It is important to optimize aggregation schemes for heterogeneous wireless networks for maximizing communication throughput utilizing any available radio access networks. In the heterogeneous networks, differences of the quality of service (QoS), such as throughput, delay and packet loss rate, of the networks makes difficult to maximize the aggregation throughput. In this paper, we firstly analyze influences of such differences in QoS to the aggregation throughput, and show that it is possible to improve the throughput by adjusting the parameters of an aggregation system. Since manual parameter optimization is difficult and takes much time, we propose an autonomous parameter tuning scheme using a machine learning algorithm for the heterogeneous wireless network aggregation. We implement the proposed scheme on a heterogeneous cognitive radio network system. The results on our experimental network with network emulators show that the proposed scheme can improve the aggregation throughput better than the conventional schemes. We also evaluate the performance using public wireless network services, such as HSDPA, WiMAX and W-CDMA, and verify that the proposed scheme can improve the aggregation throughput by iterating the learning cycle even for the public wireless networks. Our experimental results show that the proposed scheme achieves twice better aggregation throughput than the conventional schemes.

In Long-Term Evolution (LTE)-Advanced, heterogeneous networks where femtocells and picocells are overlaid onto macrocells are extensively discussed in addition to traditional well-planned macrocell deployment to improve further the system throughput. In heterogeneous network deployment, combined usage of inter-cell interference coordination (ICIC) and cell range expansion (CRE) is very effective in improving the system and cell-edge throughput. In this combined usage, the fraction of the sets of user equipment (UEs) connected to the picocells, which are controlled through CRE, and that connected to macrocells affect the gain from the ICIC. Therefore, this paper evaluates the throughput performance of different offset values for CRE and different amounts of protected resources for ICIC in picocell deployments in LTE-Advanced downlink. Simulation results (2–10 picocells and 30 UEs are located within 1 macrocell) assuming a full buffer traffic model show that when the CRE offset value is set between 8 to 20 dB, almost the same user throughput performance is obtained by allocating the appropriate resources to protect UEs that connect to the picocells. Furthermore, the appropriate resource ratio is derived based on the fraction of UEs connected to the picocells through CRE, the fraction of UEs connected to the macrocell, and the number of picocells under the simulation conditions.

In this paper, we present a coexistence protocol design for a coexistence information service to provide coexistence solutions among dissimilar or independently operated autonomous decision-making networks in a wireless communication environment over, specifically but not limited to, TV white space (TVWS) frequency bands. The designed coexistence protocol for the coexistence information service has three main functionalities: (1) To collect basic information of subscribed TVWS networks; (2) To support generating neighbor lists for the TVWS networks based on the geography information and/or propagation parameters; (3) To provide necessary information for TVWS networks to make coexistence decisions. Both theoretical analysis and simulation results show that the designed coexistence information service ensures harmonious communications among dissimilar networks and is able to achieve coexistence over an area with the limited number of available channels in white space.

When a cognitive radio system dynamically utilizes a frequency band, channel control information must be communicated over the network in order for the currently available carrier frequencies to be shared. In order to keep efficient spectrum utilization, this control information should also be dynamically transmitted through channels such as cognitive pilot channels based on the channel conditions. If transmitters dynamically select carrier frequencies, receivers must receive the control signal without knowledge of its carrier frequencies. A novel scheme called differential code parallel transmission (DCPT) enables receivers to receive low-rate information without any knowledge of the carrier frequency. The transmitter simultaneously transmits two signals whose carrier frequencies are separated by a predefined value. The absolute values of the carrier frequencies can be varied. When the receiver receives the DCPT signal, it multiplies the signal by a frequency-shifted version of itself; this yields a DC component that represents the data signal, which is then demodulated. However, the multiplication process results in the noise power being squared, necessitating high received signal power. In this paper, to realize a bandpass filter that passes only DCPT signals of unknown frequency and that suppresses noise and interference at other frequencies, a DCPT-adaptive bandpass filter (ABF) that employs an adaptive equalizer is proposed. In the training phase, the received signal is the filter input and the frequency-shifted signal is the training input. Then, the filter is trained to pass the higher-frequency signal of the two DCPT signals. The performance of DCPT-ABF is evaluated through computer simulations. We find that DCPT-ABF operates successfully even under strong interference.

