We consider a simple ad-hoc cognitive scenario with two data up-links, one licensed to use the spectral resource (primary) and the other unlicensed (secondary or cognitive). It is assumed that the cognitive link accesses the channel only when the channel is sensed idle. An ON-OFF channel model is used for the primary link, where traffic statistical characteristics are taken into account. A closed-form expression for the signal-to noise-plus interference (SINR) statistics of the cognitive nodes is derived that can be used for estimating the network performance. Moreover, a M/G/1 queueing model is exploited for deriving a simple expression for the average packet delay. Finally, a MAC strategy based on a channel-and-queue aware scheduling is introduced.

Cognitive radios have been proposed as a means to implement efficient reuse of the licensed spectrum. Commonly, wireless networks are characterized by a fixed spectrum assignment policy. The limited available spectrum and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. We consider a simple single-cell scenario with two data up-links, one licensed to use the spectral resource (primary) and the other unlicensed (secondary or cognitive). It is assumed that the cognitive user accesses the channel only when the channel is sensed idle. An ON-OFF channel model is used for the primary link, where traffic statistical characteristics are taken into account. We study a practical resource allocation algorithm that assigns the uplink to the secondary users according to a channel-and-queues aware scheduler when primary link OFF periods are sensed. We fit the resource allocation algorithm to the widely investigated orthogonal frequency division multiple access (OFDMA) scheme and we exploit multiuser diversity by applying a smart power allocation within independent OFDMA subchannels. A video encoder rate control is introduced in order to limit the video frame loss due to overflow that trades the video frame loss probability with the overall encoding quality. Lastly, the performance of the cognitive network model is investigated under the proposed resource allocation algorithm.

In wireless cellular systems, capacity can be increased if both in-cell and out-of-cell cochannel interference (CCI) is properly handled. Moreover, spatial multiplexing has been proved to be much effective in multiuser MIMO systems. The authors propose a cross-layer approach to opportunistic interference management and spatial multiplexing, by using a random beamforming strategy and a smart scheduler assuming a certain degree of cooperation between transmitters. In this paper, we recall the resource allocation algorithm, we derive the PDF and CDF of the SINR of a simplified cooperative multiuser MIMO system and we discuss some numerical results. In particular, we examine the tradeoff between spatial diversity and multiplexing as a function of the out-of-cell CCI level. Numerical results show that, for high out-of-cell interference, a larger throughput is achieved if at most one user is scheduled at a time in each cell. Otherwise, spatial multiplexing must be used to improve the system overall throughput. The CCI threshold value strongly depends on the receivers complexity (e.g., MISO or MIMO).

The mutual interference among co-channel users greatly limits the performance of cellular wireless systems. In particular, if a tight frequency reuse is employed, intercell interference must be properly handled. In this paper, we propose a cross-layer approach to the interference management, by using a random beamforming strategy and a smart scheduler with joint processing of signals related to different users in the network. Random beamforming is performed at each base station of the system, partial CSI is collected and shared by the network of interfering transmitters, and a scheduler chooses a subset of the users to be transmitted to. Optimization of beamforming in broadcast MIMO channels is precluded by the amount of feedback and complexity required. In this paper we propose to reduce the feedback by employing a random beamforming where a stream can be linearly preceded before being transmitted on the antenna array of each transmitter and the users with channel/interference matched to the beamforming configurations are scheduled at each time. In MIMO system the users can further improve the overall throughput by minimizing the co-channel interference. The feedback necessary to employ the spatial multiplexing can be limited to the signal to interference ratios for a subset of users that are compatible for the random beamforming configuration. In practice, a form of adaptive frequency reuse is performed on the basis of the spatial signal-to-interference ratio distribution among the users. We provide numerical results to compare the performance of our scheme with a form of dynamic channel allocation and opportunistic beamforming

It is well known that in high density magnetic recording channels noise models should comprise the contributions due to the non-ideal transitions. A simplified model of 'transition noise' includes the first order Taylor's expansion of the function that represents the ideal response in order to include the effects of transition (position) and width jitters. In this work we present an analysis that provides an evaluation of the probability density function of the noise projection over a generic error event. This procedure is used to evaluate the probability density functions of the reliability measures obtainable by a soft detection as max-log-MAP (maximum a posteriori) or SOVA (soft output Viterbi algorithm) applied to a magnetic channel.

