We present a novel transmission rate control method for Wireless Mesh Networks, termed Semi-Fixed Rate Control (SFRC), which incorporates the advantages of Fixed Rate Control (FRC) and Adaptive Rate Control (ARC). SFRC has two periods, which are alternately repeated: an autorate period and a fixed-rate period. A unit of an autorate period and the successive fixed-rate period is termed “rate-control period”. The duration of the rate-control period is set considerably longer than that of the autorate period. In the autorate period, RTS/CTS is used with the lowest transmission rate, transmission rate adjustment is only applied to data frames, and loss of CTS frames is not reflected in the transmission rate adjustment. In the fixed-rate period, the transmission rate that was used most frequently in the preceding autorate period (optimum rate) is fixed, and RTS/CTS is not used. Implementation of SFRC is straightforward as it uses conventional IEEE 802.11 DCF and only minor modification of the wireless LAN driver is required. SFRC, which uses a modified SampleRate, an ARC implementation in the Madwifi, (SampleRate+) in the autorate period, termed SFRC-SampleRate+, was developed. The results of real-world experiments indicate that SFRC-SampleRate+ is superior to SampleRate and SampleRate+, and is closer to FRC, which uses optimum rate on each link, in terms of throughput in wireless mesh network environments.

This paper presents a response time acceleration technique in a high-gain capacitive-feedback frontend amplifier (FA) for high output impedance sensors. Using an auxiliary amplifier as a unity-gain buffer, a sample-and-hold capacitor which is used for band-limiting and sampling the FA output is driven at the beginning of the transient response to make the response faster and then it is re-charged directly by the FA output. A condition and parameters for the response time acceleration using this technique while maintaining the noise level unaffected are discussed. Theoretical analysis and simulation results show that the response time can be less than half of the case without the acceleration technique for the specified settling error of less than 0.5%.

Hovering unmanned aerial vehicles (UAVs) with mutual sense and communication capability form a new-fashioned airborne ad hoc network. Traditional routing protocols assume that there has already existed an end-to-end path before the message forwarding starts which, however, is not always available in the airborne network featuring randomly violent topological changes. Local heuristic information without complex computational cost should be considered to help route in this specific delay tolerant network (DTN). In this letter, we take Crowd Density (CD) and Relative Velocity Direction (RVD) as the fuzzy inputs, and use approximate reasoning to calculate priority of alternative candidates. Finally, the proposed mechanism is compared with some existing protocols.

This paper proposes a novel dynamic Scratch-pad Memory allocation strategy to optimize the energy consumption of the memory sub-system. Firstly, the whole program execution process is sliced into several time slots according to the temporal dimension; thereafter, a Time-Slotted Cache Conflict Graph (TSCCG) is introduced to model the behavior of Data Cache (D-Cache) conflicts within each time slot. Then, Integer Nonlinear Programming (INP) is implemented, which can avoid time-consuming linearization process, to select the most profitable data pages. Virtual Memory System (VMS) is adopted to remap those data pages, which will cause severe Cache conflicts within a time slot, to SPM. In order to minimize the swapping overhead of dynamic SPM allocation, a novel SPM controller with a tightly coupled DMA is introduced to issue the swapping operations without CPU's intervention. Last but not the least, this paper discusses the fluctuation of system energy profit based on different MMU page size as well as the Time Slot duration quantitatively. According to our design space exploration, the proposed method can optimize all of the data segments, including global data, heap and stack data in general, and reduce the total energy consumption by 27.28% on average, up to 55.22% with a marginal performance promotion. And comparing to the conventional static CCG (Cache Conflicts Graph), our approach can obtain 24.7% energy profit on average, up to 30.5% with a sight boost in performance.

Two types of similarities between words have been studied in the natural language processing community: synonymy and relational similarity. A high degree of similarity exist between synonymous words. On the other hand, a high degree of relational similarity exists between analogous word pairs. We present and empirically test a hypothesis that links these two types of similarities. Specifically, we propose a method to measure the degree of synonymy between two words using relational similarity between word pairs as a proxy. Given two words, first, we represent the semantic relations that hold between those words using lexical patterns. We use a sequential pattern clustering algorithm to identify different lexical patterns that represent the same semantic relation. Second, we compute the degree of synonymy between two words using an inter-cluster covariance matrix. We compare the proposed method for measuring the degree of synonymy against previously proposed methods on the Miller-Charles dataset and the WordSimilarity-353 dataset. Our proposed method outperforms all existing Web-based similarity measures, achieving a statistically significant Pearson correlation coefficient of 0.867 on the Miller-Charles dataset.

