In this letter, we propose a simple adaptive switching scheme to enhance the performance of space-time/frequency block coded OFDM systems (STBC/SFBC-OFDM). Since STBC-OFDM and SFBC-OFDM undergo severe performance degradation in time- and frequency-selective fading channels, respectively, performance enhancement can be achieved by switching between STBC-OFDM and SFBC-OFDM over a continuously varying channel environments. Thus, a new switching scheme based on the characteristics of the actual channel is proposed. The effectiveness of the proposed scheme is demonstrated by computer simulations.

External interferences can severely degrade the performance of an Over-the-horizon radar (OTHR), so suppression of external interferences in strong clutter environment is the prerequisite for the target detection. The traditional suppression solutions usually began with clutter suppression in either time or frequency domain, followed by the interference detection and suppression. Based on this traditional solution, this paper proposes a method characterized by joint clutter suppression and interference detection: by analyzing eigenvalues in a short-time moving window centered at different time position, clutter is suppressed by discarding the maximum three eigenvalues at every time position and meanwhile detection is achieved by analyzing the remained eigenvalues at different position. Then, restoration is achieved by forward-backward linear prediction using interference-free data surrounding the interference position. In the numeric computation, the eigenvalue decomposition (EVD) is replaced by singular values decomposition (SVD) based on the equivalence of these two processing. Data processing and experimental results show its efficiency of noise floor falling down about 10-20 dB.

A Generalized Symbol-rate-increased (GSRI) Pragmatic Adaptive Trellis Coded Modulation (ATCM) is applied to a Multi-carrier CDMA (MC-CDMA) system with bi-orthogonal keying is analyzed. The MC-CDMA considered in this paper is that the input sequence of a bi-orthogonal modulator has code selection bit sequence and sign bit sequence. In, an efficient error correction code using Reed-Solomon (RS) code for the code selection bit sequence has been proposed. However, since BPSK is employed for the sign bit modulation, no error correction code is applied to it. In order to realize a high speed wireless system, a multi-level modulation scheme (e.g. MPSK, MQAM, etc.) is desired. In this paper, we investigate the performance of the MC-CDMA with bi-orthogonal keying employing GSRI ATCM. GSRI TC-MPSK can arbitrarily set the bandwidth expansion ratio keeping higher coding gain than the conventional pragmatic TCM scheme. By changing the modulation scheme and the bandwidth expansion ratio (coding rate), this scheme can optimize the performance according to the channel conditions. The performance evaluations by simulations on an AWGN channel and multi-path fading channels are presented. It is shown that the proposed scheme has remarkable throughput performance than that of the conventional scheme.

A composite patch array antenna with built-in polarizer has been developed to reduce road clutter noise by 20 dB for 76 GHz automotive radars. A polarizer is placed in front of Tx and Rx patch arrays within their reactive near-field region to suppress cross-polarized sidelobe radiation from their feeding lines while maintaining a low-profile characteristic with 4 mm thickness. Additional metal-lined absorbers within the composite antenna structure, while terminating cross-polarized waves undesirably excited by the patch arrays, also serve as miniature clutter plates to further reduce sidelobes toward the road surface. The resultant composite antenna achieved sidelobe levels of -45 dB, a 20 dB improvement over standard patch arrays, at elevation angles close to 90.

In this paper, an image restoration method using the Wiener filter is proposed. In order to bring the theory of the Wiener filter consistent with images that have spatially varying statistics, the proposed method adopts the locally adaptive Wiener filter (AWF) based on the universal Gaussian mixture distribution model (UNI-GMM) previously proposed for denoising. Applying the UNI-GMM-AWF for deconvolution problem, the proposed method employs the stationary Wiener filter (SWF) as a pre-filter. The SWF in the discrete cosine transform domain shrinks the blur point spread function and facilitates the modeling and filtering at the proceeding AWF. The SWF and UNI-GMM are learned using a generic training image set and the proposed method is tuned toward the image set. Simulation results are presented to demonstrate the effectiveness of the proposed method.

This letter proposes a windowing frequency domain adaptive algorithm, which reuses the filtering error to apply window function in the filter updating symmetrically. By using a proper window function to reduce the negative influence of the spectral leakage, the proposed algorithm can significantly improve the performance of the acoustic echo cancellation for speech signals.

Cognitive radio systems offer the opportunity to improve the spectrum utilization by detecting unused frequency bands while avoiding interference to primary users. This paper proposes a new algorithm for spectrum sensing, which is an energy detector using a hybrid (adaptive and fixed) threshold, in order to compensate the weak points of the existing energy detector in the distorted communication channel environment. Simulation results are presented which show that the performance of the new proposed scheme is better than the existing scheme using a fixed threshold or an adaptive threshold. Additionally, the performance is investigated in terms of several parameters such as the mobile speed and the probability of false alarms. The simulation results also show that the proposed algorithm makes the detector highly robust against fading, shadowing, and interference.