In signal equalization, a technique that allows reduction of the number of states of the Viterbi detector is the delayed decision feedback sequence detector (DDFSD). In order to achieve good performance, it is essential to operate, before the DDFSD, an appropriate prefiltering of the received sequence. This paper is devoted to performance evaluation of the DDFSD when the feedforward filter of a minimum mean square error decision feedback equalizer is adopted as a prefilter. A truncated version of the union bound is used to approximate the bit error rate. The analysis includes a method for determining the error events that dominate the bound.

In signal equalization, a detection technique that allows reduction of the number of states of the Viterbi (1979) detector is the delayed decision feedback sequence detector (DDFSD). In order to achieve good performance, it is crucial to operate an appropriate prefiltering of the received sequence before the DDFSD. The main novelty of the paper is performance evaluation of the DDFSD when the feedforward filter of the minimum mean-square error decision feedback equalizer (DFE) is adopted as prefilter. The union upper bound is used to evaluate the probability of first error event and truncation of the sum appearing in the bound to the error sequences that dominate the performance is discussed. It is also shown that the feedforward filter of the minimum mean-square error DFE leads to maximum likelihood sequence detection with a minimum number of states, which seems to be a novel result.

In signal equalization, a technique that allows reduction of the number of states of the Viterbi (1979) detector is the delayed decision feedback sequence detector (DDFSD). In order to achieve good performance, it is crucial to operate an appropriate prefiltering of the received sequence before the DDFSD. This paper is devoted to performance evaluation of the DDFSD when the prefilter of a minimum mean square error decision feedback equalizer is adopted. The union upper bound is used to evaluate the probability of first-event error, and truncation of the sum to the error sequences that dominate the performance is discussed.

SISO (soft input soft output) algorithms are present in several decoding schemes, particularly in concatenated ones that admit an efficient iterative detection, e.g. turbo codes. These algorithms have been an interesting research subject, especially for the aspects related to complexity reduction. This paper presents the idea of partitioning the set of original states in a channel or a code, generating a scaled (or reduced) trellis. Merging two or more states produces a new super-state and a standard SISO algorithm can follow the system evolution in terms of the new description.

In signal equalization, a suboptimal technique for reducing the number of states of the Viterbi detector is the delayed decision feedback sequence detector (DDFSD). In order to achieve good performance a mean-square (MS) prefilter is employed before the DDFSD. This paper is devoted to investigate the sensitivity of the MS-DDFSD to a noisy estimate of the variance of the noise. Analytical performance evaluation is addressed. A truncated version of the union bound is used to approximate the bit error rate. The analysis includes a method for determining the terms that dominate the bound.

High-density magnetic recording systems require increasingly sophisticated signal processing techniques. In magnetic recording channels, the information bits are encoded by the concatenation of an outer nonbinary error correcting code (ECC) and an inner line code. Furthermore, the high intersymbol interference that characterizes the channel is controlled by "partial response" equalization. This paper presents a study on a better-integrated decoding procedure between the inner and outer codes. Inversion of the concatenated codes (reverse concatenation) allows the direct mapping of soft information from the partial response channel to the outer ECC. A simplified soft decoding technique, based on the use of erasures, is applied to two typical magnetic recording systems. Performance curves are obtained by an analysis of the distributions of the reliability measures associated with incorrect and correct symbols.

