In this paper we propose a new routing scheme called group-epidemic routing (G-ER), which is specifically designed for group mobility in mobile ad hoc networks. G-ER is based on one proposed delay tolerant routing protocol called epidemic routing (ER). So, it could tolerate the disconnection characteristic among groups in group mobility. By considering each group as a single node, G-ER has made a great improvement to ER, which is shown in the simulation. In addition, we introduce the buffer sharing mechanism inside each group for G-ER. Also, the simulation has demonstrated the effectiveness of the buffer sharing mechanism, especially in a more disconnected scenario for group mobility.

The correlation lower bounds, as well as the set size upper bounds, of low-correlation-zone complementary sequences are presented in this paper. They can be treated as an extension of Tang-Fan-Matsufuji bounds in and , which considered only the conventional (non-complementary) low-correlation-zone sequence sets.

The cognitive radio allows spectrum sharing between licensed users (primary users) and many unlicensed users (secondary users). The secondary users are only allowed to use a licensed spectrum in the absence of its rightful owner. Thus, the ability to accurately sense the presence of the rightful owners is highly essential. In this paper, a novel cooperative spectrum sensing (CSS) approach to efficiently sense a wideband spectrum is introduced. This paper addresses two specific issues in CSS. The first issue is on dynamic detection of primary user's bands. A dynamic band clustering (DBC) algorithm that uses K-means clustering technique is proposed in this paper. The proposed algorithm reduces the number of erroneous narrow sub-bands resulting from spurious noise. This in turn minimizes the number of sub-bands to be detected and hence the overall sensing time. The second issue is on combining the local decisions made by different secondary users. A novel dynamic weighting decision fusion algorithm is also proposed in this paper. Based on extensive simulation studies, the proposed fusion algorithm is shown to be superior to conventional decision fusion techniques.

This paper considers wireless spectrum sensing in harsh environments dominated by shadowing and fading. By modeling the network of the secondary users as Markov random fields and pulling a group of secondary users to cooperate through distributed probabilistic inference, effective sensing and fusion can be achieved. The proposed framework subsumes belief propagation, as well as conventional weighted hard/soft combining (such as maximal ratio combining and equal gain combing). It can also account for the distance-dependent correlation among individual sensing results by setting appropriate compatibility function. Theoretic upper and lower bounds are derived, demonstrating the significant gains made possible by effective cooperation. Extensive simulations confirm the analytical results.

Maximum distance separable (MDS) array codes are XOR-based optimal erasure codes that are particularly suitable for use in disk arrays. This paper develops an innovative method to build MDS array codes from an elegant class of nested graphs, termed complete-graph-of-rings (CGR). We discuss a systematic and concrete way to transfer these graphs to array codes, unveil an interesting relation between the proposed map and the renowned perfect 1-factorization, and show that the proposed CGR codes subsume B-codes as their "contracted" codes. These new codes, termed CGR codes, and their dual codes are simple to describe, and require minimal encoding and decoding complexity.

This paper proposes a novel construction of analog codes based on nonlinear chaotic dynamical systems in general and the tent map in particular. In light of the importance of the symbolic coding in estimating tent chaos, the proposed construction exploit useful ideas of interleaving and parallel concatenation from classical coding theory to protect symbolic coding and subsequently chaotic states. The resultant new codes, dubbed chaotic analog turbo (CAT) codes, extend Chen-Wornell codes, in a spirit close to that of digital turbo codes extending digital convolutional codes. A new sequence detection method that improves the existing backward detection method is also developed. Through analysis and simulations, it is shown that CAT codes can noticeably outperform the existing analog ones.

A novel 4 x 1 scheme of transmitting two real orthogonal space-time block codes (O-STBC) on the I- and Q-channels with pulse-shaped offset QAM has recently been proposed. In order to achieve good spectral confinement, a pulse shape that introduces a small amount of controlled interference between I/Q- channels is used for the offset QAM signal. In this paper, two-real- symbol joint decoding is investigated for the scheme. This joint decoding can outperform the single-real symbol decoding proposed previously and the best-performing quasi-orthogonal space-time block code (QO-STBC) by more than 1 dB at bit error probability of 10-5when the interference introduced by the pulse shape is relatively large.

A new 4times1 scheme of transmitting two real orthogonal space-time block codes (O-STBC) on the I- and Q-channels with pulse-shaped offset QAM is proposed. This scheme achieves full rate and employs simple real-symbol-wise decoding. Two families of pulse shapes for the offset QAM signal are considered: i) pulse shapes with zero cross-channel interference (CCI) between I/Q-channels and ii) pulse shapes with controlled CCI. In the zero CCI case, the real-symbol-wise decoding is optimum and the bit error probability (BEP) performance is better than that of conventional full-rate, full-diversity quasi-orthogonal space-time block codes (QO-STBC), as well as rate-1/2 and rate-3/4 complex O-STBCs. To achieve good spectral confinement while maintaining decoding simplicity, we investigate pulse shapes that introduce a small amount of controlled CCI at the sampling instants so that some performance gains can be traded off. We derive a BEP upperbound for the case of nonzero CCI and formulate the design criteria on how to construct the two real O-STBCs on the I/Q channels in order to minimize the performance degradation caused by the controlled CCI. The optimum real O-STBCs are then identified and their BEP performance is compared with that of the benchmark schemes.