Combining the sphere decoding (SD) algorithm and the sequential detection method, we propose an adaptive group detection (AGD) scheme based on the sort-descending QRD (S-D-QRD) for V-BLAST architectures over an i.i.d. Rayleigh flat fading channel. Simulation results show that the proposed scheme, which encompasses the SD algorithm and the sequential detection method as two extreme cases in a probability sense, can achieve a very flexible tradeoff between the detection performance and computational complexity by adjusting the group parameter.

For phased and adaptive arrays of antennas, an optimal arrangement of antenna elements is essential to avoid grating lobes in the visible angular region of the array. Large sidelobes cause degradation in signal-to-noise ratio; grating lobes, in the worst case, cause malfunctions. One method of evaluating sidelobe level is square integration. For a given set element positions, evaluation by square integration of the sidelobes involves Fourier transform and numerical integration. For faster evaluation, we developed an equivalent transform algorithm that requires no numerical Fourier transform or integration. Using this new algorithm, we introduced a fast trial-and-error algorithm that iteratively applies random perturbation to the array, evaluates the function, and minimizes it. A number of separate runs of this algorithm have been conducted under the constraint of 3-fold rotational symmetry for stability. The optimal output, for which the function is minimized, is a uniformly spaced equilateral-triangular-type arrays that, unfortunately, has unwanted grating lobes. However the algorithm also yields variations trapped at local minima, some of which do not have grating lobes and whose sidelobe peaks are sufficiently low within a wide angular region. For the case N=12, a characteristic triagular-rectangular-type array often arises, which has not only better sidelobe properties as evaluated by square-integration and peak sidelobe, but also sufficient element-to-element clearance. For the case N=36, one of the results achieves a peak-sidelobe level of -8 dB, with a minimum element-to-element separation of 0.76 wavelength.

Backbone network of the mobile networks, i.e. mobile backhaul networks, is an important part of mobile network system. With the decreasing size of mobile network system cells, it is considered next-generation mobile backhaul networks will form mesh topology. Most mobile backhaul networks are formed with microwave radios. To increase data rate, Adaptive Modulation and Coding (AMC) is used for wireless links. However, the data rate of each wireless link changes over time and leads to unexpected packet loss or traffic degradation. This paper proposes a routing scheme and methods for estimating the transmission parameters or modes of wireless links to route bandwidth guaranteed flows over mobile backhaul networks. Proposed routing scheme can reduce degradation of flows caused by unexpected changes of the data rate of wireless links. We evaluate our routing scheme when mode distribution of links follows normal, uniform and Poisson distributions. This paper shows mode estimation using mode history of link to estimate the link quality can route bandwidth guaranteed flows efficiently by choosing more stable links for the path.

IEEE 802.15.4 is a new standard, uniquely designed for low rate wireless personal area networks (LR-WPANs). It targets ultra-low complexity, cost, and power, for low-data-rate wireless connectivity. However, one of the main problems of this new standard is its insufficient, and inefficient, media access control (MAC) for priority data. This paper introduces an extended contention access period (XCAP) concept for priority packets, also an traffic adaptive contention differentiation utilizing the XCAP (TACDX). The TACDX determines appropriate transmission policy alternatively according to the traffic conditions and type of packet. TACDX achieves not only enhanced transmission for priority packets but it also has a high energy efficiency for the overall network. The proposed TACDX is verified with simulations to measure the performances.

When we design a robust vector quantizer (VQ) for noisy channels, an appropriate index assignment function should be contrived to minimize the channel-error effect. For relatively high rates, the complexity for finding an optimal index assignment function is too high to be implemented. To overcome such a problem, we use a structurally constrained VQ, which is called the sample-adaptive product quantizer (SAPQ) [12], for low complexities of quantization and index assignment. The product quantizer (PQ) and its variation SAPQ [13], which are based on the scalar quantizer (SQ) and thus belong to a class of the binary lattice VQ [16], have inherent error resilience even though the conventional affine index assignment functions, such as the natural binary code, are employed. The error resilience of SAPQ is observed in a weak sense through worst-case bounds. Using SAPQ for noisy channels is useful especially for high rates, e.g., > 1 bit/sample, and it is numerically shown that the channel-limit performance of SAPQ is comparable to that of the best codebook permutation of binary switching algorithm (BSA) [23]. Further, the PQ or SAPQ codebook with an affine index assignment function is used for the initial guess of the conventional clustering algorithm, and it is shown that the performance of the best BSA can be easily achieved.

We propose a novel adaptive segment repair mechanism to improve traditional MPLS (Multi-Protocol Label Switching) failure recovery. The proposed mechanism protects one or more contiguous high failure probability links by dynamic setup of segment protection. Simulations demonstrate that the proposed mechanism reduces failure recovery time while also increasing network resource utilization.

