In this paper, we propose a novel channel quality reporting approach for cellular communication systems. The proposed approach features a differential coding scheme in stationary propagation conditions and a detector of non-stationary propagation conditions, which further triggers a channel-quality predictor for the non-stationary environment based on a machine learning method. In particular, the machine learning engine learns about the specific large variations of the channel quality by collecting signaling information from mobile terminals in a given region. Our simulations in a controlled urban environment with vehicular users show that the proposed solution can effectively replace the 4-bit channel-quality reporting scheme of LTE and NR standards with a 2-bit one, providing correct channel-quality indication in non-stationary conditions with high probability.

A novel code based channel shortening (CCS) algorithm for faster-than-Nyquist (FTN) signaling is proposed, where special convolutional codes are used to absorb the channel memory. These convolutional codes have a special type of generator matrix that allows previous code symbols to be determined by the current code trellis state and thus been referred to as output-retainable convolutional codes (ORCCs). Different from conventional schemes, the CCS algorithm performs joint detection and decoding (JDD) based only on the code trellis by exploiting the ORCC structure. Therefore, it provides a new view for channel shortening techniques, i.e., absorbing the channel memory by using channel codes. Properties of ORCCs are discussed. Based on these properties, we derive the bit error rate (BER) bound for the CCS algorithm. According to the bound, a code search algorithm is proposed to facilitate the code design. Furthermore, two concatenated codes based on ORCCs are designed. Simulation results show that with a 16-states BCJR algorithm for JDD, the BER performance of the designed self-concatenated convolutional code incorporated with FTN signaling is only 0.75 dB away from the Shannon limit of the shaping pulse, and the required signal-to-noise ratio is below the BPSK limit of Nyquist signaling.

This paper presents a spectrum-edge detection algorithm for initial cell-search in Long-Term Evolution (LTE) wireless networks. The algorithm consists of three steps. First, we roughly identify possible edges in the spectrum. Then, we confirm these “candidate” edges by means of a threshold on the local average spectrum. Finally, the center frequency is precisely determined by searching a pair of edges located at a distance approximately equal to a possible bandwidth of the LTE transmission. Based on tests with field signals, the proposed algorithm is much faster than the conventional sequential cell-search algorithm, where the signal is demodulated for a candidate center frequency and minimum bandwidth: if demodulation is not successful a new candidate center frequency is tried.

The usage of the millimeter wave (MMW) band in the 5th generation (5G) networks relies on beamforming to compensate the strong path-loss suffered at higher frequencies. To exploit the beamforming implemented by multiple antenna devices, proper algorithms to estimate the channel need to be designed. In this work we propose a novel channel estimation method for MMW systems where both transmitter and receiver are equipped with fewer radio frequency chains than antennas and implement hybrid analog-digital beamforming. First, we define a training sequence which includes a set of analog and digital beamformers to probe the channel. Then, we develop an algorithm which estimates the channel parameters directly rather than the multiantenna channel matrix and it is based on the two dimensional (2D) discrete Fourier transform (DFT) of the received training samples. Numerical results show the effectiveness of the proposed channel estimation method even in low signal to noise ratio (SNR) conditions.

For a cellular system where mobile terminals transmit in the uplink to base stations (BSs) using single carrier-frequency division multiple access (SC-FDMA), we consider multicell processing among BSs. Received signals are first quantized on a per-subcarrier basis and then forwarded to the serving BS on a backhaul with limited rate. With the aim of maximizing the network throughput we a) design an efficient composite signal representation and b) propose a rate allocation algorithm for the backhaul. Using a closed-form expression of the achievable throughput in the presence of quantization noise, an iterative greedy algorithm for the backhaul rate allocation is developed, where at each iteration we select the signal to be exchanged as the one providing the maximum network throughput increase per backhaul bit. In order to determine how many quantization bits are used for each received signal, we consider either a static bit allocation with a fixed number of bits, or a dynamic bit allocation (which ensures a predetermined network percentage throughput loss with respect to the unquantized case). In an LTE scenario, it is seen that the proposed bit allocation methods flexibly adapt to channel and backhaul conditions and yield similar performance, hence the static approach is preferred due to its lower complexity.

