Mutual Information based Partial Band Coexistence for Joint Radar and Communication System

We show that the concept of correlation detection of deterministic signals in additive Gaussian noise can be extended in a natural manner to the detection of signals that are transmitted through a "Gaussian" random channel besides being corrupted by additive Gaussian noise. Such situations are typical in communication over scatter-multipath channels (with or without a specular component). In the deterministic case, the receiver essentially crosscorrelates the received signal with the signal before the additive noise was introduced. When a random channel is present, however, this latter signal, i.e., the output of the random channel, is not known at the receiver, However, knowing the statistics of the channel and the noise, the receiver can make an estimate of it from the received signal on the hypothesis that a particular signal was transmitted. The optimum receiver then crosscorrelates this estimate with the received signal.

The use of information theory to design waveforms for the measurement of extended radar targets exhibiting resonance phenomena is investigated. The target impulse response is introduced to model target scattering behavior. Two radar waveform design problems with constraints on waveform energy and duration are then solved. In the first, a deterministic target impulse response is used to design waveform/receiver-filter pairs for the optimal detection of extended targets in additive noise. In the second, a random target impulse response is used to design waveforms that maximize the mutual information between a target ensemble and the received signal in additive Gaussian noise. The two solutions are contrasted to show the difference between the characteristics of waveforms for extended target detection and information extraction. The optimal target detection solution places as much energy as possible in the largest target scattering mode under the imposed constraints on waveform duration and energy. The optimal information extraction solution distributes the energy among the target scattering modes in order to maximize the mutual information between the target ensemble and the received radar waveform. >

One approach to the analysis of the high signal-to-noise ratio (SNR) capacity of noncoherent wireless communication systems is to ignore the noise component of the received signal in the computation of its differential entropy. In this paper, we consider the error incurred by this approximation when the transmitter and the receiver have one antenna each and when the noise has a Gaussian distribution. We consider the complex and real cases, and we show that when the probability density function (pdf) of the signal component of the received signal is piecewise differentiable, the approximation error decays as 1/SNR, which tightens the available result that the error decays as o(1). In addition, we consider the special instance in which the signal component of the received signal corresponds to a signal transmitted over a channel with a Gaussian fading coefficient. For that case, we provide explicit expressions for the first nonconstant term of the Taylor expansion of the differential entropy, and we invoke Schwartz's inequality to obtain an efficiently computable bound on it. Our results are supported by numerical examples.

The Wigner distribution (WD) is applied to the detection and localization in time, of narrow-band transient signals of unknown waveform in an additive background comprised of quasiharmonic and random components. A traditional method of processing such signals is the spectrogram or short-time power spectrum. Based on an important relationship between the spectrogram and the WD, the application of the WD to the problem is investigated. The smoothed-pseudo-WD is shown to provide superior time and frequency resolutions of the received signal. Based on monitoring the received power in localized regions of the WD spectrum, a detector that achieves good time localization of the transient waveform and is relatively insensitive to changes in signal duration and frequency is obtained. The signal-to-noise ratio of the proposed detection statistic is derived for a transient signal in additive Gaussian noise and its dependence on various signal and detector parameters discussed.

: The report proposes a design of an adaptive receiver for the detection and estimation of nearly periodic signals in additive Gaussian noise. A nearly periodic signal is defined to be a sample function of a Gaussian random process which can be divided into equal length intervals, called periods, in such a manner that the correlation between periods decreases exponentially with their separation. The receiver computes a low signal-to-noise ratio conditional likelihood ratio from which the observer must make decisions. The likelihood ratio is conditional because the receiver estimates any unknown parameters necessary for the computation of the true likelihood ratio. Thus the receiver can only compute a likelihood ratio conditioned upon these estimates being the true values of the unknown parameters. The receiver consists of pre- emphasis filters followed by a comb filter, energy detector, and weighted summation. A theoretical evaluation of the receiver, in terms of ROC curves, is made for the special case of nearly periodic signals with statistically independent equal-strength harmonics in white noise of known power.

