In this paper, we propose a new method for wideband spectrum sensing using compressed measurements of the received wideband signal; we can directly separate information of the sub-channels and perform detection in each. Wideband spectrum sensing empowers us to rapidly access the vacant sub-channels in high utilization regime. Regarding the fact that at each time instant some sub-channels are vacant, the received signal is sparse in some bases. Then we could apply the Compressive Sensing (CS) algorithms and take the compressed measurements. On the other hand, the primary user signals in different sub-channels could have different modulation types; therefore, the signal in each sub-channel is chosen among a signal space. Knowing these signal spaces, the secondary user could separate information of different sub-channels employing the compressed measurements. We perform filtering and detection based on these compressed measurements; this decreases the computational complexity of the wideband spectrum sensing. In addition, we model the received wideband signal as a vector which has a block-sparse representation on a basis consisting of all sub-channel bases whose elements occur in clusters. Based on this feature of the received signal, we propose another wideband spectrum sensing method with lower computational complexity. In order to evaluate the performance of the proposed method, we employ the Monte-Carlo simulation. According to simulations if the compression rate is selected appropriately according to the CS theorems and the problem model, the detection performance of our method leads to the performance of the ideal filter bank-based method, which uses the ideal and impractical narrow band filters.

We report a trial of 100-GS/s optical quantization with 5-bit resolution using soliton self-frequency shift (SSFS) and spectral compression. We confirm that 100-GS/s 5-bit optical quantization is realized to quantize a 5.0-GHz sinusoid electrical signal in simulation. In order to experimentally verify the possibility of 100-GS/s 5-bit optical quantization, we execute 5-bit optical quantization by using two sampled signals with 10-ps intervals.

Fast string matching is essential for deep packet inspection (DPI). Traditional string matchers cannot keep up with the continuous increases in data rates due to their natural speed limits. We add a multi-byte processing prefilter to the traditional string matcher to detect target patterns on a multiple character basis. The proposed winnowing prefilter significantly reduces the number of identity blocks, thereby reducing the memory requirements.

Probabilistic Packet Marking (PPM) is a scheme for IP traceback where each packet is marked randomly with an IP address of one router on the attack path in order for the victim to trace the source of attacks. In previous work, a network coding approach to PPM (PPM+NC) where each packet is marked with a random linear combination of router IP addresses was introduced to reduce number of packets required to infer the attack path. However, the previous work lacks a formal proof for benefit of network coding to PPM and its proposed scheme is restricted. In this paper, we propose a novel method to prove a strong theorem for benefit of network coding to PPM in the general case, which compares different perspectives (interests of collecting) at the collector in PPM+NC scheme. Then we propose Core PPM+NC schemes based on our core network coding approach to PPM. From experiments, we show that our Core PPM+NC schemes actually require less number of packets than previous schemes to infer the attack path. In addition, based on the relationship between Coupon Collector's Problem (CCP) and PPM, we prove that there exists numerous designs that CCP still benefits from network coding.

We propose a new analytical method for a composite dielectric grating embedded with conducting strips using scattering factors in the shadow theory. The scattering factor in the shadow theory plays an important role instead of the conventional diffraction amplitude. By specifying the relation between scattering factors and spectral-domain Green's functions, we derive expressions of the Green's functions directly for unit surface electric and magnetic current densities, and apply the spectral Galerkin method to our formulation. From some numerical results, we show that the expressions of the Green's functions are valid, and analyze scattering characteristics by composite gratings.

The overall performance of multi-hop cognitive radio networks (MHCRNs) can be improved significantly by employing the diversity of orthogonal licensed channels in underlay fashion. However, the mutual interference between secondary links and primary links and the congestion due to the contention among traffic flows traversing the shared link become obstacles to this realizing technique. How to control congestion efficiently in coordination with power and spectrum allocation optimally in order to obtain a high end-to-end throughput is motivating cross-layer designs for MHCRNs. In this paper, by taking into account the problem of joint rate adaption, power control, and spectrum allocation (JRPS), we propose a new cross-layer optimization framework for MHCRNs using orthogonal frequency division multiple access (OFDMA). Specifically, the JRPS formulation is shown to be a mix-integer non-linear programming (MINLP) problem, which is NP-Hard in general. To solve the problem, we first develop a partially distributed algorithm, which is shown to converge to the global optimum within a reasonable time interval. We next propose a suboptimal solution which addresses the shortcomings of the first. Using numerical results, we finally demonstrate the efficiency of the proposed algorithms.

