In this work, the volume-based method for spectrum sensing is analyzed, which is able to provide the desirable properties of constant false-alarm rate, robustness against deviation from independent and identically distributed (IID) noise and being free of noise uncertainty. By computing the first and second moments for the signal-absence and signal-presence hypotheses together with using the Gamma distribution approximation, we derive accurate analytic formulae for the false-alarm and detection probabilities for IID noise situations. This enables us to develop theoretical decision threshold as well as receiver operating characteristic. Numerical results are presented to validate our theoretical findings.

Energy harvesting (EH) technology has emerged as a promising energy-supplier to unattended wireless systems. In the commonly used harvest-store-use (HSU) scheme, harvested energy is always stored in a battery before its subsequent use. The existence of storage loss in practical battery systems, however, unavoidably reduces the energy efficiency. In this paper, we therefore propose the use of a more efficient harvest-use-store (HUS) architecture for point-to-point data transmission, where the harvested energy is prioritized for use in data transmission while its balance/debt is stored in or extracted from the storage device. We derive the optimal energy polices, under the criterion of throughput maximization, for the HUS architecture on static and block fading channels, and investigate the properties of the resulting power allocation pattern. The optimization is done in the Lagrangian framework, uncovering the special structure of the optimal power pattern and obtaining a closed-form solution conditioned on the knowledge of the block locations for zero battery level. A dynamic programming (DP) based algorithm is developed for locating such blocks in the optimal power patterns. Numerical results are presented to demonstrate the properties of the proposed HUS architecture and its superior performance over the existing schemes.

Energy harvesting (EH) technology has become a promising alternative to solve the problem of the energy-limited wireless systems. As such, in this paper, we consider optimization of a single-user wireless communication system, where an EH transmitter operates in harvest-use-store (HUS) mode with the non-ideal rechargeable battery. With the storage efficiency and causality constraints, our key design goal is to maximize the throughput over a finite horizon transmission blocks under a non-fading channel scenario. Assuming the energy harvesting profile is known prior to transmission, we explore the properties of the optimal power allocation solution by the Lagrangian optimization algorithm (e.g., KKT). Further, based on this, we propose an optimal offline policy with the dynamic programming (DP) approach. Numerical results show that our proposed optimal transmission policy is indeed able to improve the overall throughput as compared to existing schemes.

In this paper, we investigate a joint relaying and superposition coding (SupC-R) transmission strategy for downlink networks. By relaxing the orthogonality constraint between different users, the SupC-R strategy facilitates coordination and channel sharing among different data flows, by which the disparity in the channel qualities of different users, as an inherent feature of downlink network topology, is utilized as benefits for potential performance gains. The inter-user interference due to non-orthogonality can be steered by smart design of superposition coding (SupC), including both the selection of the superposition factor and the decoding order. At the same time, channel sharing saves time and leads to more efficient utilization of network resources. The analytical and numerical results show significant gains of SupC-R over its conventional relaying counterpart. The effect of the channel disparity on the design of SupC and the performance of the resultant SupC-R strategy is highlighted.

This paper considers a conditional decode-and-forward (DF) based cooperative system where a source (S) with multiple (M) antennas transmits information to a single-antenna destination (D) with the help of multiple (L ≤ M - 1) single-antenna relays ({Ri}). The optimal transmit weighting vector at the source is not available in the literature due to the non-linear conditional DF operation, which renders the problem non-convex. To solve this problem, we first show that the optimal transmit vector for the single-relay system can be determined by comparing the S-D beamformer (maximum-ratio-transmit beamforming vector for the S-D link) with the one that utilizes “just sufficient” energy to activate the relay-link. However, it is difficult to directly apply the above idea to the multi-relay system, due to the fact that the S-R and S-D links are normally not orthogonal. To tackle this issue, we propose to utilize basis functions that are orthogonal to the S-D and S-R links, respectively, which enables the activating of one S-R link without considering the S-D link and the other S-R links. We then apply the new basis functions to the multi-relay system and propose a selective relay-activation algorithm, where the optimal solution is obtained by comparing the S-D beamformer with schemes that selectively activate different combinations of the relay-links. The selective relay-activation algorithm is different from the conventional water-filling in the sense that the energy is filled to discrete levels to activate the S-R links, a unique feature arising from the conditional DF operation.

In this paper, we tackle the energy efficiency (EE) issue in uplink virtual MIMO systems, which requires the optimization of two interlaced parameters: the number of constituent mobile users in the virtual MIMO and their corresponding power allocation. By exploiting the fact that increasing the number of active users can increase the number of contributors to the total EE on one hand but reducing the diversity order for each single user on the other, we can show the existence of an optimal transmission mode and find a simple way for its search. Through in-depth analysis, we show the existence of a unique globally optimal power allocator for the case without power constraints, and further reveal the impact of power constraints upon power allocation, as compared to its global counterpart, aiming to provide a powerful means for power-constrained EE optimization. Finally, we establish theories, for homogeneous networks, to narrow down the search range for possible transmission modes, leading to a significant reduction of computational complexity in optimization. Simulation results are presented to substantiate the proposed schemes and the corresponding theories.

Driven by green communications, energy-efficient transmission is becoming an important design criterion for wireless systems, aiming to extend the life cycle of batteries in mobile devices. In this paper, we tackle the energy efficiency (EE) issue in uplink virtual multiple-input multiple-output (MIMO) systems, which requires the optimization of two interlaced parameters: the number of constituent mobile users in the virtual MIMO and their corresponding power allocation. The former parameter is a structural parameter defining the size of the virtual MIMO (usually known as the transmission mode) and its optimization relies on the method of enumeration. The difficulty is further aggravated by the fact that the EE is a non-convex function of power, even for a given transmission mode. By exploiting the fact that increasing the number of active users can increase the number of contributors to the total EE on one hand but reducing the diversity order for each single user on the other, we can show the existence of an optimal transmission mode and find a simple way for its search. Through in-depth analysis, we show the existence of a unique globally optimal power allocator for the case without power constraints under the assumption of zero-forcing receivers, and further reveal the impact of power constraints upon power allocation, as compared to its global counterpart, aiming to provide a powerful means for power-constrained EE optimization. Finally, we establish theories, for isometric networks, to narrow down the search range for possible transmission modes, leading to a significant reduction of computational complexity in optimization. Simulation results are presented to substantiate the proposed schemes and the corresponding theories.

The sufficient condition for a blindly interference-aligned 2-user 2 × 1 broadcast channel (BC) in homogeneous block fading to achieve its maximal 4/3 degree-of-freedom (DoF) is well understood. However, the condition for the general case, i.e., a homogeneous K-user 2 × 1 BC, to achieve the corresponding optimal 2K/2+K-1 DoF remains unsolved and is, thus, the focus of this paper. Here, a K-user 2×1 BC is said to be BIA-feasible if it achieves the optimal DoF via blind interference alignment (BIA). In this paper, we cast this general BIA-feasibility problem in the framework of finding solutions for a system of linear Diophantine equations. Then by studying the solvability of the Diophantine system, we derive the necessary and sufficient conditions on the K users' fading block offsets to ensure the BIA feasibility of the K-user BC. Using the results above, we also examine a 2 × 1 broadcast network with M homogeneous users, in which their offsets are independent of one another and are uniformly distributed over a coherence block. We show by simulations that when the network contains M = 11 homogeneous users, there is more than 95% chance of finding 3 users to form a BIA-feasible 3-user 2 × 1 BC. Furthermore, increasing M to infinity ensures a virtual multiple-input multiple-output (MIMO) channel to be formed from the DoF perspective.