In this paper, we put forward a computationally efficient algorithm to estimate the frequency and complex amplitude of a real sinusoidal signal in additive Gaussian noise. The novel method extends an iterative frequency estimator for single complex exponentials that is based on interpolation on Fourier coefficients to the real case by incorporating an iterative leakage subtraction strategy. Simulation results are presented to verify that the proposed algorithm can obtain more accurate estimation than both time and frequency domain parameter estimators in the literature, and the estimation variance of the method sits on the Cramer-Rao lower bound with only a few iterations required.

The linear prewhitening matched filter (PWMF) is the optimal decision function for discriminating exactly-specified signals in additive Gaussian noise. When the signals are less well specified the optimal decision function contains higher than linear terms in the data. Several examples of detection and discrimination tasks are presented for which only the linear term is required and other examples for which higher order terms are necessary. Even in the nonlinear case decision functions can often be approximated by linear operations on the data followed by logical operations. This combination of linear weights plus logic operations is typical of neural network models, which are thought to be elementary models of human processing mechanisms. A number of experiments suggest that there is no decrease in performance of humans for some complex tasks that ideally require such nonlinear operations. However, there are other such tasks where human performance is degraded and this appears to be due more to the complexity of the task and the nature of the correlations in the image than the order of the task. This suggests applications in diagnostic imaging where it might be advantageous for a machine viewer to substitute or work in conjunction with the human observer.

: Recent results on detection of random nonGaussian signals in additive Gaussian noise are discussed. A discrete-time approximation to a likelihood ratio detection algorithm is discussed, and preliminary results are presented for a computational evaluation of the performance for this approximation.

In this paper we introduce a successive interference cancellation (SIC) scheme for direct sequence optical code division multiple access (DS-OCDMA) systems using pulse position modulation (PPM). Considering double-padded modified prime code (DPMPC) as a signature sequence code, results show that the system has better performance in terms of both capacity and bit error rate (BER) as compared to the one without cancellation scheme, where the system with SIC scheme can support up to 88 users while the system without SIC scheme can support only 38 users at similar BER=10

We present a successive interference cancellation (SIC) scheme for a multicarrier (MC) DS CDMA system. In every subband, the SIC receiver successively detects the interferers' signals and substracts them from the user-of-interest. A comparison is made among SIC, matched filter detection with an equal gain combiner (MF-EGC), matched filter followed by maximal-ratio combining (MF-MRC) and minimum mean-squared error (MMSE) receivers with optimal tap coefficients. For this latter receiver, we determine the performance both when the number of taps equals the processing gain, denoted by N, and when the number of taps is roughly one-half of the processing gain. By analysis and simulation, it is shown that the SIC has better ability to suppress multiple-access interference (MAI) than do MF and [N/2]-tap MMSE in single carrier (SC) CDMA, and MF-EGC, MF-MRC and [N/2]-tap MMSE in MC CDMA, and this translates to increased capacity and better fading resistance. Further, SIC and N-tap MMSE yield approximately the same performance in SC CDMA, but SIC has a poorer performance than does an N-tap MMSE in MC CDMA. In addition, we derive results for the performance degradation that a SIC scheme experiences in MC CDMA due to both phase and timing tracking errors. It is shown that with small tracking errors, SIC can still retain a performance advantage over MF-EGC and MF-MRC, although the advantage of SIC decreases with increasing tracking errors.

We present a successive interference cancellation (SIC) scheme for a multicarrier (MC) direct-sequence code-division multiple-access (CDMA) system, using band-limited spreading waveforms to prevent self-interference. In every subband, the SIC receiver successively detects the interferers' signals and substracts them from the user-of-interest. A comparison is made among SIC, a minimum mean-squared error (MMSE) receiver, and matched filter (MF) detection with maximal-ratio combining (MRC). We also consider suboptimal combining using pilot symbol-assisted modulation (PSAM) to make the system more realistic. Analytic bit-error probabilities for SIC, MMSE, and MF in correlated Rayleigh fading channels are derived. The theoretical results for SIC, MMSE, and MF are shown to agree well with simulations. In particular, SIC and MMSE are shown to achieve better performance than MF with MRC; when the number of users is small, SIC provides better performance than does MMSE. Further, the correlation among different subcarriers is studied, and only large subcarrier correlation coefficients result in an obvious worsening of performance. Finally, we derive results for the performance degradation that an SIC scheme experiences in MC CDMA due to phase and timing tracking errors. It is shown that SIC can still retain a performance advantage over MF-MRC, although the advantage of SIC decreases with increasing tracking errors, especially when subcarrier correlation coefficients are small.

