Automatic Modulation Classification is a key technology in Cognitive Radio Networks. Blind identification of the modulation scheme of an unknown detected signal has various commercial and military applications. Performance of Automatic Modulation Classifiers degrades severely under low Signal-to-Noise ratios and fading channel scenarios. Cooperative classification is presented as a means to enhance the classification performance as well as to relax the computational constraints on individual nodes. In this work, the performance of cooperative cumulants-based modulation classification is studied under flat Rayleigh fading channels. The degradation in performance of a single node under flat Rayleigh fading is first presented in comparison to Additive White Gaussian Noise channels. Next, performance improvement obtained through cooperative combining of classification data from several nodes is presented. Analytical results as well as simulations show that cooperation will improve the overall performance of modulation classifiers, overcoming the performance loss due to fading and reaching classification results comparable to the AWGN scenario.

Automatic Modulation Classification (AMC) is an important component in Cognitive Radio (CR) Networks. Multiuser AMC classifies the modulation schemes of simultaneous multiple unknown transmitters. In addition, cooperation among multiple CR receivers for modulation classification offers significant improvements in classification performance and overcomes the detrimental channel effects that degrades the single CR classifier performance. In this paper, a novel centralized soft-combining data fusion algorithm based on the joint probability distribution of fourth order cumulants is presented for cooperative modulation classification. Fourth order cumulants of the received signals are calculated as discriminating features for different modulation schemes at each CR node and sent to a centralized data Fusion Center (FC). The FC chooses the modulation scheme that maximizes the joint probability of the estimated cumulants. As compared to independent receiver classification, cooperative classification results are significantly improved under the same multi-path environment.

In this paper we consider spectrum sharing between a communication system, modeled as MIMO interference channel (MIMO IFC), and MIMO radar. We first derive a zero-forcing precoder to eliminate the interference at the communication receivers. We show that this precoder is equivalent to orthogonal projection matrix onto the null space of an effective interference channel and show that this choice of precoder will degrade the radar target direction estimation performance. We show that the radar performance can be improved at the cost of non-zero interference at communication users by projecting the radar signal onto a subspace which is an expanded version of the aforementioned null space. We propose two approaches to smoothly expand the projected subspace and study the tradeoff between radar performance and interference at the communication users through simulation.

This paper shows how cognitive radio (CR) can help to optimize system power consumption of multiple input multiple output (MIMO) communication systems. Leveraging results from information theory and capabilities of a CR (e.g., the awareness of the component capabilities and characteristics), a theoretical framework is developed to minimize the system power consumption of MIMO systems while still considering radiated power. This paper mathematically formulates the system power consumption minimization problem under a sum rate constraint for MIMO systems. The impact of channel correlation and partial channel state information at the transmitter is considered. Numerical algorithms are developed to solve the constrained optimization problem. The simulation results show that significant power savings (e.g., up to 75% for a 4 x 4 MIMO system with Class A power amplifiers) can be achieved compared to conventional power allocation schemes. The results also show that the more computationally efficient suboptimal heuristic algorithms can achieve power savings comparable to the exhaustive search algorithm.

In this paper, we show how cognitive radio can help minimize energy consumption of a wireless mobile communication device. We propose an energy optimization framework using cognitive radio for a given quality of service requirement based on the channel and the radio capabilities. The cognitive radio not only adjusts modulation, coding, and radiated power, as with conventional adaptive modulation, but also adjusts component characteristics (e.g., power amplifier characteristics) so that the radio operates with the highest energy efficient possible way. Simulation results show that significant energy savings (up to 75%) can be achieved compared to conventional adaptive modulation. This framework also can be applied to optimize radio operations to achieve additional goals.

Abstract This work describes the Site‐Specific System Simulator for Wireless System Design (S4W), a problem‐solving environment (PSE) that integrates visualization and computational tools with a high‐level graphical user interface. S4W improves the ability of wireless system engineers to design an indoor wireless system by encouraging them to think in terms of designing the system for optimal performance. Issues of computation management, data management, and location of resources are hidden from the user. The complex nature of data sets in the domain of wireless simulations calls for a customized set of visualization tools. Therefore, a number ofad hocvisualizations were developed for S4W. A study comparing the integrated system with an earlier, unintegrated version is presented. This helps to demonstrate the productivity gains that a PSE provides. Copyright © 2007 John Wiley & Sons, Ltd.