The propagation of messages among a group of people, which forms opportunistic Disruption Tolerant Networking (DTN), can be modeled as dynamic graph with links joining every two nodes up and down at a stationary speed. As people in DTN might have different probabilities of sending messages to each other, they should be divided into distinct groups with different link generate speed λ and link perish speed µ. In this letter, we focus on the two-group case, and apply Edge-Markovian Dynamic Graphs to present an analysis framework to evaluate the average delay for the information dissemination in DTN. We also give extensive simulation and numerical results revealing the influence of various parameters.

In the IEEE 802.11e standard, a reference scheduler is presented. The reference scheduler uses the same service interval (SI) to poll all stations in a polling list, and uses separate scheduling and admission algorithms. This increases the polling overhead and decreases TXOP utilization. Many papers have attempted to enhance the reference scheduler, but its admission control is similar to reference scheduler. In this paper, we propose a scheduling and admission algorithm that assigns each station an SI close to its maximum SI (MSI). As a result, the proposed algorithm shows higher performance than that of the reference scheduler.

In this paper, we propose low complexity channel parameter tracking methods for adaptive OFDM MMSE channel estimation. Even though the MMSE estimation is one of the most accurate channel estimation methods, it requires several channel information including Doppler frequency, RMS (root mean squared) delay spread, and SNR. To implement the MMSE estimation, tracking of such parameters should be preceded. We propose methods to track the above 3 channel parameters. As for Doppler frequency estimation, we propose an extremum method with a parabolic model, which is a key contribution of this paper. We also analyze the computational complexity of the proposed algorithms. Simulations show that the proposed tracking algorithm tracks the parameters well, and performs better than the conventional fixed-parameter algorithm in terms of BER performance. The BER performance of the adaptive MMSE estimation is better than that of a fixed-parameter (robust) MMSE estimator by about 5 dB.

In this paper, we present an algorithm for reducing the transmit normalization factor by perturbing the transmit signal in a Multi-User Multiple Input Multiple Output (MU-MIMO) system which uses the channel inverse matrix as its precoding matrix. A base station must normalize unnormalized transmit signals due to the limitation of the constant transmit power. This paper defines the norm of the unnormalized transmit signal as the transmit normalization factor used to normalize the transmit signal. Recalling that the transmit normalization factor consists of a combination of the singular values from the channel inverse matrix, we provide a codebook that successively reduces the coefficients of these singular values. Through computer simulations, the proposed algorithm is compared to sphere encoding in terms of the Bit Error Rate (BER) and the outage probability in a MU-MIMO signal environment. Sphere encoding is known to be an optimal solution amongst the perturbation methods that reduce the transmit normalization factor [1]. This work demonstrates that the proposed algorithm is has very good performance, comparable to that of sphere encoding, while its computational load is nearly 200 times less. Since the codebook in our algorithm depends only on the given channel, the difference in the computational complexity becomes even greater when the channel state is not changed, because the codebook can be reused. Furthermore, the codebook exhibits the characteristic of robustness to the maximum Doppler shift.

This paper shows a new pulse swallow programmable frequency divider with the division step size of 0.5. To realize the division step size of 0.5 by a conventional pulse swallow method, we propose a parallel dual modulus prescaler with the division ratio of P and P + 0.5. It consists of simple circuit elements and has an advantage over the conventional dual modulus prescaler with the division step size of 0.5 in high frequency operation. The proposed parallel dual modulus prescaler with the division ratio 8 and 8.5 is implemented in the 0.13-µm CMOS technology. The proposed architecture achieves 7 times higher frequency operation than the conventional one theoretically. It is verified the functions over 5 GHz.

The applications of dynamic content updates for a group of users, for example weather reports and news broadcast, have been shown to benefit significantly from Delay Tolerant Networks (DTNs) communication mechanisms. In this paper, we study the performance of dynamic content updates over DTNs by focusing on the latest content distribution, which is an important factor of the system energy consumption and content update efficiency. By characterizing the content generating process and content sharing process, we obtain an explicit expression for the latest content distribution, and prove it theoretically. Moreover, through simulations based on two synthetical mobility models and a real-world scenario, we demonstrate the accuracy and correctness of the theoretically obtained result.

The operating speed scalability is demonstrated by using the forward body biasing method for a 1-V 0.18-µm CMOS true single-phase clocking (TSPC) dual-modulus prescaler. With the forward body bias voltage varying between 0 and 0.4 V, the maximum operating speed changes by about 40–50% and the maximum input sensitivity frequency changes by about 400%. This speed scalability is achieved with less than 0.5-dB phase noise degradation. This demonstration indicates that the forward body biasing method is instrumental to build a cost-saving power-efficient 1-V 0.18-µm CMOS radio for low-power WBAN and WSN applications.