We present a lattice reduction (LR) aided successive interference cancellation (SIC) scheme combined with linear pre-equalization in the correlated multi-user MIMO system. The LR-aided SIC schemes have been extensively studied to detect multiple users' symbols due to the nearly optimal performance. However, the LR algorithm and the sequential detecting method inherently incur considerable computational complexity overhead although it is of a polynomial order. To reduce their computational complexities, we decouple the entire system into multiple lower dimensional subsystems using linear pre-equalization based on the correlation among the users. We then utilize the LR-aided SIC parallel in each subsystem. Furthermore, to combine the LR-aided SIC with pre-equalization optimally, we modify the LR-aided SIC scheme, handling the residual interferences after pre-equalization.

In this paper, we propose a set of joint transmit diversity selection (TDS) and relay selection (RS) algorithms based on discrete iterative stochastic optimization for the uplink of cooperative multiple-input-multiple-output (MIMO) systems. Decode-and-forward (DF) and amplify-and-forward (AF) multirelay systems with linear minimum mean square error (MSE), successive interference cancelation, and adaptive reception are considered. The problems of TDS and RS are expressed as MSE and mutual information (MI) joint discrete optimization problems and solved using iterative discrete stochastic algorithms. Such an approach circumvents the need for exhaustive searching and results in a range of procedures with low complexity and increased speed of convergence that can track the optimal selection over an estimated channel. The proposed schemes are analyzed in terms of their complexity, convergence, and diversity benefits and are shown to be both stable and computationally efficient. Their performance is then evaluated via MSE, MI, and bit error rate comparisons and shown to outperform conventional cooperative transmission and, in the majority of scenarios, match that of the optimal exhaustive solution.

In the conventional Vertical Bell Laboratory Layered Space-Time (V-BLAST) receiver with successive interference cancellation (SIC) decoding, the diversity order for the first detected symbol is the lowest, hence its error probability dominates the overall average error probability. In this thesis, a new SIC scheme was presented, called iterative post SIC (IP-SIC) that can increase the diversity order to a fixed desired value for all symbols, thereby significantly reduce the overall average error probability. The key to the technique is that after the interference from all substreams is subtracted from the received vector (the resulting vector will be referred to as the modified received vector), the detected symbol times its channel vector is added to the modified received vector one at a time and the symbol is detected again. Important features of the proposed approach are the increase in diversity order for those symbols detected earlier and the flexibility of balancing the increase in diversity order and the suppression of remaining interference. The latter feature can be used to further reduce the average error probability. The proposed technique is applied to the V-BLAST and space-time block coded V-BLAST system and its performance and computational complexity are analyzed.

This paper considers a successive light interference cancellation and allocation algorithm (SLICA) practicing interference cancellation for an indoor visible light communication (VLC) system based on successive interference cancellation (SIC) technique. The interference among users is cancelled with the help of the proposed approach to reduce computational complexity. VLC has become the cornerstone of intelligence in the current scenario. The data services allocated to the users are demand based and rely on their channel conditions. The data is allocated to user by modulating light waves via illuminated LEDs. The receiving end has photodiode installed in it to recover back the data. Better performance rate is achieved with lesser interference with the proposed approach. To guarantee good (quality-of service) QoS, considerable simulations are carried out considering real- time scenario which further demonstrates the high level performance of the proposed approach over conventional approach. Based on the analysis, the SINR and interference level is demonstrated for the conventional and the proposed approach and there is a hike in the performance rate of SINR and interference level of about 20 – 30 % with the applied proposed approach. The prior motto of this study is to enhance the system throughput and improve per user average performance rate and reducing the complexity of the system. This contributes to the total efficiency of the optical indoor VLC network. Our proposed algorithm will provide a strong backbone for the 6G deployment.