In this letter, the blind acquisition performance of PSP is discussed. Based on the theory of indistinguishable sequences (K.M. Chugg, 1998), modifications to conventional PSP are suggested that improve acquisition performance significantly. The effects of tree search and list-based algorithms on PSP are also discussed. In blind channel estimation, the performance of list-based algorithms is better than trellis-based algorithms and can be further enhanced using the proposed techniques. The blind acquisition techniques described here can be used for other applications like multi-user detection or space-time trellis codes

This letter presents two results for multiuser wireless systems employing dirty-paper coding strategies along with greedy scheduling over the broadcast multiple-input multiple-output channel. Specifically, an efficient and suboptimal downlink scheduler is proposed to approximate the maximum sum rate using equal power allocation, and it is shown to approach the maximum sum rate of optimal power allocation for a large number of users under optimal scheduling. The second result demonstrates that the average maximum sum rate can be tightly upper bounded when spatial multiplexing is maximized.

This paper presents an analytical framework for evaluating the performance of a threshold-based generalized selection combining (GSC) scheme in equally correlated Nakagami-m fading channels. The framework extends previously published results by allowing arbitrary fading index values (mges0.5) in the analytical solution. Also, we exploit a second method which is computationally more efficient than the first approach, when fading index m is a positive integer

The article presents an analytical framework for evaluating the performance of an equally correlated multi-branch predetection equal gain combining (EGC) diversity receiver in Nakagami-m fading channels. Specifically, the characteristic function (CHF) of the EGC output signal-to-noise ratio (SNR) with L correlated inputs is derived. Selected numerical examples are provided to illustrate the effects of branch correlation and fade distribution on the average error rate and outage probability of EGC receivers.

This article investigates the impact of antenna diversity implementation at both mobile handsets and basestations on the reverse link DS/CDMA capacity in a myriad of fading environments. Our numerical results reveal that transmit diversity implementation at mobile handsets is most beneficial in indoor propagation channels (since only a few significant resolvable multipaths are available) with low order antenna diversity at the base-station and in harsh fading environments.

This paper investigates peak-to-average power ratio (PAR) reduction with constrained transmit power for spatially precoded downlink transmission, based on orthogonal frequency-division multiplexing (OFDM). We generalize the concept of multiuser Tomlinson-Harashima (T-H) precoding and propose a nonlinear spatial precoder, termed a complex sphere precoder (CSP), which has the same throughput and error performance as the T-H precoder, but achieves both a low PAR and low average transmit power. Our study shows that a sequential CSP over individual tones achieves a significant PAR reduction while requiring a moderate transmit power increase. The suboptimal per-tone lattice search constitutes a good compromise between performance and complexity.

This paper considers packet transmission over a multiple-input-and-multiple-output (MIMO) Gaussian broadcast channel (GBC). Specifically, we compare and contrast two transmission strategies built on dirty paper coding (DPC) and the Bell labs layered space-time architecture (BLAST), respectively, under channel-aware scheduling, and demonstrate the advantage of a distributed MIMO architecture at a system performance level. For the DPC-based strategy, we also present an efficient suboptimal scheduling algorithm using equal transmit power allocation across users with a maximum order of spatial multiplexing which achieves near optimal scheduling performance for a sufficient number of users.

We consider the use of multiple antennas at the transmitter and/or the receiver to provide open-loop spatial diversity in a multiuser wireless data network. With channel quality information (CQI) available to the transmitter, and by always scheduling the transmission to the active user having the best channel conditions at the time of scheduling, another form of diversity, termed multiuser diversity, is obtained in a data system. This paper provides an analysis of the interaction between these two forms of diversity. From a network point of view, we prove that the asymptotic sum rate, in the limit of a large number of active homogeneous users and subject to the same average total transmit power, is inversely related to the number of transmit antennas for independent and identically distributed (i.i.d.) flat Rayleigh fading channels. In the case of i.i.d. flat Rician fading, the asymptotic sum rate also depends inversely on the number of transmit antennas, but directly on the number of receive antennas. Numerically, we show that the total diversity gain is also constrained by finite CQI quantization and channel fading statistics.

A global optimization technique is applied to solve the optimal transmitter placement problem for indoor wireless systems. An efficient pattern search algorithm - DIviding RECTangles (DIRECT) of Jones et al.- has been connected to a parallel three-dimensional radio propagation ray tracing modeler running on a 200-node Beowulf cluster of Linux workstations. Surrogate functions for a parallel wideband code-division multiple-access (WCDMA) simulator were used to estimate the system performance for the global optimization algorithm. Power coverage and bit-error rate are considered as two different criteria for optimizing locations of a specified number of transmitters across the feasible region of the design space. This paper briefly describes the underlying radio propagation and WCDMA simulations and focuses on the design issues of the optimization loop.

In this paper, we present model-based techniques for joint detection of two near equal power co-channel MSK signals. It is shown that an MSK signal is piecewise linear in the parameters of interest and therefore can be represented in the standard linear form. The problem of joint detection is then reduced to one of parameter estimation and this allows us to develop receiver architectures based on the minimum variance and minimum mean square error criterion. Simulation results have shown that model-based techniques provide a performance gain of about 12 dB for equal power signals and about 8-10 dB when the signals are near equal power (SIR/spl sim/1dB) over the conventional correlation receiver.