In this paper we consider a downlink multi-cell scenario where a central processor is connected by a finite-throughput backhaul to base stations (BSs) employing beamforming and QAM constellations. Both the serving BS and auxiliary BSs transmit a signal that combines at the mobile terminal (MT) to provide a QAM symbol while achieving a diversity gain. In order to reduce backhaul occupation, auxiliary BSs receive from the central processor only a quantized version of the QAM symbols to be forwarded to MTs. We formalize the problem of maximizing the network spectral efficiency on air for all the MTs within an area illuminated by the cooperative BSs optimizing a) the QAM constellation size, b) the quantization rate dictated by the finite-throughput backhaul and c) the power allocated by each BS. Since the resulting optimization is a mixed integer programming problem, we investigate a suboptimal solution where the same power is allocated to each MT and obtain a simple iterative algorithm for the rate optimization. Numerical results show that for typical cellular scenarios the suboptimal approach yields a network spectral efficiency close to the theoretical limit of Slepian-Wolf encoding.

In orthogonal frequency division multiplexing (OFDM) communication systems mobility results in time-variations of the channel, which yield intercarrier interference (ICI), especially when large OFDM blocks are employed in order to achieve a high spectral efficiency. In this letter we focus on systems with very long OFDM blocks, where many of the existing ICI mitigation techniques can not be applied due to complexity constraints. To mitigate ICI we propose a pre-equalizer, operating on sub-blocks of the received OFDM block, whose aim is to force all sub-blocks to have almost the same equivalent channel. In other words, the pre-equalizer combats only time variations of the channel. Next, after OFDM demodulation, the classical equalizer compensates frequency selectivity of the target channel. Performance of the proposed scheme, together with a suitable channel estimate implemented on a per sub-block basis, is evaluated for a digital video broadcasting scenario, according to the DVB-T2 standard, where the OFDM block size may be 32k, and its possible extension to hand-held devices in a next-generation DVB-H.

In recent years single carrier modulation (SCM) has again become an interesting and complementary alternative to multicarrier modulations such as orthogonal frequency division multiplexing (OFDM). This has been largely due to the use of nonlinear equalizer structures implemented in part in the frequency domain by means of fast Fourier transforms, bringing the complexity close to that of OFDM. Here a nonlinear equalizer is formed with a linear filter to remove part of intersymbol interference, followed by a canceler of remaining interference by using previous detected data. Moreover, the capacity of SCM is similar to that of OFDM in highly dispersive channels only if a nonlinear equalizer is adopted at the receiver. Indeed, the study of efficient nonlinear frequency domain equalization techniques has further pushed the adoption of SCM in various standards. This tutorial paper aims at providing an overview of nonlinear equalization methods as a key ingredient in receivers of SCM for wideband transmission. We review both hybrid (with filters implemented both in time and frequency domain) and all-frequency-domain iterative structures. Application of nonlinear frequency domain equalizers to a multiple input multiple output scenario is also investigated, with a comparison of two architectures for interference reduction. We also present methods for channel estimation and alternatives for pilot insertion. The impact on SCM transmission of impairments such as phase noise, frequency offset and saturation due to high power amplifiers is also assessed. The comparison among the considered frequency domain equalization techniques is based both on complexity and performance, in terms of bit error rate or throughput.

The widespread proliferation of wireless sensor networks is revolutionizing our capabilities of monitoring and controlling the environment. The wireless connection of spatially distributed sensors, controllers and actuators poses challenges to the control system, due to packet drops, delays and measurements quantization, as well as to the wireless network resource allocator. These challenges push for a cross-layer design of communication and estimation/control systems. In this paper, assuming a TCP-like protocol between controller and actuator, we solve the problem of optimum control around a target state for a stable system in case of both packet drops and signal quantization. Generalization for unstable systems is also given in case of negligible quantization error. Moreover we propose a general framework for cross-layer optimization of signal quantization and network resource allocation. Here our main contributions are on i) quantizer design (how many bits to allocate for signal quantization), ii) network resource allocation (bit-rate for each radio link) and iii) choice of the transmission mode (constellation and channel coding rate). As application example, we consider a simple scalar, stable system and compare network resource allocation in the presence of i) low-cost sensors using a fix modulation and ii) long-term future sensors capable of rate adaptation. Interestingly, almost optimal control is achievable with small bandwidth transmissions and simple BPSK, supporting the use of low-cost sensors in applications dealing with state control around a target state trajectory.