Channel estimation for an orthogonal frequency-division multiplexing (OFDM) broadband system over a doubly selective channel is very challenging. This is mainly due to the significant Doppler shift, which results in a time-frequency doubly-selective (DS) channel. The DS channel features a large number of channel coefficients, which introduces inter-carrier interference (ICI) and forces the need for allocating a large number of pilot subcarriers. To tackle this problem, in this paper we propose a novel channel estimation scheme based on distributed compressive sensing (DCS) theory. Taking advantage of the basis expansion model (BEM) and the channel sparsity in the delay domain, we transform the original DS channel into a novel two-dimensional channel model, where several jointly sparse BEM coefficient vectors become the estimation goal. Then a special decoupling form originating from a novel sparse pilot pattern is designed for such estimation, which results in an ICI-free structure and enables the DCS application to make joint estimation of these vectors accurately. Combined with a smoothing treatment process, the proposed scheme can achieve significantly higher estimation accuracy than the existing ones, although with a much smaller number of pilot subcarriers. Theoretical analysis and simulation results both confirm its performance merits.

Energy-efficient transmission is increasing in importance for wireless system design because of limited battery power in mobile devices. In this paper, we consider energy efficiency optimization in uplink virtual MIMO systems. First, accurate closed-form expressions are derived for the achievable energy efficiency for both multi-user (MU) transmission mode and single-user (SU) transmission mode, which are based on the ergodic throughput, transmit power and circuit power. Then, we demonstrate the existence of unique globally optimal energy efficiency for SU and MU mode, respectively. Since users have data rates requirement and peak power limits, we further consider power constraint, and develop joint mode switching with power loading schemes to optimize energy efficiency for both homogeneous and heterogeneous networks. Finally, our simulation results show that the proposed adaptive transmission strategies significantly improve energy efficiency.

This work considers linear precoding strategies for multiple-input single-out (MISO) interference channels with channel mean feedback at transmitters, where the interference at each receiver is treated as additive noise. The challenge here is that previous precoder designs with perfect channel state information (CSI) at transmitters do not apply and new approaches are required. Based on the Laplace transform order, an altruistic non-equilibrium strategy, i.e., the stochastic zero forcing, is first proposed under practical assumptions, generalizing the traditional zero forcing which requires perfect CSI. Interestingly, the precoding matrices here are all rank-one beamformers as in the traditional zero forcing. The competitive use of the common physical media in MISO interference channels is also formulated as a strategic noncooperative game. In contrast to the perfect CSI case with a unique rank-one Nash equilibrium, with channel mean feedback, the Nash equilibria here are not necessarily rank-one in general. Nevertheless, when achieved by the rank-one beamforming, the equilibrium is unique and convenient for implementation. Accordingly, the condition for beamforming to achieve the equilibrium is derived. Comparisons of the above two strategies reveal no overall dominance of one over the other, thereby establishing stochastic zero forcing as an alternative to the Nash equilibrium designs.

This paper investigates the optimal source transmit precoding to maximize the ergodic mutual information between the input and the output of a noncoherent amplify-and-forward relay channel, with multiple antennas at the source and with a single antenna at both the relay and the destination. It is assumed that only the source-relay channel mean information is available at the source. The challenge here is that relaying introduces a nonconvex structure in the objective function. Therefore, previous methods dealing with channel mean feedback, which generally require the concavity of the objective function, cannot be applied. To circumvent the difficulty at hand, a different approach based on stochastic ordering is employed. The stochastic optimization problem here is ultimately transformed into the comparison of two nonnegative random variables in the Laplace transform order. It is shown that the optimal source transmit strategy is to transmit along the known channel mean and its orthogonal eigen-channels. Our result subsumes as an asymptotic case the optimal precoding for multiple-input single-output (MISO) channels without relaying under mean feedback. Furthermore, the analysis can be partially extended to the case with multiple antennas at the relay. Numerical examples are provided to complement and corroborate the analysis.

Two linear precoding strategies are investigated for multiple-input single-out (MISO) interference channels with channel mean feedback at transmitters. The interference at each receiver is treated as additive noise. The challenge here is that previous analysis with perfect channel state information (CSI) at transmitters does not apply. Based on stochastic ordering, the altruistic non-equilibrium stochastic zero forcing strategy is first proposed, generalizing traditional zero forcing which requires perfect CSI. Interestingly, the precoding matrices here are all rank-one as in traditional zero forcing. The competitive use of the common channel is also formulated as a strategic game. Different from the perfect CSI case, with channel mean feedback, infinitely many Nash equilibria exist in general, which are not necessarily rank-one. Comparisons of the above two precoding strategies reveal no overall dominance of one over the other, thereby establishing stochastic zero forcing as an appealing alternative to the prevailing Nash equilibrium strategies.

Stochastic optimization arising from precoding in a multi-antenna fading channel with channel mean feedback to maximize data rates is important but challenging. The use of relaying further complicates the situation, as it may induce a nonconvex structure in the objective function, thereby excluding the use of existing approaches which re quire convexity or concavity. To deal with challenges as such, this paper presents a new framework for solving a class of stochastic optimization problems. The analysis here involves the comparison of two nonnegative random variables in the Laplace transform order. Our framework is particularized to optimal precoding for maximum ergodic or effective capacity in multi-antenna channels with or with out relaying assuming channel mean feedback, where the objectives may or may not have convexity or concavity. The application to stochastic power allocation is also discussed.

This paper investigates the optimum source transmission strategy to maximize the capacity of a multiple-input single-output (MISO) amplify-and-forward relay channel, assuming source-relay channel mean feedback at the source. The challenge here is that relaying introduces a nonconvex structure in the objective function, thereby excluding the possible use of previous methods dealing with mean feedback that generally rely on the concavity of the objective function. A novel method is employed, which divides the feasible set into two subsets and establishes the optimum from one of them by comparison. As such, the optimization is transformed into the comparison of two nonnegative random variables in the Laplace Transform order, which is one of the stochastic orders. It turns out that the optimum transmission strategy is to transmit along the known channel mean and its orthogonal eigenchannels. The condition for rank-one precoding (beamforming) to achieve capacity is also determined. Our results subsume those for traditional MISO precoding with mean feedback.

In this paper, the aggregate interference in a finite-area multi-antenna wireless ad hoc network is statistically characterized. While most of the existing studies model the spatial distribution of transmit nodes as a Poisson point process in an infinite plane, a binomial point process is adopted here to better characterize the node distribution in a finite area. In the test link, maximum-ratio combining (MRC) is employed at the receiver, whereas spatial multiplexing or transmit antenna selection is employed at the transmitter depending on the availability of limited feedback. Moments of aggregate interference as well as outage probability formulas are obtained. Interestingly, for a finite network, our analysis establishes the optimality of single-stream transmissions in spatial multiplexing with a MRC test receiver, and justifies the use of transmit antenna selection for further enhancing the outage performance with limited feedback. Simulations are provided to corroborate the analysis.