This paper proposes a sensing method for TV signals of DVB-T standard to realize effective TV White Space (TVWS) Communication. In the TVWS technology trial organized by the Infocomm Development Authority (iDA) of Singapore, with regard to the sensing level and sensing time, detecting DVB-T signal at the level of -120 dBm over an 8 MHz channel with a sensing time below 1 second is required. To fulfill such a strict sensing requirement, we propose a smart sensing method which combines feature detection and energy detection (CFED), and is also characterized by using dynamic threshold selection (DTS) based on a threshold table to improve sensing robustness to noise uncertainty. The DTS based CFED (DTS-CFED) is evaluated by computer simulations and is also implemented into a hardware sensing prototype. The results show that the DTS-CFED achieves a detection probability above 0.9 for a target false alarm probability of 0.1 for DVB-T signals at the level of -120 dBm over an 8 MHz channel with the sensing time equals to 0.1 second.

We mathematically analyze the sleep mode operation of IEEE 802.16m. The sleep mode operation for downlink traffic is modeled as a 3-dimensional discrete time Markov chain. We obtain the average power consumption of a mobile station and the average delay of a message. Numerical results match simulations very well. Numerical results show that there is a tradeoff between power consumption and message delay. We find the optimal lengths of sleep cycle and close-down time that minimize the power consumption while satisfying the quality of service (QoS) constraint on message delay. The power consumption of the sleep mode in IEEE 802.16m is better than that of sleep modes in legacy IEEE 802.16e standard under the same delay bound.

A hybrid buffer structured optical packet switch and its scheduling algorithm are presented for a limited number of tunable wavelength convertors (TWCs) and internal wavelengths. The hybrid buffer consists of the fiber delay line (FDL) buffer and the electronic buffer. With the proposed algorithm, it could lead realizable packet loss reduction that the LAUC-VF algorithm with only the FDL buffer does not reach. Also, we optimized the number of TWCs and internal wavelengths of the hybrid buffer structured OPS. For the fully shared TWC structure, the optimum number of TWCs and internal wavelengths to guarantee minimum packet loss is evaluated to prevent resource waste under the hybrid buffer.

To provide scalability against group size, Global Location Search based Hierarchical Geographic Multicast Protocols (GLS-HGMPs) have recently been proposed for wireless sensor networks. To reduce the communication overhead imposed by the global location search and prevent the multicast data detour imposed by the hierarchical geographic multicasting in GLS-HGMPs, this letter proposes Local Location Search based Progressive Geographic Multicast Protocol (LLS-PGMP). Simulation results show that LLS-PGMP is superior to GLS-HGMPs.

In this paper, we propose a novel scheme to optimize the allocation of continuous queries in a sensor network with multiple sinks. The existing scheme compares the coverage areas of given queries and estimates the amount of sharing among them. It tries to allocate queries to the optimal sink that maximizes the amount of sharing and reduces the communication costs among sensor nodes and sinks. However, it inefficiently allocates continuous queries. The amount of sharing among continuous queries depends not only on their coverage area but also on their time-parameters like time-duration and time-interval. We define a new cost estimator with time-parameters for continuous queries and optimize their allocation in the sensor network. Simulation results show that our scheme performs the allocation of continuous queries efficiently and reduces the communication cost.

The double threshold detecting strategy is widely used for spatially distributed target detection in practical systems. However, the detector is limited in terms of robustness and effectiveness. In this paper, an improved double threshold detector is proposed that avoids these shortcomings. In the proposed detector, the energy in range cells that exceed the first threshold is accumulated and then the output of the accumulator is compared with the second threshold for detection. The threshold selection strategy is derived to guarantee the constant false-alarm rate (CFAR) property. A simulation shows that the proposed detector is superior to the conventional approach in terms of both robustness and effectiveness.

This paper presents a memory-efficient VLSI architecture for output probability computations (OPCs) of continuous hidden Markov models (HMMs) and likelihood score computations (LSCs). These computations are the most time consuming part of HMM-based isolated word recognition systems. We demonstrate multiple fast store-based block parallel processing (MultipleFastStoreBPP) for OPCs and LSCs and present a VLSI architecture that supports it. Compared with conventional fast store-based block parallel processing (FastStoreBPP) and stream-based block parallel processing (StreamBPP) architectures, the proposed architecture requires fewer registers and less processing time. The processing elements (PEs) used in the FastStoreBPP and StreamBPP architectures are identical to those used in the MultipleFastStoreBPP architecture. From a VLSI architectural viewpoint, a comparison shows that the proposed architecture is an improvement over the others, through efficient use of PEs and registers for storing input feature vectors.

This paper discusses a wireless control system for cooperative motion of multiple machines, and clarifies the influence of packet losses on the system behavior. We focus on the synchronization of the motion of the machines, and using the nature of wireless, we propose a new wireless control scheme for maintaining the synchronization performance under packet loss conditions. In the proposed scheme, each controlled object (plant) utilizes control information destined for all plants, and the main controller also utilizes state information of all plants. The additional information of the other controller-plant pairs is used to compensate lost information. As an example of the controlled plants, rotary inverted pendulums, which move synchronously with wireless connections in their control-feedback loops, are considered. Numerical examples confirm the superiority of the proposed scheme from the view-point of the synchronization of the motion of the plants.