Self-encoded spread spectrum (SESS) derives its spreading codes from the random information source rather than using traditional pseudo-random codes. It has been shown that the memory in SESS modulated signals not only can deliver a 3 dB gain in additive white Gaussian noise (AWGN) channels, but also can be exploited to achieve time diversity and robust bit-error rate (BER) performance in fading channels. In this paper, we propose an extension to SESS, namely coded-sequence self-encoded spread spectrum (CS-SESS), and show that it can further improve the BER performance. We describe the CS-SESS scheme and present the theoretical analysis and simulation results for AWGN and fading channels. Iterative detector is developed to exploit the inherent temporal diversity of CS-SESS modulation. The simulation results show that it can achieve the expected 4.7 dB gain with a complexity that increases linearly with the spreading sequence length under AWGN. In Rayleigh fading channel, it can effectively mitigate the fading effects by exploiting the overall diversity gain. Chip interleaving is shown to yield a performance improvement of around 4.7 dB when compared to an chip interleaved direct sequence spread spectrum (DSSS) system.

In this letter, we analyze the outage performance of cognitive spectrum sharing in two-way relaying systems. We derive expressions of outage probability for the primary and secondary network over independent but not necessarily identically distributed (i.n.i.d.) Rayleigh fading channels. Monte Carlo simulations are presented to verify the theoretical analyses.

In this work, we analyze the performance of cognitive amplify-and-forward (AF) relay networks under the spectrum sharing approach. In particular, by assuming that the AF relay operates in the semi-blind mode (fixed-gain), we derive the exact closed-form expressions of the outage probability for the cognitive relaying (no direct link) and cognitive cooperative (with direct link) systems. Simulation results are presented to verify the theoretical analysis.

Based on a proposed frame structure with an unequal sensing slot duration for each channel, and two sensing scenarios (with or without cooperation), a joint channel and sensing time assignment is suggested to maximize the uplink throughput of the centralized multi-band cognitive radio network with the consideration of the mutual interference among the secondary users (SUs). Firstly, the channel assignment is performed by using the proposed Delta Non-square Hungarian (DNH), which is a modified iterative Hungarian algorithm distinguished by throughput increment maximization and non-square weight matrix. Simulation results illustrate that DNH has significant advantages in enhancing the throughput and reducing the computational complexity. Moreover, a hybrid channel assignment, also performed by DNH, is improved based on the two sensing scenarios to maximize the throughput while efficiently limiting the interference power to primary users. Secondly, the convexity of the throughput functions within the range of sensing time is proved under the proposed frame structure, and then the maximum throughput is achieved through the steepest descent method-based sensing time assignment. Both of these results are corroborated by simulations.

A specific physical layer network coding (PNC) scheme is proposed for the two-way relay channel. Unlike the traditional binary PNC that focuses mainly on BPSK modulation, the proposed PNC scheme is tailored for general MPSK modulation. In particular, the product of the two modulated signals is considered as a network-coded symbol. The proposed network coding operation occurs naturally in the inner or outer product of the received signal. A novel PNC-specific detection principle is then developed to estimate the network-coded symbol. Simulations show that the proposed scheme achieves almost optimal performance in terms of end-to-end bit error rate (BER), where the relay node is equipped with multiple antennas.

This paper is concerned with coding theorems in the optimistic sense for separate coding of two correlated general sources X1 and X2. We investigate the achievable rate region Ropt (X1,X2) such that the decoding error probability caused by two encoders and one decoder can be arbitrarily small infinitely often under a certain rate constraint. We give an inner and an outer bounds of Ropt (X1,X2), where the outer bound is described by using new information-theoretic quantities. We also give two simple sufficient conditions under which the inner bound coincides with the outer bound.

Recently, cooperative spectrum sensing is being studied to greatly improve the sensing performance of cognitive radio networks. To develop an adaptable cooperative sensing algorithm, an important issue is how to properly induce selfish users to participate in spectrum sensing work. In this paper, a new cognitive radio spectrum sharing scheme is developed by employing the trust-based bargaining model. The proposed scheme dynamically adjusts bargaining powers and adaptively shares the available spectrum in real-time online manner. Under widely different and diversified network situations, this approach is so dynamic and flexible that it can adaptively respond to current network conditions. Simulation results demonstrate that the proposed scheme can obtain better network performance and bandwidth efficiency than existing schemes.

