Performance Analysis of Network Coding with Exponential back off Algorithm Using Multi Path Transfer Protocol in Wireless Network

Network coding is an effective technique to boost the capacity of wireless networks. In that network, transmitted data is encoded and decoded to increase network throughput and to reduce end to end delay and make the network more robust. In this paper, the throughput and end to end delay of network coding is investigated under IEEE802.11 DCF. It is proposed that this can be achieved with CSMA/CA as in IEEE802.11 distributed coordination function with Multi Path Transfer Protocol (DCF-MPTP). CSMA/CA is based on the combination of physical carrier sensing and exponential back off algorithm. Proposed model prevents the delay and packed loss

Minimizing End-to-End Delay and Maximizing Reliability using Multilayer Neural Network-based Hamming Back Propagation for Efficient Communication in WSN

Wireless sensor network (WSN) comprises number of spatially distributed sensor nodes for monitoring the physical environment conditions and arranging the gathered data at central location. WSN gained large attention in medical field, industry, military, etc. However, congestion control mechanism for communication between sensor nodes failed to consider the end-to-end delay features. In addition, it failed to handle reliability and not achieved the data concurrency. In order to address the above mentioned problems, Multilayer Neural Network-based Hamming Back Propagation (MNN-HBP) technique is introduced for efficient communication in WSN. In MNN-HBP technique, Amorphous View Point Algorithm is introduced for sensor node initialization for efficient communication in WSN. Amorphous View Point Algorithm used time of arrival to measure the time distance between the sender node and receiver node. After that Hamming Back Propagation Algorithm is used to identify the current location of the sensor nodes for minimizing the end-to end delay and improving the reliability. Each sensor node compares their distance with the neighbouring sensor nodes distance to identify the associated error. When the distance is higher, the associated error is higher and propagates error back to other sensor nodes in the previous layers. The process gets repeated until the communication established between source sensor and lower associated error nodes. By this way, efficient communication is carried out with higher reliability and minimum end-to end delay. Extensive simulation are conducted to illustrate the efficiency of proposed technique as well as the impacts of network parameters on end-to-end delay, reliability and data packets successful rate with respect to data packet size and number of data packets

5G無線通信における誤り訂正符号化方式の評価に関する研究

早大学位記番号:新8267早稲田大

Large-Scale Site and Frequency Diversity in Urban Peer-to-Peer Channels for Six Public Safety Frequency Bands

We report on peer-to-peer large-scale wireless channel characteristics for an urban environment in six public-safety bands, for five simultaneous receiving sites. Results are based upon measurements taken in Denver in July 2009 with stationary receivers and a pedestrian transmitter. The six frequencies at which we measured are (in MHz) 430, 750, 905, 1834, 2400, and 4860. We quantify both site and frequency diversity, and show that 5-site selection yields minimum average gains of 15 dB in mean received power levels; 5-site selection diversity also reduces received power variation by 17-29 dB, depending on frequency. Frequency diversity yields similar gains. By approximating received powers as lognormal, we describe an analytical method to approximate the cdf of the per-site, or per-frequency (or both) maximum received power. These data and diversity models should be useful for public-safety and ad hoc communication system designers, and for cooperative diversity schemes, wherein multiple users act as a virtual array

Network performance & Quality of service in data networks involving spectrum utilization techniques

This research has developed technique to improve the quality of service in wireless data networks that employ spectrum utilization techniques based on Cognitive Radio. Most multiple dimension implementations focus on maximizing the Successful Communication Probability SCP in order to improve the wireless network utilization. However this usually has a negative impact on the Quality of Service, since increasing the SCP leads to increasing signal interference and Packet Loss, and thus network performance deterioration. The Multiple Dimension Cognitive Radio technique is a new technique, proposed in this thesis, that improves the Cognitive Radio Networks (CRN) efficiency by giving opportunity to secondary users (Unlicensed users) to use several dimension such as time, frequency, modulation, coding, and antenna directionality to increase their opportunity in finding spectrum hole. In order to draw a balance between improving the networking utilization and keeping the network performance at an acceptable level, this thesis proposes a new model of multiple dimension CR which provides a compromise between maximizing the SCP and network throughput from one side and keeping the QoS within the accepted thresholds from the other side. This is important so as to avoid network performance degradation which may result from the high user density in single wireless domain as a result of maximizing the SCP. In this research, a full Cognitive Radio model has been implemented in the OPNET simulator by developing modified nodes with the appropriate coding which include basic functionality. The Purpose of this model is to simulate the CR environment and study the network performance after applying the controlled multi dimension technique presented here. The proposed technique observes the channel throughput on TCP (Transmission Control Protocol) level, also QoS KPIs (Key Performance Index) like Packet Loss and Bit Error rate, during the operation of the CR multi dimension technique and alerts the system when the throughput degrades below a certain level. The proposed technique has interactive cautious nature which keeps monitoring the network performance and once find evident on network performance deterioration it takes corrective action, terminates low priority connections and releases over utilized channels, in order to keep the performance accepted

Optimal Power Allocation for Energy Efficient MIMO Relay Systems in 5G Wireless Communication

Wireless communication has undergone a significant growth to meet the unexpected demand of wireless data traffic over the past two decades. As manifested by the revolution of the third and fourth generations and long-term evolution advanced (LTE-A), engineers and researchers have been devoted to the development of the next-generation (5G) wireless solutions to meet the anticipated demand of 2020. To this end, cooperative relay communication has been introduced as an enabling technology to increase the throughput and extend the coverage of the broadband wireless networks. Decode-and-forward (DF) has been known as an effective cooperative relaying strategy for its outstanding features. On the other hand, merging massive multi-input-multi-output (MIMO) with cooperative DF relay is considered as a key technology for 5G wireless networks to improve the quality-of-service (QoS) in a cost-effective manner. The objective of this thesis is to establish and solve a power allocation optimization problem for energy efficient multi-pair DF relay systems integrated with massive MIMO. The first part of the thesis is focused on a constrained optimization problem to minimize the total transmit power for each transmission phase of the DF relay. Due to the non-convexity characteristic, the objective function is approximated as a convex function by means of complementary geometric programming (CGP) which is then solved by a sequence of geometric programming (GP). A lower bound of average SINR is also introduced by adopting the MMSE channel state information (CSI) to relax the constraint functions in the standard GP form. Finally, we proposed a homotopy or continuation method based algorithm to solve the optimization problem via popular CVX optimization toolbox. MATLAB simulations are conducted to validate the proposed algorithm. In the second part, another optimization problem is presented for the entire two-hop transmission of the DF relay to improve the global energy efficiency (GEE) under different channel conditions. Here, we estimate the channel by maximum likelihood (ML) criterion and investigate a closed-form expression of GEE. Further, GEE is approximated in a convex form by applying CGP due to the difficulty arising from the non-convexity and a lower bound of the average SINR expression is also derived to relax the constraint functions in the GP problem. Numerical results showing a detailed comparison of GEE under ML and MMSE channel estimation conditions and the performance improvement from the proposed algorithm are provided