android platform with the Zigbee motes and the different modes of communications involved.

Exact expressions are obtained for the bit error rate (BER) for coherent and noncoherent decode and forward (DF) cooperative systems with upto three relays between the source and destination. The piecewise linear (PL) combiner is employed at the receiver. BER analysis is done using a contour integral approach for evaluating the Gil-Pelaez integral involving the characteristic function (CF) of the decision variable. This removes restrictions on relay location, imposed by the direct approach. Simulation results are provided to support the analysis and the relay diversity gain is demonstrated through BER plots.

The statistics of gamma conditionally Gaussian (CG) random variables are derived in closed form. These variables can be loosely defined to be normally distributed with mean and variance proportional to a gamma random variable. In this paper, we provide exact expressions for the bit error rate (BER) for single relay maximum likelihood (ML) decode and forward (DF) cooperative systems in Nakagami-m fading for binary phase shift keying (BPSK). This is done by expressing the ML decision variable in terms of functions of gamma CG random variables. For the piecewise linear (PL) approximation to the ML detector, a closed form expression for the BER is obtained. Simulation results are provided to verify the validity of the derived analytical expressions.

Maximum-likelihood (ML) detectors for single-input-single-output (SISO) relay systems are well known. In this paper, closed form expressions for the bit error rate (BER) for multiple-input-multiple-output (MIMO) relay systems employing ML based decode and forward (DF) cooperative diversity are obtained. The DF operation at the relay intelligently employs the multiple antennas available at the relay for receive diversity on the source-relay link and space-time coding (STC) on the relay-destination link resulting in an extension of the ML detection rule for SISO systems to MIMO systems as well. For the piecewise linear (PL) approximation to the ML detector, exact expressions for the BER are obtained for single-relay systems with both the source and relay supporting multiple antennas. For a multirelay system, each relay having multiple antennas, approximate expressions for the BER are obtained. This is done by finding the statistics of conditionally Gaussian (CG) random variables, that appear in the decision variable. Through numerical results obtained from the BER expressions, it is shown that using multiple antennas at the source as well as the relay leads to significant improvement in BER performance.

The bit error rate (BER) performance analysis of maximum-likelihood (ML) based decode and forward (DF) cooperative diversity systems has been a subject of considerable interest. Exact analysis of ML-DF transmission has been considered a challenging problem due to the nonlinear characteristic of the ML detector. In this paper, we provide exact expressions for the BER of ML-DF cooperative systems employing a single relay. We extend these results to the case of multiple relays for the piecewise linear (PL) combiner, that is known to be a close approximation of the ML detector. This is done by using a novel theory of conditionally Gaussian random variables. By expressing the ML decision variable in terms of functions of conditionally Gaussian variables, exact expressions for the BER of the ML-DF system are obtained. Through simulation results, we verify the validity of the derived analytical expressions.

Tight closed form lower bounds for the average bit error rate (BER) are derived for a dual hop cooperative network employing nonregenerative relays for the multiple input multiple output (MIMO) relay channel experiencing Rayleigh fading. The bounds are obtained for three different nonregenerative relaying schemes. The lower bounds for the BER are obtained using the moment generating function (MGF) approach by evaluating the MGF of the end-to-end equivalent signal to noise ratio (SNR) of the system. From the BER expressions obtained, we also show that the diversity order for the MIMO relay cooperative system with each relay having M antennas increases approximately by a factor M from that of a system with single-antenna relays. Simulation results confirm that the analytical expressions for the lower bounds are very tight and can thus be used to get approximate values of the BER.

Closed form expressions for the bit error rate (BER) for a multiple input multiple output (MIMO) relay system employing maximum likelihood (ML) based decode and forward (DF) cooperative diversity are obtained. The DF operation at the relay involves maximal ratio combining (MRC) on the source-relay link and space-time coding (STC) on the relay-destination link. Exact expressions of the BER are obtained for the case of a single relay supporting two antennas. For a system employing a large number of relays, each having two antennas, approximate expressions for the BER are obtained using the piecewise linear (PL) approximation for the ML detector. This is done by finding the statistics of conditionally Gaussian random variables, that appear in the decision variable. The validity of the analytical expressions is then verified through simulations. Through numerical results obtained from the BER expressions for large number of relays, it is then shown that the loss in diversity order due to DF can be compensated by using multiple antennas at the relay.

Antenna sharing by multiple users using cooperative diversity has been shown to mimic the performance of traditional multiple input, multiple output (MIMO) systems. While this was originally done using a single antenna at each relay, the benefits of cooperative diversity based on multiantenna relays has been a subject of considerable interest. Maximum likelihood (ML) detectors for cooperative diversity through single antenna relays are well known. In this paper, we propose to combine the benefits of cooperative diversity, and transmit and receive diversity offered by MIMO systems. This is done within the ML based decode and forward (DF) cooperative diversity framework, by using multiple antennas at each relay, through ML based processing on the source-relay link and space-time coding on the relay-destination link. Through simulations, we then show that the performance of MIMO relay based systems is superior to those having a single antenna at each relay.

In this correspondence, we average , where is the Euclidean norm of an complex circularly Gaussian vector . This is done by finding the characteristic function of the decision variable and subsequently applying the Gil-Pelaez theorem to obtain a one-dimensional real integral. The integral is then converted to a contour integral which is evaluated using a variant of the Cauchy's integral formula to obtain an expression for , where is the expectation operator.

Code division multiple access (CDMA) and orthogonal frequency division multiplexing (OFDM) are two techniques that are being commonly used in most wireless communication systems. In this paper we examine the coexistence of the above schemes through a two user communication system, i.e., one user transmits using CDMA and the other transmits using OFDM. Using an OFDM based receiver, we derive the received symbols at the output of each branch of the OFDM demodulator. The symbols transmitted by the CDMA user are then detected using the minimum power distortionless response (MPDR) approach, an array processing technique commonly used in beamforming. Through simulations, we then show that the MPDR method is indeed very efficient in suppressing the OFDM interference