This paper discusses a control system that employs a power line to transfer signals to control the motion of a single machine, and explores the influence of packet losses on the quality of the control. As an example of a controlled system, a controller with a rotary inverted pendulum as a controlled object, is considered. The feedback loop in between is the power line. The control performance is evaluated in the power line cyclostationary noise environment and compared against the performance in a stationary noise environment. As a result, it is confirmed that the power line and its cyclostationary noise features present an advantage against transmission in a channel with stationary noise.

The Viterbi algorithm is widely used for decoding of the convolutional codes. The trace-back method is preferable to the register exchange method because of lower power consumption especially for convolutional codes with many states. A drawback of the conventional trace-back is that it generally requires long latency to obtain the decoded data. In this paper, a method of the trace-back with source states instead of decision bits is proposed which reduces the number of memory accesses. The dedicated memory is also presented which supports the proposed trace-back method. The reduced memory accesses result in smaller power consumption and a shorer decode latency than the conventional method.

In the analysis of maximum-likelihood decoding performance of low-density parity-check (LDPC) codes, the weight distribution is an important factor. We presented a probabilistic method for computing the weight distribution of LDPC codes, and showed results of computing the weight distribution of several LDPC codes. In this paper, we improve our previously presented method and propose a probabilistic computation method with reliability for the weight distribution of LDPC codes. Using the proposed method, we can determine the weight distribution with small failure probability.

This paper proposes an adaptive bandwidth control scheme for the private wireless networks. Carrier sense multiple access with collision avoidance (CSMA/CA), which is commonly used within the private networks, is not efficient in terms of spectral efficiency due to its strict collision avoidance process. In order to relax the collision avoidance rule, this paper employs dynamic spectrum control (DSC), in which a certain number of discrete spectra having the higher channel gain is selected in a selfish manner with each link allowing a partial band interference. Such interference may be suppressed by the equalizer at the receiver. Aiming at optimal selection of the bandwidth for the selfish DSC according to channel realizations, in the sense of throughput maximization, this paper proposes a channel capacity maximization-based BAR control scheme. Computer simulations validate that the proposed scheme achieves high throughput efficiency.

With the proliferation of IEEE 802.11 wireless local area networks, large numbers of wireless access points have been deployed, and it is often the case that a user can detect several access points simultaneously in dense metropolitan areas. Most owners, however, encrypt their networks to prevent the public from accessing them due to the increased traffic and security risk. In this work, we use pricing as an incentive mechanism to motivate the owners to share their networks with the public, while at the same time satisfying users' service demand. Specifically, we propose a “federated network” concept, in which radio resources of various wireless local area networks are managed together. Our algorithm identifies two candidate access points with the lowest price being offered (if available) to each user. We then model the price announcements of access points as a game, and characterize the Nash Equilibrium of the system. The efficiency of the Nash Equilibrium solution is evaluated via simulation studies as well.

Maximum likelihood block signal detection employing QR decomposition and M-algorithm (QRM-MLBD) can significantly improve the bit error rate (BER) performance of single-carrier (SC) transmission while significantly reducing the computational complexity compared to maximum likelihood detection (MLD). However, its computational complexity is still high. In this paper, we propose the computationally efficient 2-step QRM-MLBD. Compared to conventional QRM-MLBD, the number of symbol candidates can be reduced by using preliminary decision made by minimum mean square error based frequency-domain equalization (MMSE-FDE). The BER performance achievable by 2-step QRM-MLBD is evaluated by computer simulation. It is shown that it can significantly reduce the computational complexity while achieving almost the same BER performance as the conventional QRM-MLBD.

Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular protocols to resolve tag collisions in RFID systems. In DFSA, it is widely known that the optimal performance is achieved when the frame size is equal to the number of tags. So, a reader dynamically adjusts the next frame size according to the current number of tags. Thus it is important to estimate the number of tags exactly. In this paper, we propose a novel tag estimation and identification method using litmus (test) slots for DFSA. We compare the performance of the proposed method with those of existing methods by analysis. We conduct simulations and show that our scheme improves the speed of tag identification.

Tomlinson-Harashima precoding (THP) is considered to be a prominent precoding scheme due to its ability to efficiently cancel out the known interference at the transmitter side. Therefore, the information rates achieved by THP are superior to those achieved by conventional linear precoding schemes. In this paper, new lower bounds on the achievable information rates for the regularized THP scheme are derived. Analytical results show that the lower bounds derived in this paper are tighter than the original lower bounds particularly for the low SNR range, while all lower bounds converge to as SNR ∞.