In this paper, we show, in both theory and simulation, that by transmitting two real orthogonal space-time block codes (O-STBC) on the I- and Q-channels with pulse-shaped offset QAM, we are able to achieve full rate transmit diversity for a 4 times 1 system with very simple "half-symbol" detection, i.e., the real I- and Q-symbols can be separately decoded. For this scheme, two families of pulse shapes of the offset QAM signal are considered: i) pulse shapes with zero inter-symbol interference (ISI) and ii) pulse shapes with controlled ISI between the I- and Q-channels. In the zero ISI case, the half-symbol decoding is optimum in the maximum likelihood sense and the system is able to achieve full transmit diversity. The associated bit error probability (BEP) performance is better than that of conventional full-rate, full-diversity quasi-orthogonal space-time block codes (QO-STBC), as well as rate-1/2 and rate-3/4 complex O-STBCs. To achieve good spectral confinement while maintaining decoding simplicity, we investigate pulse shape design techniques so that some performance gains can be traded off by introducing a controlled small amount of ISI at the sampling instants. We also extend the analysis to a 4 times 4 multiple-input multiple-output (MIMO) system, and derive the design criteria on how to construct the two real O-STBCs in order to minimize the performance degradation caused by the controlled ISI

This paper describes an adaptive space-time receiver with joint channel-data estimation (JCDE) to combat time-varying (TV) multipath channels in the presence of undesired cochannel interference (CCI). The receiver uses a colored Gaussian metric for sequence detection in order to suppress the CCI. The proposed scheme also uses the knowledge of the transmit filter for improved channel estimation to enhance performance. The algorithm is derived as a quasi-Newton scheme on a chosen cost criterion and is also locally convergent. The performance of this class of interference cancellers is examined through the pairwise error probability (PEP). Through these expressions we gain insight into the properties of the canceller. The effect of channel dynamics and identification mismatch on the PEP is also examined. To reduce implementational complexity, a hybrid delayed-decision feedback and JCDE scheme is also proposed. The performance is illustrated using numerical results in realistic transmission environments.

This paper describes a direct equalization approach for channels with some underlying structure. A semi-blind approach is taken here where a small amount of training symbols is available. A family of MMSE equalizers is obtained that includes some prior information about the channel structure. The channel structure assumed in this paper is that the channel vector lies approximately in the subspace of a matrix associated with the samples of the transmit pulse shape. Blind identifiability issues of the structured equalizer are also addressed. Numerical results using experimental indoor channel data indicate that these structured equalisers can achieve bit error rates that are significantly lower than traditional non-blind MMSE equalizers.

This paper describes an adaptive space-time receiver with joint channel and data estimation (JCD) to combat time-varying multipath channels in the presence of undesired co-channel interference (CCI). The receiver uses a colored Gaussian metric in the sequence detection to suppress the CCI. The proposed scheme also uses the knowledge of the transmit filter for improved channel estimation to enhance the performance. We gain insight into the interference suppression scheme through pairwise error-probability analysis. To reduce implementational complexity, a hybrid delayed-decision feedback and JCD scheme is also proposed. The performance is illustrated using numerical results in realistic transmission environments.

This paper presents a simple expression for the Cramer-Rao bound (CRB) for parametric estimation under differentiable, deterministic constraints on the parameters. In contrast to previous works, the constrained CRB presented does not require that the Fisher information matrix (FIM) for the unconstrained problem be of full rank. This is a useful extension because, for several signal processing problems (such as blind channel identification), the unconstrained problem is unidentifiable. Our expression for the constrained CRB depends only on the unconstrained FIM and a basis of the nullspace of the constraint's gradient matrix. We show that our constrained CRB formula reduces to the known expression when the FIM for the unconstrained problem is nonsingular. A necessary and sufficient condition for the existence of the constrained CRB is also derived.

In contrast to conventional array processing, in many applications, such as mobile communications, the concept of a parametric array manifold is ill defined. In mobile communications the loss of a well defined array manifold can be attributed to the complex propagation environment consisting of multiple local scatterers near the mobile and remote dominant scatterers, as well as other co-channel signals. In such applications, estimation methods developed in the conventional setting of array processing are of little use and blind estimation of the transmitted signals is of real importance. We present an unconditional maximum likelihood (UML) approach for blind estimation of multiple co-channel digital BPSK signals received by an antenna array, along with the array response matrix A. Based on the idea of fixed point iteration, an efficient algorithm is derived to obtain the UML estimate of A and the maximum a posteriori (MAP) estimates of the digital signals. Simulation results are presented to demonstrate the improved performance of the proposed UML method over the conventional conditional ML (CML) methods. An upper bound on the bit error rate is also presented.