Using the multitaper spectrum (MTS) for spectrum sensing in cognitive radio has been investigated by a number of researchers. An MTS detector can be applied to various operational environments with the knowledge of perfect or inaccurate noise variance. So far, however, no systematic procedure is available for the determination of theoretical thresholds and their corresponding detection performance. In this paper, we tackle this issue, ending up with various closed-form analytic formulas for the probabilities of detection and false alarm with different settings. The validity of theoretical formulas are examined intensively through numerical results and computer simulations.

Conventional cooperative relaying schemes usually process the network CSI in a centralized way by setting one central node where decisions, such as relay selection, are made by relying on information from all channels. In this paper, we propose a novel distributed relay selection scheme for Decode-and- Forward networks. In this scheme, each relay decides to participate in cooperation based on link status of its own, thereby eliminating the need for relay coordination. Outage performance of the proposed distributed system is then investigated and general results applicable to an arbitrary number of relays are provided in closed-form.

In this paper, we propose a novel equalization scheme combining the Tomlinson-Harashima precoding (THP) and linear precoding for frequency selective fading channels. The newly introduced linear precoder at the transmitter is jointly designed with the feedforward filter (FFF) and the feedback filter (FBF) of the THP unit, aiming to minimize the mean-square-error (MSE) of the receive signal. The final solutions obtained are closely related to a novel matrix decomposition named Geometric-Mean Decomposition. It is shown that the new scheme eventually attains the receive SNR/SINR upper bound of the conventional non-linear equalization systems, thus enjoys much better error performance. Furthermore, the implementation issue is considered by proposing a suboptimal scheme which enables the designer to take a tradeoff between the system performance and complexity. Numerical results are presented to demonstrate the superior performance of the proposed schemes.

Full-rate full-diversity (FRFD) space-time block codes (STBCs), which are originally designed for independent and identically distributed (i.i.d.) multiple-input multiple-output (MIMO) channels, may suffer from severe performance degradation in the presence of channel correlation. A feasible solution is to adopt a linear precoder to match the eigen beams of these codes with that of the channels. The precoder design addressed in the literature is applicable only to the cases of orthogonal/quasi-orthogonal STBCs in semi-correlated MIMO channels, where the minimum codeword difference matrices (CDM) are either equal, or reducible, to the identity matrix. A general FRFD STBC, however, can have multiple CDMs which, when interacting with a general doubly correlated MIMO channel of covariance matrix feedback, call for a new design criterion for precoding which is the focus of this paper. Furthermore, a modified sphere decoder is also proposed to resolve the problem of degenerated equivalent channel matrix caused by the precoding at low SNRs. Numerical results are presented to demonstrate the superior performance of the resulting optimal precoder when used alongside various real- and complex-rotation based FRFD STBCs.

Optimal transmit/receive diversity (TRD) is one of the most important configurations for wireless multiple-input multiple-output (MIMO) systems, due to its good performance and ease of implementation. Though investigated intensively, the performance of optimal TRD in general correlated fading with cochannel interference is still not well understood. Since the optimal TRD's output instantaneous signal-to-interference-plus-noise ratio (SINR) is equal to the largest sample eigenvalue of a quadratic form involving signal and interference channel matrices, directly determining the probability density function (pdf) of this eigenvalue has been a prevailing approach in the literature. Given the nonlinearity involved in the quadratic form, however, finding such a pdf is not simple except for some special channel conditions. In this paper, we formulate the problem, in a totally different framework, as testing the positive-definiteness of a random matrix whereby the theory of matrix-variate distributions can be invoked to obtain exact solutions in terms of special functions. The solutions are very general including most of existing results as a special case and allowing for the correlation structures of both signal and interferers to be arbitrary at both transmitter and receiver ends. Numerical results are presented to validate the theoretical analysis.

The energy based test is a popular detection scheme for cognitive radio (CR). However, it is infeasible or confronted with difficulty in threshold determination when a reference noise power level is unavailable or inaccurate. In fact, the presence of a primary signal not only changes the received signal energy, but also its correlation structure. In this paper, we show how to exploit information in both the energy and correlation for the detection of CR signals in different operational environments where the reference noise power level can be perfectly known, inaccurate, or completely unavailable. Different types of detectors are derived with emphasis on their philosophy and techniques for their threshold determination. Numerical results are presented for illustration of the theory and performance of the proposed detectors.

Spectrum sensing is inevitable for cognitive systems to locate the spectrum holes. In the IEEE 802.22 proposal, very short quiet periods are arranged inside frames to perform a coarse intra-frame sensing whose results are then utilized to decide whether a fine inter-frame sensing is needed. The purpose of intra-frame sensing is to make an early alarm about the presence of primary users. However, the placement of short quiet periods in intra-sensing requires quiet period synchronization and degrades the transmission rate. In this paper, we propose active sensing as an alternative for intra-frame sensing to save the short quiet periods so that the system throughput is increased. In active sensing scheme, the sensing is performed by some inactive CPEs when the cognitive system is active. The motivation comes from the facts that we have much more received samples for active sensing and we only need a coarse result.

Fully exploiting the phase and magnitude information in received data is crucial to the detection of cognitive radio signals, and this is usually done in the time domain. In fact, the same set of information can also be exploited in the frequency domain in the form of power spectrum. The most appealing one is the multitaper spectrum (MTS) estimator, which enjoys a high estimation accuracy and relatively low computational complexity making it an attractive candidate for use in CR networks. In this paper, we investigate a MTS-based CR detector, aiming to fully understand its capability in exploiting the advantage of MTS. We obtain simple expressions for detection probability and constant false-alarm rate whereby a threshold can be easily determined. Numerical results are presented to verify the theory and to demonstrate the superior performance of the proposed scheme.

The optimal transmit-beam number and power allocation over generic correlated multiple-input multiple-output (MIMO) Rayleigh fading channels are investigated. By fully exploiting the algebraic structures and properties of the optimization problem, we obtain a procedure for determining the thresholds of optimal beam number and derive a set of elementary equations for optimal power allocation, which can be efficiently solved by using a Broyden-like method. A closed-form criterion for the optimality of beamforming is also proposed. Numerical results are presented for illustration.

Analysis of mutual information is important to wireless transmission over fading channels, and is usually done by assuming perfect channel state information (CSI) available at the receiver. In many practical applications, however, the CSI must be estimated by sending a limited number of pilot symbols and thus, can suffer from considerable inaccuracy. The influence of CSI inaccuracy on achievable mutual information, though analyzed in the past, is not well understood. The difficulty arises from the presence of a product term of signal and channel estimation error in the received signal model, and the lack of appropriate tools to determine its probability density function. This situation forces the adoption of a bounding technique in current literature by treating the product term either as a signal component or as a noise component. In this paper, we take a different methodology by accurately fitting the received signal with the multivariate Pearson's type-7 (MPT-7) distribution. The new results are simple in expression, very accurate as evidenced by simulation, and capable of directly revealing the dependence of the achievable mutual information on a particular channel estimator.

Distributed systems with multiple amplify-andforward (AF) relays are very appealing, due to their ease of implementing space diversity. Although their performance on synchronous flat-fading channels was well understood, the corresponding design and optimization in asynchronous frequency selective fading (AFSF) channels remains unsolved. In this paper, we tackle the problem in the information-theoretic framework, revealing that multi-relay amplify-and-forward (MR-AF) systems over AFSF channels can be better understood through the concept of virtual sub-channels. Each relay node virtually performs two functions, appropriately amplifying sub-channel signals on one hand and serving as a local switching center on the other. System design, therefore, reduces to the determination of optimal amplification factors, switching matrices, and power allocation among the source, relays and relevant sub-channels. The optimization is implemented in a layered structure. The effects of asynchronism and knowledge of channel information on mutual information are also investigated.

