Power line communication (PLC) networks play an important role in home networks and in next generation hybrid networks, which provide higher data rates (Gbps) and easier connectivity. The standard medium access control (MAC) protocol of PLC networks, IEEE 1901, uses a special carrier sense multiple access with collision avoidance (CSMA/CA) mechanism, in which the deferral counter technology is introduced to avoid unnecessary collisions. Although PLC networks have achieved great commercial success, MAC layer analysis for IEEE 1901 PLC networks received limited attention. Until now, a few studies used renewal theory and strong law of large number (SLLN) to analyze the MAC performance of IEEE 1901 protocol. These studies focus on saturated conditions and neglect the impacts of buffer size and traffic rate. Additionally, they are valid only for homogeneous traffic. Motivated by these limitations, we develop a unified and scalable analytical model for IEEE 1901 protocol in unsaturated conditions, which comprehensively considers the impacts of traffic rate, buffer size, and traffic types (homogeneous or heterogeneous traffic). In the modeling process, a multi-layer discrete Markov chain model is constructed to depict the basic working principle of IEEE 1901 protocol. The queueing process of the station buffer is captured by using Queueing theory. Furthermore, we present a detailed analysis for IEEE 1901 protocol under heterogeneous traffic conditions. Finally, we conduct extensive simulations to verify the analytical model and evaluate the MAC performance of IEEE 1901 protocol in PLC networks.

This letter studies secure communication in a wireless powered communication network with a full-duplex destination node, who applies either power splitting (PS) or time switching (TS) to coordinate energy harvesting and information decoding of received signals and transmits jamming signals to the eavesdropper using the harvested energy. The secrecy rate is maximized by optimizing PS or TS ratio and power allocation. We propose iterative algorithms with power allocation optimized by the successive convex approximation method. Simulation results demonstrate that the proposed algorithms are superior to other benchmark algorithms.

Wireless powered communication networks (WPCNs) utilize the wireless energy transfer (WET) technique to facilitate the wireless information transmission (WIT) of nodes. We propose a two-step iterative algorithm to maximize the sum throughput of the users in a MIMO WPCN with discrete signal inputs. Firstly, the optimal solution of a convex power allocation problem can be found given a fixed time allocation; Secondly, a semi closed form solution for the optimal time allocation is obtained when fixing the power allocation matrix. By optimizing the power allocation and time allocation alternately, the two-step algorithm converges to a local optimal point. Simulation results show that the proposed algorithm outperforms the conventional schemes, which consider only Gaussian inputs.

In this letter, we study a wireless powered communication network (WPCN) with non-orthogonal multiple access (NOMA), where the user clustering scheme that groups each two users in a cluster is adopted to guarantee the system performance. The two users in a cluster transmit data simultaneously via NOMA, while time division multiple access (TDMA) is used among clusters. We aim to maximize the system throughput by finding the optimal cluster permutation and the optimal time allocation, which can be obtained by solving the optimization problems corresponding to all cluster permutations. The closed-form solution of each optimization problem is obtained by exploiting its constraint structures. However, the complexity of this exhaustive method is quite high, we further propose a sub-optimal clustering scheme with low complexity. The simulation results demonstrate the superiority of the proposed scheme.

This paper studies a wireless powered communication network (WPCN) with non-orthogonal multiple access (NOMA) under successive interference cancellation (SIC) constraints, where the users first harvest energy from the power station and then transmit data to the information receiver simultaneously. Under this setup, we investigate the system throughput maximization problem. We first formulate an optimization problem for a general case, which is non-convex. To derive the optimal solution, new variables are introduced to transform the initial problem into a convex optimization problem. For a special case, i.e., two-user case, the optimal solution is derived as a closed-form expression. Simulations on the effect of SIC constraints show the importance of the distinctness among users' channels for the proposed model.

This letter considers a backscatter assisted wireless powered communication network (BAWPCN) with non-orthogonal multiple access (NOMA). This model consists of a hybrid access point (HAP) and multiple users which can work in either backscatter or harvest-then-transmit (HTT) protocol. To fully exploit time for information transmission, the users working in the backscatter protocol are scheduled to reflect modulated signals during the first phase of the HTT protocol which is dedicated for energy transfer. During the second phase, all users working in the HTT protocol transmit information to the HAP simultaneously since NOMA is adopted. Considering both short-term and long-term optimization problems to maximize the system throughput, the optimal resource allocation policies are obtained. Simulation results show that the proposed model can significantly improve the system performance.