The wireless connection of spatially separated sensors, controllers and actuators poses challenging problems to the control system, due to packet drops, delays and measurements quantization, as well as to the wireless network resource allocator. This pushes for a cross-layer design of communication and estimation/control systems. Assuming a TCP-like protocol between controller and actuator, we solve the problem of optimum control around a target state for a stable system in case of both packet drops and signal quantization. Generalization for unstable systems is also given for large bandwidth transmissions. Next, we derive the limiting behavior of the system in the infinite horizon and propose a general framework for cross-layer optimization of signal quantization and network resource allocation. As an example of application, we consider a simple scalar, stable system and compare network resource allocation in the presence of i) low-cost sensors using a fix modulation and ii) long-term future sensors capable of rate adaptation. Interestingly, almost optimal control is achievable by small bandwidth transmissions using a simple BPSK, supporting the use of low-cost sensors in applications dealing with state control in stable systems.

We consider a multiuser MIMO-OFDM downlink system with single antenna mobile terminals (MTs) where channel state information at the base station is provided through limited uplink feedback (FB). In order to reduce the FB rate and signal processing complexity, the available bandwidth is divided into resource blocks (RBs) whose number of subcarriers reflects the coherence bandwidth of the channel. This approach is very common in the standardization of 4th generation wireless communication systems and justifies an independent channel quantization per RB. Within this framework the paper contains two main contributions. Firstly we provide joint conditions on the channel coherence bandwidth and the FB rate per RB that allow for a simpler quantization of the RB channel matrix (space-frequency) by a space vector, causing negligible performance loss in terms of system achievable throughput. This is accomplished after deriving a new metric for codebook design in RB channel quantization that exploits spatial and frequency correlation. As a second contribution we investigate the trade-off between accurate channel knowledge and frequency/multiuser diversity. It is seen that even for a moderate number of MTs in the network, concentrating all the available FB bits in characterizing only one RB provides a significant gain in system throughput over a more classical distributed approach and this result is validated both analytically and by simulations.

We consider a multiuser MIMO-OFDM downlink system with single antenna mobile terminals (MTs) where channel state information at the base station is provided through limited uplink feedback (FB). In order to reduce the FB rate and signal processing complexity, the available bandwidth is divided into resource blocks (RBs) whose number of subcarriers reflects the coherence bandwidth of the channel. This approach is very common in the standardization of 4th generation wireless communication systems and justifies an independent channel quantization per RB. The paper has two main contributions: firstly we show conditions on the coherence bandwidth of the channel and the FB rate per RB that allow for a simpler characterization of the RB channel matrix by a space vector, causing negligible performance loss. This is accomplished after deriving a new performance metric for RB channel quantization that exploits spatial and frequency correlation. As a second contribution we investigate the trade-off between accurate channel knowledge and frequency/multiuser diversity. It is seen that even for a moderate number of MTs in the network, concentrating all the available FB bits in characterizing only one RB provides a significant gain in system throughput over a more classical distributed approach and this result is validated both analytically and by simulations.

In a cellular system with partial channel state information, i.e. with limited feedback, and multiple antennas, we consider scheduling of downlink transmissions at the base station using beamforming and orthogonal frequency division multiplexing. As the complexity of optimal scheduling for throughput maximization under quality of service constraints grows exponentially with the number of subcarriers, in this paper we propose two low complexity suboptimal techniques. The first is a greedy iterative strategy that at each step selects one user with the aim of maximizing the weighted sum rate (WSR), without the need of recomputing the beamformer. We next propose a pre-selection strategy that removes from the selection process users that do not provide an increase in the WSR, thus speeding the search. Both complexity and performance of the proposed techniques are evaluated and compared with existing solutions in a long-term evolution 3GPP scenario.

In this paper we derive two iterative joint precoding and power allocation methods for downlink MC-CDMA systems with multiple transmit antennas at the base station. The first method optimally solves the so called assigned target SINRs problem, i.e. determines the precoding coefficients and the minimum sum-power allocation under a constraint on the SINR of each user. The second method instead solves the maximum sum-rate problem, i.e. maximizes the system throughput under a constraint on the overall transmit power. The main result of this paper is that the proposed joint precoding and power control solutions provide an advantage with respect to suboptimal solutions for a fully loaded system, i.e. when the number of users is equal to the spreading factor times the number of transmit antennas. For lower loads, performance of the various schemes becomes closer.