The paper deals with the design of suboptimal receivers for data transmission over frequency selective channels. The complexity of maximum likelihood sequence estimation (MLSE) turns out be exponential in the channel memory. Hence, when dealing with channels with long memory, suboptimal reception must be considered. Among the suboptimal methods, the delayed decision feedback sequence estimation (DDFSE) plays an important role. This receiver is based on a Viterbi processor where the channel memory is truncated. The memory truncation is compensated by a per-survivor decision feedback equalizer. The DDFSE was originally proposed by Duel-Hallen and Heegard (1989), where the whitened matched filter was considered as a front-end. Our contribution is to extend the principles of MLSE and DDFSE to the case where the mean-square whitened matched filter is adopted as a front-end. Simulation results show that our proposed design of the DDFSE gives substantial benefits when a severe frequency selective channel is considered.

The measurements of the impulse response of a 2.0 GHz indoor radio channel are reported. A statistical analysis of the characteristics of the amplitude of multipath components is presented. In particular, the spatial correlation of the single multipath components and the cross-correlation between the amplitudes of adjacent multipath components have been determined. Conclusions are drawn with regard to the adequacy of the wide sense uncorrelated scattering model as a consistent model for the indoor radio channel.

In burst digital transmission using PSK (phase shift keying) modulation with coherent detection, the recovery of the carrier reference phase and the symbol clock is a key aspect. If all users have a common clock synchronization, symbol timing needs not to be recovered in each burst. A digital processor for carrier recovery without preambles, in the presence of frequency offset, is considered. As an example, a 2 Mb/s QPSK transmission system is considered in which E/sub b//N/sub o/=10 dB, and the burst and estimation interval length L=15. Using the algorithm described and averaging eight successive estimated frequency offsets, in order to eliminate anomalous errors, the BER (bit error rate) degradation is equal to 0.14 dB when Delta f=20 kHz.>

In view of a digital implementation of most of the signal processing required in a QAM demodulation-equalization Structure, a performance analysis as a function of equalizer complexity, A/D conversion resolution, and precision of internal arithmetic is presented. The analysis is focused on a 140 Mbit/s 64-QAM modulation scheme (corresponding to CEPT-4 or3 \times DS3systems), but extension to other QAM constellations is straightforward. Considerations of currently available technology, overall computational complexity, and related optimal quantization formats are presented. For high-speed 64 QAM, it is shown that satisfactory performance may be expected from a full digital implementation of reasonable complexity, using current technology.

The aim of this work is to investigate frequency discriminator detection for continuous phase digital modulation (CPM) in order to avoid the RF carrier recovery problem. An efficient demodulation scheme, based on a discriminator followed by a suitable baseband digital processor of acceptable complexity, is presented. The baseband processoris based on decision feedback and correlation. In the binary case we also derive a simplified scheme with good performance.

Continuous-phase, constant-envelope digital modulation schemes are useful in various applications where a high spectrum utilization as well as immunity to nonlinear distortion is required. From this point of view, typical efficient schemes are digital partialresponse frequency modulation methods. The aim of this work is to investigate noncoherent detection in order to avoid the RF carrier recovery problem. In this paper we select for analysis tamed frequency modulation (TFM) as a particularly representative member of this class, but a similar analysis could be carried out for other partialresponse digital FM systems. After an evaluation of the optimal noncoherent detection and of differential phase detection of TFM, we propose a demodulation method based on a simple and efficient baseband processing of the output of a frequency demodulator. It turns out that the power loss with respect to coherent or optimal demodulation of TFM is on the order of 2 dB. The baseband processing here proposed is in some way equivalent to a partial recovery of the carrier phase and could be improved by using a more complex baseband processing such as a decoding scheme based on the Viterbi algorithm.

In this correspondence, the problem of lower bounds on mean-square error in parameter estimation is considered. Lower bounds on mean-square error can be used, for instance, to bound the performances, namely the attainable output signal-to-noise ratio, of pulse modulation transmission systems, such as pulse-position modulation (PPM) or pulse-frequency modulation (PFM). The tightest lower bounds to mean-square error previously known are the Ziv-Zakai bounds; the analysis carried out in this paper, which is based on an inequality first obtained by Kotel'nikov, leads to lower bounds tighter than previously known bounds.