This letter introduces a new model for backscatter assisted wireless powered communication networks (BAWPCNs) that include a hybrid access point (HAP) and multiple backscatter communication (BackCom) and traditional wireless powered communication network (WPCN) users. To make full use of time to transmit information, both backscatter and harvest-then-transmit (HTT) modes are employed. In the proposed model, during the first time slot dedicated for energy transfer in traditional WPCNs, the traditional WPCN users harvest energy radiated by the HAP, and simultaneously the BackCom users reflect modulated signals to the HAP. The traditional WPCN users are scheduled during the remaining time slots via time division multiple access (TMDA). The optimal time allocation policies for the half-duplex (HD) and full-duplex (FD) BAWPCNs are obtained to maximize the system throughput. The tradeoff between backscatter and HTT modes is analyzed. Simulation results demonstrate the superiority of the proposed model.

In this paper, we propose a multi-cell structure backscatter based wireless-powered communication network (WPCN) where a number of backscatter cells are locally separated, each containing a subset of users around a carrier emitter. The multi-cell structure backscatter based WPCN can be implemented in two ways, namely time-division multiplexing (TDM) and frequency-division multiplexing (FDM). Here users harvest energy from the carrier signal transmitted by the carrier emitter, and then transmit their own information in a passive way via the reflection of the carrier signal using frequency-shift keying modulation. We characterize the energy-free condition and the signal-to-noise ratio (SNR) outage zone in a backscatter based WPCN. Also, a backscatter based harvest-then-transmit protocol is adopted to maximize the sum-throughput of all users by optimally allocating time for energy harvesting and information transmission. Numerical results demonstrate that the backscatter based WPCN ensures an increased long-range coverage and a diminished SNR outage zone compared to conventional radio based WPCNs. Also, comparing the two types of multi-cell structure backscatter based WPCN, TDM within each backscatter cell and FDM across backscatter cells versus FDM within each backscatter cell and TDM across backscatter cells, numerical results confirm that which one yields a better performance.

This paper introduces a communication system model with renewable power supply. As we assumed a battery-free microgrid system with conventional power as a backup power supply, we propose a method of power state and data transmission scheduling for delay-tolerant communication networks, which reduces conventional power consumption by operating adaptively to changes in renewable power. We found through computer simulations that the proposed method efficiently reduced conventional power consumption.

Genetic Algorithm (GA) and other Evolutionary Algorithms (EAs) have been successfully applied to solve constrained minimum spanning tree (MST) problems of the communication network design and also have been used extensively in a wide variety of communication network design problems. Choosing an appropriate representation of candidate solutions to the problem is the essential issue for applying GAs to solve real world network design problems, since the encoding and the interaction of the encoding with the crossover and mutation operators have strongly influence on the success of GAs. In this paper, we investigate a new encoding crossover and mutation operators on the performance of GAs to design of minimum spanning tree problem. Based on the performance analysis of these encoding methods in GAs, we improve predecessor-based encoding, in which initialization depends on an underlying random spanning-tree algorithm. The proposed crossover and mutation operators offer locality, heritability, and computational efficiency. We compare with the approach to others that encode candidate spanning trees via the Pr?fer number-based encoding, edge set-based encoding, and demonstrate better results on larger instances for the communication spanning tree design problems.

Long running software systems are known to experience an aging phenomenon called software aging, one in which the accumulation of errors during the execution of software leads to performance degradation and eventually results in failure. To counteract this phenomenon a proactive fault management approach, called software rejuvenation, is particularly useful. It essentially involves gracefully terminating an application or a system and restarting it in a clean internal state. In this paper, we evaluate dependability performance of a communication network system with the software rejuvenation under the assumption that the requests arrive according to a Markov modulated Poisson process (MMPP). Three dependability measures, steady-state availability, loss probability of requests and mean response time on tasks, are derived through the hidden Markovian analysis based on the time-based software rejuvenation scheme. In numerical examples, we investigate the sensitivity of some model parameters to the dependability measures.

We propose a new call admission control (CAC) scheme for voice calls in cellular mobile communication networks. It is assumed that the rejection of a hand-off call is less desirable than that of a new call, for a hand-off call loss would cause a severe mental pain to a user. We consider the pains of rejecting new and hand-off calls as different costs. The key idea of our CAC is to restrict the admission of new calls in order to minimize the total expected costs per unit time over the long term. An optimal policy is derived from a semi-Markov decision process in which the intervals between successive decision epochs are exponentially distributed. Based on this optimal policy, we calculate the steady state probability for the number of established voice connections in a cell. We then evaluate the probability of blocking new calls and the probability of forced termination of hand-off calls. In the numerical experiments, it is found that the forced termination probability of hand-off calls is reduced significantly by our CAC scheme at the slight expense of the blocking probability of new calls and the channel utilization. Comparison with the static guard channel scheme is made.

In a telecommunication network system, a scheme for reforwarding call-terminating setup messages (SETUP messages) is used to guard against their loss. We have developed a method for evaluating the loss probability of these reforwarding schemes. We started with a stochastic model in which the messages are reforwarded after a constant time span from the time that the first messages have been forwarded. This model corresponds to the finite-capacity BPP/M/1/m model. We showed a method for calculating the "timeout" probability. We then added an approximate method for calculating the loss probability. Finally, using the proposed methods, we clarified the existence of the best reforwarding timelag.