We consider the uplink transmission of multimedia services in a cellular network where multiple access is implemented by code division multiple access (CDMA) and the base station performs successive interference cancellation (SIC) to enhance performance. We propose a cross-layer optimization technique that operates both at the physical layer, by selecting the detection order at the SIC receiver, and at the medium access control layer, by selecting the power/rate for each mobile terminal. The optimization objective is the maximization of the overall weighted network throughput with the satisfaction of the quality of service criteria for multimedia communications. The resulting problem turns out to be NP-complete and we resort to a discrete stochastic approximation (DSA) approach for its solution. Concerning DSA, an efficient implementation is proposed in order to reduce memory occupation and improve the convergence of the algorithm. In a UMTS cellular environment, numerical results show that the optimization provides a significant performance advantage over existing techniques at the cost of an increase of computational complexity and memory occupation.

For a cellular system based on frequency division duplexing where the base station (BS) is equipped with multiple antennas and the mobile terminals (MTs) have one antenna each, we propose joint techniques to a) feed back channel state information from MTs to the BS, b) design the beamformer and c) schedule downlink transmissions. We propose that both BS and MT predict channel variations, and the feedback (FB) information from MT to BS is given by the prediction error. For the beamformer design we both consider a zero forcing approach and investigate a new solution based on the minimum mean square error criterion, which takes into account the quantization error. By exploiting the FB information, we derive approximated expressions of the signal to noise ratio relative to each MT, used at BS to perform scheduling with an efficient greedy algorithm. Performance assessment on realistic 3GPP channel models show that the proposed techniques provide a significant improvement of the network throughput at a lower FB rate than existing solutions.

We propose an iterative method, based on the steepest descent algorithm (SDA), to evaluate the sum capacity in the uplink of a multi-spot system based on orthogonal frequency division multiplexing (OFDM) with centralized power allocation, at any given instant. Because the problem with user power constraints is non-convex, there is no guarantee that the proposed method converges to the optimal solution. However, simulation results show that its solutions by SDA outperform the distributed power control approach presented in S.T. Chung and J.M. Cioffi, (2003). Although, it can be hard to realize in a real time system, the method is an optimal tool to evaluate the maximum rate of a multi-spot system.

In this paper, as an alternative to post-detection techniques, we derive two iterative joint linear precoding and power allocation methods for downlink MC-CDMA systems with multiple transmit antennas at the base station. The first method optimally solves the so called assigned target SINRs problem, i.e. determines the precoding coefficients and the minimum sum-power allocation under a constraint on the SINR of each user. The second method instead solves the maximum sum-rate problem, i.e. maximizes the system throughput under a constraint on the overall transmit power. The main result of this paper is that the proposed joint precoding and power control solutions provide an advantage with respect to suboptimal solutions for a fully loaded system, i.e. when the number of users is equal to the spreading factor times the number of transmit antennas. For lower loads, performance of the various schemes becomes closer.

For a cooperative wireless network using delay diversity, the equivalent channel seen at the receiver is multipath and time-varying, as each transmitter has a local oscillator with a random frequency offset. The authors propose to use orthogonal frequency division multiplexing (OFDM) modulation, in order to efficiently implement equalization in the frequency domain; inter-carrier interference arising from multiple frequency offsets is instead compensated by a linear equalizer. For the estimate of the time-varying channel parameters a new technique was proposed that reduces the number of parameters to be estimated and exploits the multiple frequency-offsets.

For a multi-cell system using OFDM, this paper considers the multiuser power control problem in a frequency-selective interference channel. In particular, the aim of this work is to develop an iterative algorithm for user power control and bit loading on OFDM subcarriers, which minimizes the sum power under a constraint on the user bit rates. The performance of the proposed algorithm is compared against two previous algorithms in terms of sum power, probability of convergence within a fixed number of iterations, and mean number of iterations required for convergence.