Gaussian signals are widely assumed in various design and analysis since the classical work of Shannon. However, the optimality of Gaussian signals is valid only when perfect channel information is available at the receiver. In many practical applications, only a channel estimate is available with certain estimation errors. It is therefore of practical importance to ask what is the optimal input distribution for such a system. The optimization can theoretically be formulated in the framework of variational calculus which, however, is in general mathematically intractable. This letter therefore takes a compromise between the optimality and tractability by confining our optimal search within the popular Pearson's distribution system. The result is Pearson's type-VII (PT-7) distribution and its superiority over the Gaussian distribution is confirmed by both theoretical analysis and computer simulations.

Gaussian inputs and nearest neighbor decoder are optimal choices for the transceiver when perfect channel information is available. However, channel uncertainty is inevitable in practical systems due to additive noise and channel variation. Under such circumstances, Gaussian inputs are no longer optimal whereas the nearest neighbor decoder even loses part of the mutual information provided by Gaussian codebooks. In this letter, we tackle the issue of decoder optimization for channels with Gaussian inputs and channel estimation errors. The result is a normalized nearest neighbor decoder which is proved, by a semi-analytical method, capable of fully obtaining the mutual information with Gaussian inputs. We further show that the proposed decoder is capable of achieving the performance improvement provided by a better non-Gaussian codebook.

Although optimal transmit directions over generic correlated multiple-input multiple-output (MIMO) Rayleigh fading channels are well known to be the eigen beams defined by the transmit covariance matrix, general techniques for determining optimal transmit-beam number and power allocation remain unavailable. In this paper, by formulating the problem in the framework of Lagrange multipliers and by fully exploiting the algebraic structures and properties of the optimization problem at hand, we obtain a simple criterion for optimal beam number determination and a set of elementary equations for optimal power allocation, which can be efficiently solved by using the recursive algorithm derived in this paper. Numerical results are presented for the illustration of the theory.

Analysis of mutual information for wireless systems is usually performed by assuming perfect channel state information (CSI). In many practical applications, however, channel uncertainty occurs due to channel variation and additive noise. Such uncertainty introduces a product term between signal and channel estimation error in the received signal whose probability density function is thus difficult to determine. This situation makes the direct evaluation of mutual information difficult and forces the adoption of a bounding technique in current literature by treating the product term either as a signal component or as a noise component. In this paper, we solve the problem by accurately fitting the received signal with the multivariate Pearson's type-7 (MPT-7) distribution. The new results are simple in expression, very accurate as evidenced by simulation.

The energy spreading transform (EST) has recently been proposed as a technique for the multiple input and multiple output (MIMO) fading channels, ending up with an EST-based iterative detection scheme for MIMO systems. In this paper, we develop a novel concept of capacity with iterative detection, which enables us to evaluate the contribution of the iterative data processing employed in this MIMO scheme to the achievable rate region. We then discuss the diversity gain of the EST-based MIMO system. In particular, we address the case where a technique of data rate adaption to signal-to-noise ratio (SNR) is employed, given that the achievable rate increases with the increment of SNR. Some simulation results are also given to demonstrate the theoretical results obtained in this paper.

The constellation design for differential space-time modulation usually requires to construct L (constellation size) unitary matrices making the design complexity increasing rapidly with L. In this correspondence, we propose a new construction technique, which exploits the rotational invariance of unitary matrices and the property of MPSK modulation. The proposed constellations are derivable from a smaller set of D = L/M unitary matrices (via rotations defined by an M-ary PSK symbol) which, in turn, are parameterized by two unitary matrices U1and U2. They share some good property of group constellations thereby considerably simplifying the optimization of U1and U2. They also possess other good properties which allow for simplified maximum likelihood (ML) decoding. Extensive numerical examples are presented to demonstrate that the proposed constellations in general have larger diversity products than other constellations and thus, better error performance.

Transmitter optimization for correlated multiple input single-output (MISO) channels with average channel information feedback is of theoretical and practical importance. It was tackled in the past by mainly focusing on cases with either mean or covariance feedback alone. The difficulty with generic MISO optimization arises from the fact that the treatment of optimal beam directions and power allocation are no longer separable, thereby making the problem nearly impossible to be tackled on the basis of its current formulation. We therefore take a different philosophy by representing the derivative of the ergodic capacity as a single integral and linking it to the channel characteristic function. This new formulation allows us to obtain the sufficient and necessary conditions, simply in the form of two vector equations which can be efficiently solved by a Newton-Raphson type algorithm developed in this paper. Numerical results are presented for illustration.

The use of ultra wideband (UWB) technology for high-resolution ranging is widely addressed in the literature, and most these studies assume the use of a correlation detector to determine the arrival time of the first path component. The correlation detector well performs in environments without signal distortion. However, dense multi-path propagation and frequency selective fading, as encountered in a typical UWB environment, force the received UWB signal to behave like a random waveform. Such a waveform is multi-dimensional in the sense that any single preset template can only capture partial signal energy for ranging. In coping with this situation, we show in this paper how to use multi-dimensional detectors for enhancing the ranging performance. The superiority of the new detectors to the conventional one is theoretically analyzed and confirmed through simulations based on real UWB data.

Ultra wideband (UWB) impulse radio (IR) is a prospective transmission technology for low-rate indoor communications, as described in the physical-layer proposals for IEEE 802.15.4a wireless personal area networks (WPAN). Time hopping (TH) code division multiple access (CDMA) is considered as an access scheme' for multiuser UWB-IR systems. The TH- CDMA system widely addressed in the literature adopts binary phase-shift keying (BPSK) with coherent detection, which requires accurate channel estimation and thus increasing the implementation complexity. In this correspondence, we suggest using TH-CDMA-PPM (pulse position modulation) with non-coherent detection to simplify the receiver structure. The influence of different combinations of TH and CDMA processing gains on error performance of the new scheme is analyzed and numerical results are presented for illustration.

The influence of mutual coupling among multi- antenna systems is usually not negligible due to limited antenna spacing available in practice. A thorough understanding of such influence, however, is still unavailable in the literature, although it is important to the design of a transmit strategy. In this paper, by formulating the equivalent channel matrix by S-parameters that characterize mutual coupling, we obtain an explicit expression for the channel capacity. The maximization of the channel capacity leads to the optimal precoding strategy for the transmitter. Numerical examples are presented to illustrate the method.

Due to its finite-time resolution, the ultra wideband (UWB) technology has been proposed for use in high-resolution ranging. Such ranging systems employ several pingers each having a correlator to determine the direct-path component in the received signal. The problem with a correlation detector is that the ranging performance can significantly drop as the UWB signal experiences distortion, caused by dense multipath propagation. In this paper, we therefore use, instead, a multi- template detector, whose templates are derived from the covariance structure of distorted UWB signals. The superiority of the new detectors to the conventional one is theoretically analyzed and confirmed through simulations, on the basis of real UWB data.

Determination of the coherence bandwidth for multipath fading channels is of great importance for wireless systems design. However, the calculation of the coherence bandwidth so far has relied on an empirical formula. In this paper, we derive an exact coherence bandwidth formula for Rayleigh fading channels. The use of the new formula is illustrated by numerical results.