We propose optical path routing and frequency slot assignment algorithms that can make the best use of elastic optical paths and the capabilities of distance adaptive modulation. Due to the computational difficulty of the assignment problem, we develop algorithms for 1+1 dedicated/1:1 shared protected ring networks and unprotected mesh networks to that fully utilize the characteristics of the topologies. Numerical experiments elucidate that the introduction of path elasticity and distance adaptive modulation significantly reduce the occupied bandwidth.

Conventional entropy measure is derived from full-band (range from 0 Hz to 4 kHz); however, it can not clearly describe the spectrum variability during voice-activity. Here we propose a novel concept of adaptive long-term sub-band entropy ( ALT-SubEnpy ) measure and combine it with a multi-thresholding scheme for voice activity detection. In detail, the ALT-SubEnpy measure developed with four part parameters of sub-entropy which uses different long-term spectral window length at each part. Consequently, the proposed ALT-SubEnpy -based algorithm recursively updates the four adaptive thresholds on each part. The proposed ALT-SubEnpy-based VAD method is shown to be an effective method while working at variable noise-level condition.

In this study, we propose a cooperative sensing with distributed pre-detection for gathering sensing information on shared primary system. We have proposed a system that gathers multiple sensing information by using the orthogonal narrowband signal; the system is called the orthogonal frequency-based sensing information gathering (OF-SIG) method. By using this method, sensing information from multiple secondary nodes can be gathered from the surrounding secondary nodes simultaneously by using the orthogonal narrowband signals. The advantage of this method is that the interference from each node is small because a narrowband tone signal is transmitted from each node. Therefore, if appropriate power and transmission control are applied at the surrounding nodes, the sensing information can be gathered in the same spectrum as the primary system. To avoid interference with the primary receiver, we propose a cooperative sensing with distributed pre-detection for gathering sensing information in each node by limiting sensing node power. In the proposed method, the number of sensing information transmitting nodes depends on the pre-detection ability of the individual sensing at each node. Then the secondary node can increase the transmit power by improving the sensing detection ability, and the secondary node can gather the sensing information from the surrounding secondary nodes which are located more far by redesign the transmit power of the secondary nodes. Here, we design the secondary transmit power based on OF-SIG while considering the aggregated interference from multiple sensing nodes and individual sensing ability. Finally we confirm the performance of the cooperative sensing of the proposed method through computer simulation.

This paper proposes a bit-split string matcher architecture for a memory-efficient hardware-based parallel pattern matching engine. In the proposed bit-split string matcher, multiple finite-state machine (FSM) tiles share match vectors to reduce the required number of stored match vectors. By decreasing the memory size for storing match vectors, the total memory requirement can be minimized.

This paper proposes a new channel allocation algorithm for satellite communication systems. The algorithm is based on a spectrum division transmission technique as well as a spectrum compression transmission technique that we have developed in separate pieces of work. Using these techniques, the algorithm optimizes the spectrum bandwidth and a MODCOD (modulation and FEC error coding rate) scheme to balance the usable amount of satellite transponder bandwidth and satellite transmission power. Moreover, it determines the center frequency and bandwidth of each divided subspectra depending on the unused bandwidth of the satellite transponder bandwidth. As a result, the proposed algorithm enables flexible and effective usage of satellite resources (bandwidth and power) in channel allocations and thus enhances satellite communication (SATCOM) system capacity.

Image warping is usually used to perform real-time geometric transformation of the images captured by the CMOS image sensor of video camera. Several existing look-up table (LUT)-based algorithms achieve real-time performance; however, the size of the LUT is still large, and it has to be stored in off-chip memory. To reduce latency and bandwidth due to the use of off-chip memory, this paper proposes an improved LUT (ILUT) scheme that compresses the LUT to the point that it can be stored in on-chip memory. First, a one-step transformation is adopted instead of using several on-line calculation stages. The memory size of the LUT is then reduced by utilizing the similarity of neighbor coordinates, as well as the symmetric characteristic of video camera images. Moreover, an elaborate pipeline hardware structure, cooperating with a novel 25-point interpolation algorithm, is proposed to accelerate the system and reduce further memory usage. The proposed system is implemented by a field-programmable gate array (FPGA)-based platform. Two different examples show that the proposed ILUT achieves real-time performance with small memory usage and low system requirements.

A novel cooperative spectrum sensing scheme suitable for wireless cognitive radio system with imperfect reporting channels is proposed. In the proposed scheme, binary local decision bits are transmitted to the fusion center and combined to form a soft-valued decision statistics in the fusion center. To form a decision statistics, a majority-decision-aided weighting rule is proposed. The proposed scheme provides a reliable sensing capability even with poor reporting channels.