In a broadband uplink code-division multiple-access transmission, the interference among users, depending on the correlation of specific channels and codes, may be significant. Hence, when successive interference cancellation (SIC) is performed at the base station, the minimization of power consumption at the mobile terminals is achieved if a joint optimization of power control and ordering (JOPCO) of user detection is carried out. In this paper, we first investigate a closed-form solution to JOPCO, based on the assumption of perfect interference cancellation and complete knowledge of channel correlation among users. By describing the JOPCO problem as an optimization on a suitable graph, it is seen that the optimum solution is NP-hard, and we approximate it by a greedy algorithm. For a practical implementation, we then model JOPCO as a discrete stochastic optimization problem, and we derive a discrete stochastic approximation (DSA) algorithm that iteratively adapts the transmit powers and the SIC detection order. The DSA solution removes the hypothesis on perfect cancellation and explicit knowledge of the users' correlation. Moreover, by a suitable description of the problem, we obtain a simplified DSA algorithm having reduced requirements in both computational complexity and memory. Performance of the various algorithms is assessed by simulations in a universal mobile telecommunications system scenario

Orthogonal frequency division multiple access (OFDMA) and multicarrier code division multiple access (MC-CDMA) are possible candidates for the next generation of mobile wireless systems. However, when applied to an uplink broadband communication, MC-CDMA suffers from multiuser access interference, which can be reduced by using successive interference cancellation (SIC) at the base station. With this regard, here we propose an optimization of the MC-CDMA receiver that jointly determines power control and user detection ordering based on a discrete stochastic approximation algorithm. For OFDMA, we consider instead interleaved transmission and optimization of transmission power for each user. A comparison of OFDMA and MC-CDMA with SIC is then given in a multiuser uplink scenario in terms of sum-power for a required signal to noise ratio at the detection point.

Successive interference cancellation (SIC) for code division multiple access (CDMA) systems, together with a suitable power control, is an attractive technique to reduce multiuser access interference in uplink transmissions. In this paper we propose a receiver design which minimizes the system transmit power while ensuring a constant signal to noise plus interference ratio (SNIR) at each user detection point by using a suitable order of user detection. Indeed, the problem is a joint optimization of power control and ordering of user detection and its optimum solution is NP-hard. Hence, we derive both a suboptimal greedy algorithm and a randomized search which explores many solutions. All these approaches are evaluated in an uplink multiuser scenario for the UMTS-TDD standard in terms of bit error rate and power consumption.

In this paper, a convolutionally-coded uplink multi-carrier code-division multiple-access (MC-CDMA) system with multiple transmit and receive antennas is considered, over multipath Rayleigh fading channels. In this framework, a new iterative hybrid scheme based on the combination of a successive interference cancellation (SIC) and a vertical-BLAST detector is presented, to cope, respectively, with multiple-access interference and multiple-substream interference. Based on simulation results, the performance of the uplink MC-CDMA system, decoded by hard or soft-input decoding methods, is found to improve significantly by the use of antenna arrays in conjunction with the proposed multi-user receiver

This letter focuses on maximization of achievable throughput for uplink orthogonal frequency-division multiplexing code-division multiple-access (OFDM-CDMA) systems. In particular, a new pre-equalization technique is presented where all users employ spreading both in frequency (on sub-bands of the available spectrum) and time; moreover, bit and power loading is used at the mobile terminals to accomplish throughput maximization. To avoid interference among users, the proposed loading algorithm inherently inverts the channel amplitude on the sub-carriers of each sub-band, while the phase is adjusted separately.

Error-propagation phenomena and computational complexity of the filters' design are important drawbacks of existing decision-feedback equalizers (DFE) for dispersive channels. In this paper, we propose a new iterative block DFE (IBDFE) which operates iteratively on blocks of the received signal. Indeed, a suitable data-transmission format must be used to allow an efficient implementation of the equalizer in the frequency domain, by means of the discrete Fourier transform. Two design methods are considered. In the first method, hard detected data are used as input of the feedback, and filters are designed according to the correlation between detected and transmitted data. In the second method, the feedback signal is directly designed from soft detection of the equalized signal at the previous iteration. Estimators of the parameters involved in the IBDFE design are also derived. From performance simulations on a wireless dispersive fading channel, we observed that the IBDFE outperforms existing DFEs. Moreover, the IBDFE exhibits a reduction of the computational complexity when compared against existing schemes, both in signal processing and in filter design.