Optimizing the input covariance matrix of a multiple-antenna transmit system with partial channel-structure feedback is an important issue to fully exploit the channel capacity. Efficient design of the optimal input covariance matrix, however, remains unavailable although its eigenvector structure was clearly revealed in a recent publication. In this paper, we obtain an explicit derivative function forming a solid basis for optimizing the optimal input covariance matrix. This new derivative expression enables us to further develop an efficient iterative algorithm for determining the optimal eigenvalues. The technique is illustrated through numerical examples.

As described in the physical-layer proposals for IEEE 802.15.4a wireless personal area networks (WPAN), ultra wideband (UWB) impulse radio (IR) is a prospective transmission technology for low-rate indoor communications. Time hopping (TH) code division multiple access (CDMA) is considered as an access scheme for multiuser UWB-IR systems. The TH-CDMA system widely addressed in the literature adopts binary phase-shift keying (BPSK) with coherent detection, which requires accurate channel estimation and thus increasing the implementation complexity. This paper suggests using TH-CDMA-PPM (pulse position modulation) with non-coherent detection to simplify the receiver structure. The error performance of the new scheme is analyzed and numerical results are presented for illustration.

Optimum combining (OC) is a powerful means for combatting co-channel interference. Its performance, however, is difficult to analyze. The prevailing methodology in current use is to neglect the influence of additive white Gaussian noise (AWGN). Inclusion of AWGN into the analysis usually leads to mathematical intractability, except for some extreme cases. In this letter, we formulate the problem in the framework of hypergeometric functions, so that their good properties can be exploited to enable the analysis to account for the influence of AWGN and co-channel interference simultaneously. We obtain closed-form solutions to the characteristic function (CHF) of the signal-to-interference-plus-noise ratio at the OC output for three important operational scenarios in Rayleigh fading, although the general solution still needs further effort to simplify. The assumptions made here are that both signal and interferers suffer from Rayleigh fading, and the number of interferers is not less than the number of antennas. The use of resulting CHF formulas is illustrated through their application to the bit-error and outage performance evaluation of OC.

Coherence bandwidth is an important characteristic of multipath fading channels, serving as a useful tool for wireless systems design. Regardless of its importance, the determination of the coherence bandwidth, so far, has relied on an empirical formula. In this correspondence, we derive an exact coherence-bandwidth formula for Rayleigh fading channels. The use of the new formula is illustrated by numerical results.

For a space-time coded system subject to flat Rayleigh fading, we formulate the pairwise error probability (PEP) in a unified expression, which accounts for the cases of perfect channel-state information, imperfect channel estimation, and unknown channel. The unified PEP expression is then bounded by an exponential-type inequality leading to a tight upper bound on the PEP. The bound indicates that to design a good code set, we not only need to maximize the geometric mean of the nonzero eigenvalues of the code difference matrix, but also minimize their harmonic mean.

Orthogonality restoring combining (ORC) is appealing for the downlink of multicarrier code-division multiple- access (MC-CDMA) since it can eliminate multiple access interference (MAI) which would otherwise fundamentally limit the CDMA system performance. The ORC output instantaneous signal-to-noise ratio (SNR), however, takes the form of a harmonic mean of SNRs on different subcarriers, making its error performance difficult to analyze. In this paper, we tackle the problem in the framework of characteristic functions (CF) ending up with useful results for various modulation schemes including M-ary phase-shift keying (MPSK) and M-ary quadrature amplitude modulation (MQAM). The general solution for arbitrary real m can be evaluated numerically, and reduces to closed form for m being an odd multiple of half. Extensive simulations are conducted to verify the theoretical analysis. It is found that in general MQAM outperforms MPSK, and the error performance of MC-CDMA with ORC is insensitive to the number of subcarriers and to the correlation among subcarriers.

For a space-time coded system subject to flat Rayleigh fading, we formulate the pairwise error probability (PEP) in a unified expression, which accounts for the cases of perfect channel-state information, imperfect channel estimation, and unknown channel. The unified PEP expression is then bounded by an exponential-type inequality leading to a tight upper bound on the PEP. The bound indicates that to design a good code set, we not only need to maximize the geometric mean of the nonzero eigenvalues of the code difference matrix, but also minimize their harmonic mean.

Channel estimation is a key issue to OFDM systems no matter for inter-carrier interference cancellation or for symbol detection. The difficulty with a fast-fading OFDM channel lies in that the channel over one OFDM symbol interval is characterized by a channel matrix whose dimensions much exceeds the total number of subcarriers. Consequently, the channel estimation techniques developed for slowly fading channels are of little use. In this paper, we show how to parsimoniously parameterize an OFDM channel matrix by representing each path-coefficient vector through its eigen structure. The resulting unknown parameters are much less than that of the original channel matrix making their estimation possible. The new technique is superior to its conventional counterpart as evidenced by simulation results.

Received ultra wideband (UWB) signals in most indoor environments are stochastic in nature, typically composed of abundant multi-path components with random attenuation and arrival time. A commonly adopted detection strategy is to use a chosen deterministic template to correlate the received signal segment by segment, and only those segments having significant cross-correlation with the template are selected, temporally synchronized and co-phased in their projections for coherent combining. Correlating a deterministic template with a random signal usually results in only partial energy captured by the receiver since a random signal is of multidimensions. In this paper, we construct a receiver with multiple orthogonal branches to fully capture the signal energy, in much the same way as a quadrature receiver does in conventional digital communications. The local reference signals are derived from the orthogonal expansion of UWB signals. The random projections of a UWB signal onto different orthogonal basis functions are non-coherently combined, leading to the concept of dimension diversity. Dimension diversity can be either used alone, or alongside a Rake receiver to further exploit path diversity. The error performance of proposed receivers is analyzed, and their superiority over the conventional ones is examined by numerical results based on real UWB data

Lognormal approximation to a sum of lognormal variables is widely addressed in wireless communications. Its discrepancy from simulation results, however, is often reported in the literature. In this correspondence, we reexamine the issue of fitting a lognormal sum in a more rigorous framework of model selection in the Pearson system. It is found that over a general parameter setting for lognormal sums, a much better approximation is the Pearson type IV distribution whose parameters can be easily determined through simple arithmetic operations. Numerical examples are presented for illustration

Wireless ultra-wideband (UWB) receivers usually employ a deterministic clean pulse or pulses derived from a Gaussian monocycle as a template for correlation. A deterministic template cannot be expected to have high correlation with random UWB signals at all times. Such a mismatch can significantly degrade the system error performance. In this letter, a deterministic template is designed to maximize the energy capture capability on ensemble average, ending up with the eigen-based correlator. The eigen-based correlator can be used alone or alongside path diversity to further enhance signal detection. The new receivers outperform their counterparts using a clean pulse, as shown by theoretical analysis, and demonstrated by numerical results based on real UWB data

Due to the functional complexity of its signal-to-interference (SIR) ratio, the outage probability of maximum ratio combining is available only for certain independent and identically distributed (i.i.d.) fading environments. In this paper, we partially relax this restriction by allowing the signal channel-gain vector to follow a general fading distribution with arbitrary spatial correlation. The problem is tackled in a novel framework. The key step is to represent the probability density of the reciprocal of SIR, conditioned on signal vector, as the higher-order derivative of a simple exponential function in signal power whereby a generic formula for outage probability can be determined. The application of the generic formula to Rayleigh, Rician, and Nakagami faded signals is elaborated. Numerical results are also presented for illustration.