The lateral velocity is of importance in cases like target identification and traffic management. Conventional Doppler methods are not capable of measuring lateral velocities since they quantify only the radial component. Based on the spectrogram characteristic of laterally moving targets, an algorithm based on fractional Fourier transform has been studied in the signal processing literature. The algorithm searches the peak position of the transformation, and calculates the lateral velocity from the peak position. The performance analysis of this algorithm is carried out in this paper, which shows that this algorithm approaches Cramer-Rao bound with reasonable computational complexity. Simulations are conducted at last to compare the analytical performance and the experimental result.

We propose a novel method for measuring the matched total radiated power (TRP) and matched total radiated sensitivity (TRS) of small radio terminals, called over-the-air (OTA) measurement, using a spheroidal coupler (SC). To measure these parameters accurately in a multiple-reflection environment, such as in an SC, we developed two key techniques, i.e. displacement method and reflection compensation method, and verified their effectiveness by several simulations and fundamental experiments on a test transmitter. We also describe an absolute method for measuring antenna radiation efficiency using the displacement method. Furthermore, we describe TRP and TRS measurements for actual UMTS (Universal Mobile Telecommunications System) terminals, and verify that the proposed method achieves quick measurements with good accuracy. The SC provides a compact, low-cost OTA measurement system with high sensitivity and high speed.

This letter proposes an efficient Location-Aware Social Routing (LASR) scheme for Delay Tolerant Networks (DTNs). LASR makes forwarding decisions based on a new metric which uses location information to reflect the node relations and community structure. Simulation results are presented to support the effectiveness of our scheme.

In this paper, we derive a simple formula to generate a wide-sense systematic generator matrix(we call it quasi-systematic) B for a Reed-Solomon code. This formula can be utilized to construct an efficient interpolation based erasure-only decoder with time complexity O(n2) and space complexity O(n). Specifically, the decoding algorithm requires 3kr + r2 - 2r field additions, kr + r2 + r field negations, 2kr + r2 - r + k field multiplications and kr + r field inversions. Compared to another interpolation based erasure-only decoding algorithm derived by D.J.J. Versfeld et al., our algorithm is much more efficient for high-rate Reed-Solomon codes.

Decoding of Reed-Solomon (RS) codes requires many arithmetic operations in the Galois field. While the software decoding of RS codes has the advantage of its flexibility to support RS codes of variable parameters, the speed of the software decoding is slower than dedicated hardware RS decoders because arithmetic operations in the Galois field on an ordinary processor require many instruction steps. To achieve fast software decoding of RS codes, it is effective to accelerate Galois operations by both dedicated circuitry and parallel processing. In this paper, an accelerator is proposed which is attached to the base processor to speed up the software decoding of RS codes by parallel execution of Galois operations.

In this paper, we propose three Deflection-Routing-based Multicast (DRM) schemes for a bufferless NoC. The DRM scheme without packets replication (DRM_noPR) sends multicast packet through a non-deterministic path. The DRM schemes with adaptive packets replication (DRM_PR_src and DRM_PR_all) replicate multicast packets at the source or intermediate node according to the destination position and the state of output ports to reduce the average multicast latency. We also provide fault-tolerant supporting in these schemes through a reinforcement-learning-based method to reconfigure the routing table to tolerate permanent faulty links in the network. Simulation results illustrate that the DRM_PR_all scheme achieves 41%, 43% and 37% less latency on average than that of the DRM_noPR scheme and 27%, 29% and 25% less latency on average than that of the DRM_PR_src scheme under three synthetic traffic patterns respectively. In addition, all three fault-tolerant DRM schemes achieve acceptable performance degradation at various link fault rates without any packet lost.

In this paper, the problem of control reconfiguration in the presence of actuator failure preserving the nominal controller is addressed. In the actuator failure condition, the processing algorithm of the control signal should be adapted in order to re-achieve the desired performance of the control loop. To do so, the so-called reconfiguration block, is inserted into the control loop to reallocate nominal control signals among the remaining healthy actuators. This block can be either a constant mapping or a dynamical system. In both cases, it should be designed so that the states or output of the system are fully recovered. All these situations are completely analysed in this paper using a novel structural approach leading to some theorems which are supported in each section by appropriate simulations.

An adaptive rate controller (ARC) based on an adaptive neural fuzzy inference system (ANFIS) is designed to autonomously adjust the data rate of a mobile heterogeneous network to adapt to the changing traffic load and the user speed for multimedia call services. The effect of user speed on the handoff rate is considered. Through simulations, it has been demonstrated that the ANFIS-ARC is able to maintain new call blocking probability and handoff failure probability of the mobile heterogeneous network below a prescribed low level over different user speeds and new call origination rates while optimizing the average throughput. It has also been shown that the mobile cognitive wireless network with the proposed CS-ANFIS-ARC protocol can support more traffic load than neural fuzzy call-admission and rate controller (NFCRC) protocol.