This paper is focused on low-complexity joint-detection (JD) algorithms, where the computational complexity is reduced using banks of discrete Fourier transformations. Mainly, we have developed a fast hybrid zero-forcing block decision-feedback equalizer (H-ZF-BDFE) combining the Fourier-based JD scheme (IEEE J. Sel. Areas Commun., vol. 19, p. 1461, 2001) with the fast decision-feedback structure (F-ZF-BDFE) IEEE J. Sel. Areas Commun., vol. 19, p. 245, 2001. In a Rayleigh frequency-selective fading channel, the new structure yields an improvement in E/sub b//N/sub 0/ of almost 2 dB against the fast block linear equalizer (BLE) (IEEE J. Sel. Areas Commun., vol. 19, p. 1461, 2001) at a bit error rate (BER)=10/sup -3/. Moreover, it has the same performance as the F-ZF-BDFE, but the computational complexity for the signal processing is reduced by almost 50%.

In wireless broadband communications using code division multiple access (CDMA), interference cancellation (IC) techniques have been proposed to reduce multiuser access interference (MAI); however, their performance is limited by complexity constraints that still favor the use of rake receivers. In this paper, we propose an IC architecture that makes use of a block decision feedback equalizer (DFE) to remove intersymbol interference (ISI) and whose overall complexity is much lower than equivalent (in terms of performance) existing structures. In fact, by making use of a particular block data transmission format, all filters are implemented in the frequency domain (FD), and in particular, the DFE is iteratively designed according to the reliability of the detected data in the previous iteration. Due to the strong interaction of the FD-IC and the block DFE, error propagation in the receiver is reduced by simply interleaving (INT) chips before transmission. Simulations performed for an uplink communication on a wireless multipath channel show that the combination of FD-IC, block DFE, and chip INT provides an efficient solution with good performance for CDMA systems in dispersive channels.

In broadband code division multiple access (CDMA) communications, it has been shown that receivers based on successive interference cancellation (SIC) provide an effective reduction of multiuser access interference at an affordable complexity. We propose an optimization of CDMA systems by using power control and a suitable order of user detection at the SIC receiver. The aim is to minimize the total transmit power, while ensuring equal signal to noise plus interference ratio (SNIR) at the detection point for all users. Performance evaluation in an uplink multiuser scenario for the UMTS-TDD standard shows that the proposed algorithm provides energy saving of up to 7 dB in the absence of scrambling and up to 3 dB in the presence of scrambling, with respect to existing architectures based on SIC.

In this paper we address the problem of how best selecting the smallest set of transmission modes (i.e. modulation and channel code formats) to be employed in adaptive modulation and coding (AMC) schemes for OFDM. In fact, by decreasing the number of allowable modes, the complexity of the ACM scheme is greatly reduced. The method makes use of an optimum throughput maximization algorithm for the bit and power allocation. We start with a large set of possible transmission modes. Then, for a given channel, we iterate the loading algorithm with mode sets having successive removal of the mode which yields the smallest contribution to the overall throughput. By using this method in a Rayleigh fading channel, we are able to show that in the test case of the HIPERLAN/2 modes, up to five modes out of seven can be removed with a very small impact on the average achievable throughput.

A convolutional coded MC-CDMA system is considered for high-rate data transmission in a typical indoor environment with Rayleigh multipath fading. To mitigate the effect of multiple-access interference, new results, with iterative parallel and successive soft-interference cancellation schemes, that can benefit from information available through decoding, are presented, both for downlink and uplink transmissions. Based on the results, a combination of convolutional coding with soft successive interference cancellation (SIC) is found to be attractive also in the more critical fully loaded uplink scenario. Furthermore, in order to reduce the latency of SIC, a simplified receiver is presented where only a reduced number of users is canceled, based on a power criterion; on average, the latency of the system is halved, while the offered performance is still reasonably good.

In this paper the possibility of using pre-equalization on the uplink of a MC-CDMA system is investigated. Specifically, different single-user techniques are analyzed together with two approaches to limit the transmit power. Results of computer simulations show that pre-equalization is a very effective technique for the uplink and that several single-user techniques, with different degrees of complexity, can be applied.