This paper presents comparisons between STTD (transmit diversity in WCDMA), downlink beamforming, and a system which combines both transmit diversity and beamforming.

Current bandwidth-efficient modulated signals are significantly distorted during nonlinear amplification. Memoryless digital predistortion is a cost-effective method to compensate for such distortion caused by a nonlinear amplifier. However, significant frequency-dependent effects in high power, wideband nonlinear amplifiers operating on signals such as multicarrier WCDMA reduce the effectiveness of memoryless predistortion and thus cancellation of memory effects is necessary. In this paper, we have presented a nonlinear tapped delay line (NTDL) predistorter structure with memory compensation as well as indirect learning capability, and demonstrated its performance for a 2-carrier WCDMA signal.

This paper considers the application of minimum mean squared error linear space-time processing in tandem with successive interference cancellation (MMSE-SIC) to the extraction of symbol-asynchronous /spl pi//4-DQPSK signals with RRCOS pulse shaping (35%-75% rolloff) in overloaded environments. The performance is analyzed through simulation in terms of the symbol error rate ranked by cancellation order. The effect of signal excess-bandwidth, adjacent channel interference, the number of users, SNR, and array type are considered. The channel statistics of all users are assumed known.

An antenna array is overloaded when the number of cochannel signals in its operating environment exceeds the number of elements. This paper proposes an iterative joint detection technique, spatially reduced search joint detection (SRSJD), that well approximates the joint maximum likelihood (JML) receiver, while reducing its computational complexity by several orders of magnitude. This complexity reduction is achieved by first exploiting the spatial separation between interfering signals with a linear preprocessing stage, and second, performing iterative joint detection with a reduced-state trellis formed over space instead of time. These novel joint detection trellises are possibly tail-biting and vary in structure from stage to stage. Through simulation, SRSJD is shown to demodulate over 2M synchronous quaternary phase-shift keying signals of zero excess bandwidth with an M element circular array. The channels of all users are assumed known.

Existing adaptive filtering techniques usually attempt to minimize the mean square error (MSE) of some aspect of a received signal, with respect to the desired aspect of that signal. However, adaptive minimization of MSE does not always guarantee minimization of bit error rate (BER). Instead, the probability density function of the received signal can be estimated and used to adaptively determine a solution that minimizes BER. To this end, a new adaptive procedure called the minimum BER estimation (MBE) algorithm has been developed. The MBE is shown to provide, in some cases, a lower BER signal output than traditional MSE-based methods of adaptive filtering.

The convergence behavior of the least squares constant modulus (CM) algorithm in an adaptive beamforming application is examined. It is assumed that the desired signal and the interference are uncorrelated. The improvement in output signal-to-interference ratio (SIR) with each iteration of the algorithm is predicted for several different signal environments. Deterministic results are presented for an environment containing two complete sinusoids. Probabilistic results are presented for a CM desired signal with a CM interferer and with a Gaussian interferer. The asymptotic improvement in output SIR as the output SIR becomes high is also derived. The results of Monte Carlo simulations using sinusoidal, frequency modulation, and quadrature phase-shift keying signals are included to support the derivations.

The performance of a Reed-Solomon coded binary communication system on a bursty-noise channel is considered. Bursty noise is defined to be background Gaussian noise plus burst noise, where burst noise is defined to be a series of finite-duration Gaussian-noise pulses with fixed duration and Poisson occurrence times. Using the noise model, along with ideal symbol interleaving, decoded bit-error probability bounds are derived for the case where the noise bursts are long with respect to the channel symbol rate. Specific performance results are presented for the (31,15,8) Reed-Solomon Joint Tactical Distribution System (JTIDS) code with a binary phase shift keyed (BPSK) modulation scheme. Simulation results are presented and they compare well with the theoretical results.>

When simulating multicarrier digital communication systems operating over nonlinear channels, the required high sampling rate contributes significantly to long execution times. A new method that reduces the sampling rate of simulations of such systems is developed. The partial rate of products (ParSOP) method reduces the sampling rate by generating only the intermodulation products that lie in a frequency band of interest. The ParSOP method requires that the bandpass nonlinearity be represented by memoryless operations on the complex envelope of the signal and that the subcarriers constituting the frequency-division multiplexed signal are sufficiently separated to prevent significant adjacent channel interference. Simulation results for such systems show that an order of magnitude reduction in the sampling rate is possible while producing only minimal error in the bit error rate estimate.>

Two examples are provided of the use of microcomputer simulation for computer-aided design and analysis of communication systems: a fixed topology simulation program for digital data links written in Pascal; and a simulation of an analog link using Fortran. Such applications are reported to require a minimum of investment. The new 32-bit single-board computers and their potential impact on microcomputer simulation are discussed.>