In this paper, we investigate the performance of using a square array of four antennas for selection combining (SC), maximal-ratio combining (MRC) of Nakagami correlated signals. The closed form of average output signal-to-noise ratio (SNR) and bit error rate (BER) with SC for arbitrary 4 correlated branches will be derived and the expression of BER with MRC is also derived by utilizing the method of characteristic function (CF). Two models for angle of arrival (AOA), e.g. uniform and Gaussian, will be considered, as well as the comparison between their system performances. The effect of correlation coefficients and fading factor on the system performance are discussed by numerical results, which show that the uniform distributed AOA system outperforms the Gaussian distributed AOA system with small angular spread.

We analyze the error performance of minimum selection generalized selection combining (MS-GSC), in which the minimum number of diversity branches are selected such that their combined signal-to-noise ratio (SNR) is above a given threshold. A flat Rayleigh fading channel with independent and distinctly distributed branch SNR is considered. By transforming the ordered instantaneous branch SNR to their differences, we derive the distribution of the number of selected branches in closed-form. We then modify the derivation of this distribution to get the characteristic function (c.f.) of the combiner output SNR. This c.f. is used to obtain the symbol error probability for different coherent digital modulation schemes.

We present a new approach to design unitary constellations for differential space-time modulation. By exploiting the rotational invariance of unitary matrices and the property of M-ary PSK symbols, the proposed constellations of size L are derivable from a smaller set of D=L/M unitary matrices (via rotations defined by M-ary PSK symbols) which, in turn, are parameterized by two unitary matrices U/sub 1/ and U/sub 2/. The proposed constellations share some good properties of group constellations thereby considerably simplifying the optimization of U/sub 1/ and U/sub 2/. They also possess many other good properties which, when exploited, allow for simplified maximum likelihood decoding. Extensive numerical examples are provided to demonstrate that the proposed constellations in general have larger diversity products than other constellations.

Wireless ultra-wideband (UWB) receivers usually employ a deterministic clean pulse or a pulse derived from a Gaussian waveform as a template for correlation. A deterministic template is not expected to have the capability of correlating highly with random UWB signals all the time. The resulting mismatch, however, can significantly degrade the system error performance. We therefore optimize a deterministic template to achieve the maximum energy capture capability in the sense of ensemble average. The UWB correlator using the optimal deterministic template can be employed along with combining to enhance signal detection. The resulting receivers outperform their counterparts using a clean pulse, as evidenced by theoretical analysis and numerical results based on real UWB data.

No systematic procedure for tightly bounding the average capacity of multiple-input-multiple-output (MIMO) correlated Rician fading channels is available in the literature. In addition to the involvement of a highly nonlinear log-determinant operator in the conditional capacity expression, the difficulty arises from the complicated noncentral Wishart distribution of channel sample matrix. In this paper, we tackle the problem with arbitrary antenna correlation existing either at the transmitter or at the receiver, but allowing for the numbers of the transmit and receive antennas to be arbitrary. By introducing an exact determinant expansion and by finding an explicit expression for the general moment of the determinant of the channel sample matrix, we obtain a general upper bound for the average channel capacity. To obtain a general lower bound, we construct and prove a multivariate convex function with each of its variables being the log-determinant function of a complex noncentral Wishart-distributed matrix. We further show that the general bounds so obtained can be simplified to explicit expressions for Rician fading channels with arbitrary semicorrelation and a mean matrix of rank one. The new results are simple, easy to be used, and superior in tightness as evidenced by intensive numerical examples.

The error performance of M-ary differential phase-shift keying on Rayleigh fading channels is widely analyzed in the framework originated by Pawula, and the results usually take the form of an integral. In this letter, we formulate the same problem in a different framework, and solve it by using a linear prediction-based technique resulting in a simple solution in closed form.

We analyze the problem of optimum combining with a single spatially correlated interferer in white Gaussian noise and Rayleigh fading by focussing on the conditional characteristic function (c.f.) of the combiner output signal-to-interference-plus-noise ratio, given the interference propagation vector. Unconditioning of this c.f. using the interference statistics, along with a finite-range integration, results in the symbol error probability (SEP) integral, which is a common integral factor to most digital-modulation schemes. We obtain an exact expression, partly in closed form, for the SEP integral. For the case of large values of average signal-to-noise ratio and signal-to-interference ratio per antenna element, we obtain closed-form asymptotic formulas for the SEP integral. Using the SEP integral, we can easily evaluate the symbol error performance of various modulation schemes. The correctness of our analytical results are verified by some numerical examples.

Due to the difficulty in its exact analysis, the ergodic (average) channel capacity of correlated multiple-input multiple-output (MIMO)-fading channels is evaluated mainly by resorting to bounding techniques. Most of bounding techniques, however, are focused on the upper bound, and exploit the information in a Wishart-distributed sample covariance matrix solely in the form of its determinant or mean value. In this paper, we rigorously represent the determinant of form det(I + /spl gamma/S) in terms of all possible principal submatrices of S, thereby allowing us to exploit the fine structure of S to derive an upper bound for the channel capacity. To obtain a lower bound, we carefully construct a multivariate function and verify its multivariate convexity. Besides their simplicity in mathematics, the new bounds show superior tightness, as evidenced by various numerical examples.

No systematic procedure for tightly bounding the average capacity of MIMO correlated Rician fading channels is available in the literature. The difficulty arises from the complicated non-central Wishart distribution of channel sample matrix, in addition to the involvement of a highly nonlinear log determinant operator in the conditional capacity expression. In this paper, we tackle the problem with arbitrary antenna correlation existing either at the transmitter or at the receiver, but allowing for the numbers of the transmit and receive antennas to be arbitrary. By introducing an exact determinant expansion and by finding the explicit expressions for the expected values of the determinant and log-determinant of the complex non-central Wishart-distributed matrix, we obtain a simple but very tight upper and lower bounds for the average channel capacity. Both bounds are simple, in closed form, easy to be used, and superior in tightness as evidenced by intensive numerical examples.

Modelling ultrawideband (UWB) received signals is an indispensable step to the UWB receiver design and UWB data regeneration. A popular framework for UWB modelling stems from the discrete multipath channel model whose path gains and time delays are random variables and thus, must be specified by their probability density function (pdf)- Besides, various partial characterization is used in the literature by virtue of second-order statistics (such as power delay profile), nonparametric characteristics (such as zero-crossing rate), or their combination. So far, little UWB models have the capability to account the correlation structure existing among received UWB data and little work directly addresses the original UWB data. In this paper, we take a different philosophy which believes that the information in the received UWB data itself, as long as fully exploited, plus some simple physical intuition should suffice for the model identification and its parameter estimation. The model so obtained is directly for the original data while having the capability to account for the correlation structure and nonstationarity of UWB data. The application of the new model to data regeneration is illustrated by using the real UWB data provided by the TimeDomain Corporation.