Based on trace function over finite field GF(pn ), new construction of generalized Hadamard matrices with order pn is presented, where p is prime and n is even. The rows in new generalized Hadamard matrices are cyclically distinct and have large linear span, which greatly improves the security of the system employing them as spreading sequences.

In this paper, we study an opportunistic scheduling and adaptive modulation scheme for a wireless network with an XOR network coding scheme, which results in a cross-layer problem for MAC and physical layers. A similar problem was studied in [2] which considered an idealized system with the Shannon capacity. They showed that it may not be optimal for a relay node to encode all possible native packets and there exists the optimal subset of native packets that depends on the channel condition at the receiver node of each native packet. In this paper, we consider a more realistic model than that of [2] with a practical modulation scheme such as M-PSK. We show that the optimal policy is to encode native as many native packets as possible in the network coding group into a coded packet regardless of the channel condition at the receiver node for each native packet, which is a different conclusion from that of [2]. However, we show that adaptive modulation, in which the constellation size of a coded packet is adjusted based on the channel condition of each receiver node, provides a higher throughput than fixed modulation, in which its constellation size is always fixed regardless of the channel condition at each receiver node.

Scheduling algorithms are crucial in radio resource management especially for multimedia networks. Many scheduling algorithms are based on the assumption of error-free connections, which is not suitable for wireless networks. Therefore, a scheduling algorithm based on the modification of Static Priority (SP) algorithm and Earliest-Due-Date (EDD) algorithm is proposed for wireless multimedia networks with link adaptation in this paper. In the proposed algorithm, various quality of service requirements, such as delay, throughput, and packet loss ratio, are considered. Particularly, the influence of error tolerance of voice communications, which is usually ignored in most scheduling algorithms, is taken into account. Simulation results show that the proposed algorithm, compared with SP, EDD, and other scheduling algorithms, succeeds in meeting the delay and packet loss ratio (PLR) requirements at much heavier traffic load.

This letter presents VLA-MAC, a novel adaptive MAC protocol for wireless sensor networks that can achieve high energy efficiency and low latency in variable load conditions. In VLA-MAC, traffic load is measured online and utilized for adaptive adjustment. VLA-MAC transmits packets via a burst style to alleviate packets accumulation problem and achieve low latency in high load condition. Furthermore, it also saves obvious energy by removing unnecessary listen period in low load condition. Unlike current approach, VLA-MAC does not need to adjust duty-cycle according to load online. Simulation results based on ns-2 show the performance improvements of our protocol.

This letter presents an adaptive beamformer robust to random steering errors, based on the projection of received signals onto the orthogonal complement of the interference subspace. In the presence of random steering errors, to prevent the suppression of the desired signal, the proposed beamformer effectively finds basis vectors for the estimation of the interference subspace.

Conventional radar imaging systems use Fourier transform for image formation, but due to the target's complicated motion the Doppler spectrum is time-varying and thus the reconstructed image becomes blurred even after applying standard motion compensation algorithms. Therefore, sophisticated algorithms such as polar reformatting are usually employed to produce clear images. Alternatively, Joint Time-Frequency (JTF) analysis can be used for image formation which produces clear image without using polar reformatting algorithm. In this paper, a new JTF-based method is proposed for image formation in inverse synthetic aperture radars (ISAR). This method uses minimum entropy criterion for optimum parameter adjustment of JTF algorithms. Short Time Fourier Transform (STFT) and Fractional Fourier Transform (FrFT) are applied as JTF for time-varying Doppler spectrum analysis. Both the width of Gaussian window of STFT and the order of FrFT, α, are adjusted using minimum entropy as local and total measures. Furthermore, a new statistical parameter, called normalized correlation, is defined for comparison of images reconstructed by different methods. Simulation results show that α-order FrFT with local adjustment has much better performance than the other methods in this category even in low SNR.

In this paper, we focus on the adaptive resource allocation issue for uplink OFDMA systems. The resources are allocated according to a proportional fairness criterion, which can strike an alterable balance between fairness and efficiency. Optimization theory is used to analyze the multi-constraint resource allocation problem and some heuristic characteristics about the optimal solution are obtained. To deal with the cohesiveness of the necessary conditions, we resort to bargaining theory that has been deeply investigated in game theory. Firstly, we summarize some assumptions about bargaining theory and show their similarities with the resource allocation process. Then we propose a priority-ranked bargaining model, whose primary contribution is applying the economic thought to the resource allocation process. A priority-ranked bargaining algorithm (PRBA) is subsequently proposed to permit the base station to auction the subcarriers one by one according to the users' current priority. By adjusting the predefined rate ratio flexibly, PRBA can achieve different degrees of fairness among the users' capacity. Simulation results show that PRBA can achieve similar performance of the max-min scheme and the NBS scheme in the case of appropriate predefined rate ratio.