This paper discusses self-similarity in cell dwell time of a mobile terminal, the discovery of which was described in our previous paper, and its effects on teletraffic of mobile communication networks. We have evaluated various teletraffic statistics, such as cell dwell time and channel occupancy time, of a mobile terminal based on measurements of motion for various types of vehicles. Those results show that cell dwell time follows a long-tailed log-normal distribution rather than the exponential distribution that has been used for modeling. Here, we first elaborate on self-similarity in cell dwell time of various vehicles. We then evaluate self-similarity in channel occupancy time. For future mobile multimedia communication systems employing a micro-cell configuration, it is anticipated that data communication will be the main form of communication and that call holding time will be long. For such cases, we have shown that channel occupancy time will be greatly affected by the cell dwell time of the mobile terminal, and that self-similarity, a characteristic that is not seen in conventional systems, will consequently appear. We have also found that hand-off frequently fails as self-similarity in cell dwell time of a mobile terminal becomes stronger.

In evaluating the teletraffic of mobile communication networks, it is important to model the motion of terminals. In the previous migration model, mobility characteristics of terminals, such as cell dwell time, have been expressed by a single probability distribution. In this paper, we discuss the modeling of the cell dwell time of terminals in each cell. Using measured data we show that cell dwell time differs from cell to cell and follows log-normal distributions rather than conventional exponential distributions.

It is a fundamental problem to construct a virtual path layout minimizing the hop number as a function of the congestion for a communication network. It is known that we can construct a virtual path layout with asymptotically optimal hop number for a mesh of trees network, butterfly network, cube-connected-cycles network, de Bruijn network, shuffle-exchange network, and complete binary tree network. The paper shows a virtual path layout with minimum hop number for a complete binary tree network. A generalization to complete k-ary tree networks is also mentioned.

Teletraffic characteristics of a mobile packet communication network, which supports mobile Internet, were quantitatively evaluated by using a terminal migration model in which the cell dwell time possesses self-similarity. I used a migration model in which the migration speed of the terminal is determined by the density of the dwell terminals in a cell (determined from measured vehicular mobility characteristics). The transmission rates per terminal in a cell were estimated as teletraffic on the mobile packet communication networks using this migration model. I found that when there is self-similarity in the terminal cell dwell time, communicating terminals may be concentrated in the cell and restricted for an indefinite period of time to using only a narrow bandwidth.

We describe a control scheme for wireless-link layers and the TCP/IP layers in which wireless link states, such as signal strength and transmission rate, are transparent to the upper network layers and govern the behavior of the upper layers. Monitoring and notifying functions for wireless link states are incorporated into mobile hosts, and prefetching functions for the mobility agent lists are added to the present MobileIP functionalities of the network layers. In addition, we give the mobile hosts functions for controlling the TCP advertised windows in the transport layers and give the base-stations buffering functions to deal with the variable signal strength of the wireless links. A simulation (using ns-2) of this control scheme shows that mobile agent can be switched at the network layers soon after base-station hand-over and that errors in packet routing, packet loss and communication throughput reduction can be avoided. Moreover, communications can be interrupted without having to shrink the size of the congestion windows of the TCP senders, which improves overall throughput.

In this paper, we propose a call arrival history-based location tracking strategy for a variable call arrival rate over time. The basis of the proposed strategy is a time-based location tracking strategy. A mobile terminal obtains the up-to-date information about changes in the call arrival rate by maintaining its call arrival history, from which it can calculate an appropriate timeout interval for a variable call arrival rate. We present a simple analytical model and numerical results to investigate its performance for both a fixed and a variable call arrival rate which is modeled by a Markov-modulated Poisson process.

In this paper, we study the link capacity assignment problem in packet-switched networks (CA problem) focusing on the case where link cost function is a piecewise linear concave function. This type of cost function arises in many communication network design problems such as those arising from developments in communication transmission technologies. It is already known that the method of link set assignment is applicable for solving the CA problem with piecewise linear convex cost function. That is, each link in the network is assigned to one of a group of specific sets, and checked for link set contradiction. By extending the method of link set assignment to the case of piecewise linear concave cost function, an important characteristic of the optimal solution of the CA problem is derived. Based on this characteristic, the non-differentiable link cost function can be treated as a differentiable function, and a heuristic algorithm derived from the Lagrange multiplier method is then proposed. Although it is difficult to determine the global optimum of the CA problem due to its non-convexity, it is shown by numerical results that the solution obtained from the proposed algorithm is very close to the global optimum. Moreover, the computation time is linearly dependent on the number of links in the problem. These performances show that the proposed algorithm is very efficient in solving the CA problem, even in the case of large-scale networks.