The filtered multitone (FMT) modulation requires both equalization of the transmission channel and of the transmit subchannel filters. Since decision feedback equalization is affected by error propagation and yields a greater complexity when combined with coding, in this paper we consider the use of pre-coding for FMT. However, by observing that precoding disrupts partially the subchannel orthogonality, we propose a new fractionally spaced pre-coding scheme, and consequently a novel subchannel filter design method based on a MSE criterion. The resulting scheme restores the subchannel orthogonality and it is also simpler than previous architectures. By simulations performed on an indoor broadband wireless transmission scenario we show that in general precoding schemes outperform equalization schemes. Furthermore, the fractionally spaced pre-coding scheme outperforms classical pre-coding schemes by about 2 dB.

In order to defeat both intersymbol and multiple access interference arising in code division multiple access systems, numerous multiuser detection techniques have been investigated . Actually, the computational complexity of the optimum maximum-likelihood multiuser detector (MLMD) increases exponentially with the number of users, therefore it is infeasible. We propose two suboptimum versions of MLMD, especially designed for down-link connections, which are based on a computational efficient reduced-state technique. It has been found that these algorithms have a significant performance gain as compared with other suboptimum joint detection criteria, such as zero forcing and minimum mean squared error. Moreover, they have a computational complexity which is proportional to the number of users.

Most comparisons between single carrier and multicarrier modulations assume frequency-domain linear equalization of the channel. We propose a new frequency-domain decision feedback equalizer (FD-DFE) for single carrier modulation, which makes use of a data block transmission format similar to that of the orthogonal frequency-division multiplexing with cyclic prefix (OFDM). The scheme is a nonadaptive DFE where the feedforward part is implemented in the frequency domain, while feedback signal is generated by time-domain filtering. Through simulations in a HIPERLAN-2 scenario, we show that FD-DFE yields a capacity very close to that of OFDM. This result is also confirmed by analytical derivations for a particular case. Furthermore, when no channel loading is considered, FD-DFE performs closely to OFDM for the same averaged frame error rate in a coded transmission. Design methods of the FD-DFE are investigated and a reduced complexity technique is developed, with the result that FD-DFE and OFDM have a similar computational complexity in signal processing.

Multicarrier systems are adopted in several standards for their ability to achieve optimal performance in very dispersive channels. In particular, orthogonal-frequency division multiplexing (OFDM) and filtered multitone (FMT) systems are two examples where the modulation filter has an ideal rectangular amplitude characteristic in time and frequency domains, respectively. In this letter, we propose new equalization schemes for FMT and compare their performances with OFDM. In general, FMT has a greater spectral efficiency than OFDM, due to the absence of the cyclic prefix and a reduced number of virtual carriers. However, it exhibits a higher distortion per subchannel, due to the imperfect equalization of the transmit filters. As a performance comparison, we considered both the achievable bit rate (ABR) and the bit error rate (BER) in a multipath Rayleigh fading channel. We note that while ABR gives a theoretical bound on the system bit rate, assuming the knowledge of the channel at the transmit side, the BER refers to an uncoiled system with a fixed modulation. Although FMT requires a fixed structure with a higher computational complexity than OFDM, it turns out that FMT, even with the simplest one tap per subchannel adaptive equalizer, yields a better performance than OFDM, both in terms of ABR and BER. Hence, FMT can be a valid alternative to OFDM for broadband wireless applications, also.

The third generation cellular communications standard (UMTS) will be based on wideband code division multiple access technology. In this paper the conventional RAKE receiver architecture is compared to the chip matched filter (CMF). Consider that performance of both RAKE and CMF is highly dependent on the channel impulse response estimate which is typically carried out by a correlation method for the RAKE. The CMF instead allows for the more powerful least squares (LS) method. Indeed, due to the presence of interference and noise, better results are obtained by considering only the coefficients of the channel impulse response with higher amplitude. Hence, two new structures, the reduced chip matched filter (R-CMF) and the selective RAKE (S-RAKE) architecture have been considered. For a typical UNITS environment we compare the performance of CMF, R-CMF and S-RAKE both in terms of signal to estimation error (SER) and bit error rate (BER) and show that R-CMF outperforms both S-RAKE and CMF.