Nearly all multirate detection schemes proposed for IS-95 and CDMA2000 rely heavily on the assumption of an additive white Gaussian noise (AWGN) channel model. The idea is to exploit the property of symbol repetition and to test, in one way or another, the equality of the mean value of the received samples within an appropriate data block. In a fast fading environment as encountered in cellular mobile systems, however, the time-varying channel gain destroys the block-wise constant-mean structure in the received process lending the use of an AWGN channel model no longer justified. It is the correlation structure, rather than the mean value, of the received process that carries the information for multirate detection. To fully reflect this nature, we formulate the problem of multirate detection in a completely new framework ending up with a simple maximum-likelihood-based algorithm to examine the canonical correlation of the received sequence. The new test possesses the property of constant false-alarm rate thereby allowing for thresholds to be analytically determined. Computer results are also presented to demonstrate the superior performance of the new algorithm in Rayleigh fading.

The performance of differential amplitude and phase-shift keying (DAPSK) with post-detection diversity combining over general fading channels is of great theoretical interest and practical importance. Hence, a general and accurate performance analysis is very useful. In this paper, we analyze the distribution of the phase and amplitude decision variable at the DAPSK receiver output by using the moment generating function (MGF) approach. Exact results for the error probability of DAPSK on general Rician and Nakagami fading channels are derived, taking into account the effects of all system and fading channel parameters including correlated signal branches and correlated noise. By using our analytical results, the effects of the ring ratio and the amplitude decision boundary, etc., on the DAPSK performance are investigated, and some new findings are presented.

Novel decision-feedback (DF) linear prediction (LP) receivers, which process multiple samples per symbol interval in conjunction with optimal sample combining, are proposed for differential space-time modulation (DSTM) over Rayleigh fast-fading channels. Performance analysis demonstrates that multisampling DF-LP receivers outperform their symbol-rate sampling counterpart in fast fading substantially. In addition, an asymptotically tight upper bound on the pairwise error probability is derived. In view of this bound, the design criterion of DSTM for fast fading is the same as that for block-wise static fading. To avoid the estimation of the second-order statistics of the channel, a polynomial-model-based DF-LP receiver is proposed. It can approach the performance of the optimum DF-LP receiver at high signal-to noise ratios, provided fading is moderate.

A complete statistical characterization of correlated Nakagami channels is either their joint probability density function or their joint characteristic function (CHF), which is indispensable to many applications in wireless communications. The classical correlated multivariate Nakagami model in current use is subject to a restriction that the fading parameters must be identical. We derive a generic correlated Nakagami fading model, in the form of a multiple CHF, allowing for an arbitrary covariance matrix and distinct real fading parameters. The application of the new model to wireless communications is also presented.

The central issue to the error probability analysis of M-phase signaling is to determine the phase distribution of the received signal. In this paper, we take a novel approach by formulating the phase distribution in terms of joint moment generating functions (MGFs) of the real and imaginary parts of the decision variable at the receiver output. We further derive fast convergent formulas by using the two-dimensional (2-D) inverse Laplace transform enabling us to accurately evaluate the phase distribution. The new technique is very general, taking into account the effects of arbitrary diversity order, symbol alphabet size M, and arbitrary diversity branch correlation. Numerical results are also presented for illustration.

The error probability analysis of M-ary differential phase-shift keying signals with noncoherent diversity combining over general fading channels is not available in the literature except for some simple cases. The difficulty lies in the philosophy which attempts to explicitly determine the phase distribution expressions of the received signal, and this often leads to a mathematically intractable issue. In this paper, we take a novel approach by formulating the phase distribution in terms of joint moment generating functions of the real and imaginary parts of the decision variable at the receiver output. We further derive fast convergent techniques for two-dimensional (2-D) inverse Laplace transform enabling us to accurately evaluate the phase distribution. The error probability formulas thus obtained involve a twofold integral, which can be efficiently evaluated by using our algorithms developed on the basis of the 2-D trapezoidal summation and Gauss-Chebyshev quadrature. The new technique is very general, taking into account the effects of arbitrary diversity order, symbol alphabet size M, and arbitrary diversity branches correlation. Numerical results are also presented for illustration.

Driven by the potential application to wireless communications, intensive research efforts have been made on the study of various selective combining (SC) schemes in the past decade. Nevertheless, regardless of its practical importance, performance analysis of multi-branch SC over spatially correlated fading channels is not available in literature except for the simplest case of dual diversity. The major difficulty lies in the fact that SC has its root in the theory of order statistics, and yet systematic methodology has been developed mainly for order statistics obtained from an independent population. In this paper, we formulate the problem in a very general framework, whereby a general solution is derived. The application of the new solution to SC with different modulation schemes and operational environments is elaborated. The fading environments to be addressed include correlated Nakagami, Rayleigh, and Rician channels. Numerical examples are also presented to illustrate the use of the theory.

Noncoherent diversity reception of M-ary frequency-shift keying (MFSK) signals becomes increasingly important due to its widespread use in wireless communications. Its error performance analysis, however, is not available in the literature except for the simple case using binary modulation. We address the problem directly based on the decision variables, ending up with closed-form solutions to both conditional and average error probabilities for a general noncoherent MFSK diversity system operating on Rayleigh, Rician, and Nakagami fading channels. The solutions involve some higher order derivatives, and efficient recursive algorithms have been derived for their calculation. The solutions are very general permitting arbitrary diversity order, symbol size, channel parameters, and antenna-array covariance matrix. Numerical examples are also presented for illustration.

The use of power control to achieve the desired signal-to-interference ratio (SIR) is a crucial issue to ensure the quality of service of a code division multiple access (CDMA) cellular system. Power control based on SIR alone, however, often leads to the problem of vicious circle such that all mobile stations reach their power limits and yet, fail to achieve the desired SIR. In this paper, we present a novel power control scheme, which can significantly reduce the possibility of a vicious circle. The new scheme Is based on two observations. First, control of the target function SIR must take the signal power into account so as to avoid the problem of trivial optimization. Second, for a given channel operational environment, it is unnecessary and also impossible to pursue an unreasonably high SIR using brute force. The basic philosophy behind the new technique is therefore to define an acceptable SIR region over the entire SIR axis instead and use an adaptive technique for two purposes. Namely, adaptively adjust both the target SIR and the step size to approach it according to the changing channel characteristics. The new scheme is essentially a Markov system with adaptive control.

Correlated Nakagami m-fading is commonly encountered in wireless communications. Its generation in a laboratory environment is therefore of theoretical and practical importance. However, no generic technique for this purpose is available in the literature. Correlated Rayleigh fading is easy to simulate since it has a simple relationship with a complex Gaussian process. Unfortunately, this is not the case for Nakagami fading. The difficulty lies in that the fading parameter can be a real number and there is no general theory linking a Nakagami vector to a finite set of correlated Gaussian vectors. In this paper, by introducing a direct-sum decomposition principle and determining the statistical mapping between the correlated Nakagami process and a set of Gaussian vectors for its generation, a simple general procedure is derived for the generation of correlated Nakagami channels with arbitrary parameters. A key parameter in the statistical mapping can be determined by using an iterative method. The validity of the new technique is examined through the generation of a correlated Nakagami sequence, as encountered in U.S. digital cellular, and a multibranch vector channel as encountered in diversity reception.

Modeling variable-bit-rate (VBR) video source traffic is a crucial issue to evaluate the end-to-end performance of transmitting video signals over asynchronous transfer mode (ATM) networks. Difficulties in source modeling arise from the fact that VBR video source traffic usually follows a gamma distribution with high correlation among adjacent data. Many researchers adopt autoregressive (AR) models driven by a Gaussian error process to account for such correlation. The problem is: due to the closure property of the Gaussian distribution, the traffic so generated is Gaussian rather than gamma. As a remedy, some researchers directly consider gamma AR models instead. Unfortunately, the trouble arises from the fact that the closure property does not apply to gamma distributions, and thus, the linear operation performed by an AR model fails to produce gamma traffic. In this paper, we present a new technique that is capable of generating gamma-distributed traffic with arbitrary correlation while retaining the computational efficiency of Gaussian AR models. The central idea is to decompose given gamma traffic into a linear combination of a number of /spl lambda//sup 2/(1) sequences, and each of these latter processes can be easily obtained from a Gaussian AR process through a simple nonlinear operation. Results based on actual video teleconference data are presented to verify the validity of the new algorithm.

Current techniques used to tackle the outage problem in a lognormal shadowed (LNS) Rician environment follow the philosophy of using the chain rule in probability. The crucial issue is to determine the probability density function (pdf) of the total power of the co-channel interferers (CCI), ending up with a mathematically intractable integral of multiple fold. Results available in the literature, all based on certain explicit or hidden assumptions, apply only to some special cases. The purpose of this paper is to present an exact solution to outage performance for cellular or microcellular systems operating in an arbitrary lognormal shadowed Rician environment without any restrictions. We formulate the outage event as an inequality in terms of a decision variable and directly determine the outage probability from the characteristic function of the decision variable. The integrand so obtained is in a simple factored form, so that all integrals can be determined individually. As a result, the expression for the outage probability takes the form of a two-fold integral, which can accurately be evaluated by using Hermite and Gaussian quadrature.

Postdetection combining is a popular means to improve the bit error performance of DPSK and noncoherent FSK (NFSK) systems over fading channels. Nevertheless, the error performance of such systems in an arbitrarily correlated Nakagami environment is not available in the literature. The difficulty arises from inherent nonlinearity in noncoherent detection and from attempts to determine explicitly the probability density function of the total signal-to-noise ratio at the combiner output. We directly determine the error probability from the characteristic function of decision variables, resulting in closed-form solutions involving matrix differentiation. The performance calculation is further simplified by developing a recursive technique. The theory is illustrated by analyzing two feasible antenna arrays used in base stations for diversity reception, ending up with some findings of interest to system design.

The probability of error of a general equal-gain combiner (EG) in closed form is not available in the literature. By formulating the problem in the framework of signal detection and evaluating the probability of error directly from the characteristic function (CF) of the signal at the combiner output, we obtain closed-form solutions for the probability of error of the EG combiner with two or three branches operating over a Rayleigh-fading channel.

Most code-division multiple-access (CDMA) systems described in the literature provide only one single service (voice or data) and employ the strategy of "one-code-for-one-terminal" for code-assignment. This assignment, though simple, fails to efficiently exploit the limited code resource encountered in practical situations. We present a new protocol called reservation-code multiple-access (RCMA), which allows all terminals to share a group of spreading codes on a contention basis and facilitates introducing voice/data integrated services into spread-spectrum systems. The RCMA protocol can be applied to short-range radio networks, and microcell mobile communications, and can be easily extended to wide area networks if the code-reuse technique is employed. In RCMA, a voice terminal can reserve a spreading code to transmit a multipacket talkspurt while a data terminal has to contend for a code for each packet transmission. The voice terminal will drop a long delayed packet while the data terminal just keeps it in the buffer. Therefore, two performance measures used to assess the proposed protocol are the voice packet dropping probability and the data packet average delay. Theoretical performance is derived by means of equilibrium point analysis (EPA) and is examined by extensive computer simulation.

A generalized normalization technique is presented for detecting random signals in a nonstationary, two-dimensional noise field. By comparing the covariance structure of the data under test with that of reference data, the test exploits information in both amplitude and phase of the data. As a result, the proposed scheme considerably outperforms the conventional normalization technique which is based only on the amplitude information. Theoretical performance has been established and its correctness has been confirmed through computer simulations.>

Two new information theoretic criteria for detecting the number of signals in spatially correlated noise with unknown covariance matrix are presented. The new criteria take a very simple form involving the canonical correlation coefficients of sensor data, and are applicable to the cases either two sensor arrays or a single array are available. In both cases, the new schemes are significantly superior to the conventional information criteria.>

By comparing the second-order statistics of the resolution cells under test with those obtained from their neighboring range cells, a detection scheme for detecting a target in a locally stationary two-dimensional random noise field is derived. The assumptions made are: (1) the noise field is uncorrelated in range but correlated in azimuth; (2) the correlation of the data in azimuth can be modeled by a Gaussian autoregressive process of relatively low order. The detection scheme exploits the full information of the second-order statistics in the data to make a detection decision. Its performance is superior to those schemes based on the amplitude or on Doppler shift information only. The proposed scheme is a constant false-alarm rate processor; its threshold can be evaluated by using a central chi-square probability distribution factor and its detection probability can be predicted by a non-central one.>

The asymptotic distributions of the sample estimates of the partial correlation coefficients (PCORs) of a complex Gaussian AR (autoregressive) process are derived. Unlike the PDF (probability density function) of the sample model coefficients, which is asymptotically complex Gaussian distributed and has a form similar to that for a real AR process, the PDF of sample PCORs cannot be simply expressed in a complex Gaussian form. Rather, the real and imaginary parts of sample PCORs have a jointly real Gaussian distribution, whose covariance matrix can be evaluated through a recursive algorithm. Computer simulations have been performed confirming the correctness of the theory. Although the PDFs are derived on the basis of a large-sample theory, computer results show that they work quite well even for small samples; this is important to some applications such as radar.>

A problem central to most high-resolution methods of array processing is the determination of the number of signals K from a finite set of observations. Two common criteria which do not make use of a subjective threshold are the AIC (Akaida information criterion) and MDL (minimum distance length), both of which consist of a likelihood-function term and a penalty term. The idea is to find a number of K such that either of the criteria is minimized. Examination of both criteria reveals that the likelihood function encompasses irrelevant parameters resulting in the relatively inaccurate estimation of the relevant parameters. A criterion is proposed such that a new likelihood function is derived, consisting of only the parameters having some bearing on the determination of K. The improvement of the accuracy in the estimation of the relevant parameters is evaluated. Computer simulations indicate that considerable improvement in performance is attained.>

Presents a new approach to a near optimum MTI filter design using adaptive techniques. The resulting scheme consists of an adaptive whitening filter for radar clutter followed by a likelihood ratio test (LRT) for target signal in white noise. A complete procedure is developed for the whitening filter design. The LRT may operate either with or without a clutter power map. The detection performance of the new scheme is evaluated using real radar data. When operating with a clutter map, it provides 7.5 dB average performance improvement over the innovations-based detection algorithm (IBDA) for ground clutter-dominated data and 5 dB improvement for weather clutter. And the latter has been demonstrated to be superior to the classical moving-target-detection (MTD) by 3 to 5 dB.>

The problem considered in this work is the detection of a random signal in colored noise. A modelling approach was used to construct two hypotheses: that the received data consisted of noise alone (hypothesis H 0 ) and that they consisted of signal plus noise (hypothesis H 1 ). The models used were linear auto-regressive models. A log likelihood ratio was constructed, based on these hypothesis. The probability density of this ratio was approximated by a χ2- distribution, from where the threshold levels for the detector under a given probability of detection could be estimated. Computer simulations showed that the χ2-approximation provided a good basis for threshold estimation. A good detection performance was also verified.