We propose two reduced state versions of maximum likelihood multiuser detector (MLMD) for down-link connections in time division-code division multiple access (TD-CDMA) systems. Simulation results have shown that these algorithms perform substantially better than other widely used suboptimum detection techniques. Moreover, they have a computational complexity proportional to the number of users.

In the hybrid multiple access technique time division-code division multiple access (TD-CDMA), both multiple-access interference and intersymbol interference (ISI) arise. In order to combat the overall interference, we propose four efficient joint detection schemes based on zero-forcing and minimum-mean square error criteria. By exploiting the Toeplitz-block structure of matrices and the asymptotic equivalence between finite-order Toeplitz matrices and circulant matrices, most computations can be carried out very efficiently through extensive use of discrete Fourier transform (DFT) and independent DFT (IDFT) transforms. Performance results based on the UMTS scenario are presented.

Coherent detection of HIPERLAN Gaussian minimum-shift keying signals calls for complex and expensive receivers. However, when the channel delay spread is limited to at the most 50% of the symbol time and a reliable line-of-sight component of the radiated signal exists (Rician fading model), noncoherent detectors are capable of achieving a good performance. Based on the above motivations, we compare four different demodulation techniques, namely the following: (1) one-bit differential detector; (2) discriminator detector; (3) limiter discriminator detector; and (4) limiter discriminator integrator detector (LDID). The intersymbol interference introduced by these demodulators is nonlinear (with respect to the data symbols) and a decision-feedback equalizer (DFE) based on a mean square-error criterion may not be appropriate. Moreover, at this high speed, a DFE may be very complex to implement. Hence, we propose a new DFE design method that increases the eye-diagram aperture by removing the worst case interference. Performance of the above demodulators in the presence of a simple nonlinear DFE (with feedback part only) is computed in terms of the bit-error rate (BER) by means of the saddle-point approximation. This procedure, for static channels, turns out to be a very general tool with a simple and robust implementation. The same method can be applied, for multipath fading channels, to the BER evaluation as part of a semianalytic approach. The main conclusion from this work is that for LDID demodulators and in the presence of Rician fading channels with an average normalized root mean square delay spread of 0.3 and dual antenna diversity, the new equalizer lowers the outage probability from 60% to 10% at a BER of 10/sup -4/.

Noncoherent demodulators are very attractive for high performance radio LAN (HIPERLAN) systems because of their low implementation costs and their inherent robustness against frequency and carrier phase offsets. However, when the channel is time dispersive, the nonlinear intersymbol interference (ISI) introduced by these demodulators precludes the use of conventional linear equalization strategies. We present an alternative noncoherent receiver structure followed by a nonlinear equalizer, which includes a RAM and a Viterbi detector, capable of equalizing nonlinear multipath fading channels. In addition, we also present a new algorithm specifically for noncoherent demodulators, which allows estimation of all useful signal values at the input of the equalizer to be stored in the RAM. By means of computer simulations, we report the performance and computational complexity tradeoffs of the receiver/equalizer structure, including antenna diversity. We show that demodulators which consist of a complex receiver and a Viterbi detector are much more robust against multipath fading channels than traditional real noncoherent demodulators. The results suggest that in a typical HIPERLAN scenario, where the channel delay spread is less than 50 ns and a reliable line of sight component exists, it is feasible to combat multipath effects using noncoherent demodulation.

We report a very efficient semianalytical approach for the performance evaluation of differential detection schemes for GMSK signals of the DECT standard. Precisely, for a given channel, the performance is determined by means of an analytical procedure which includes the saddlepoint approximation. We consider both static channels (with impulse response generated by the simulation program SIRCIM) and two-ray Rayleigh and log-normal fading channels. As a departure from previous works, our receiver includes an all-digital part after the analog differential detection scheme. The digital part includes: (1) a block for the estimation of both the optimum sampling phase and the nonlinear channel coefficients (by making use of the DECT training sequence), (2) a one-tap decision feedback (DF) equalizer, and (3) a block for the evaluation of the approximate optimum bias level (/spl gamma//sub e/) in the threshold detector. Both the DF equalizer coefficient and /spl gamma//sub e/ are based on the nonlinear channel coefficients estimate. For channels with a normalized delay spread up to 0.2, the use of the optimum threshold together with the DF equalizer permits a gain of about 2 dB at BER=10/sup -6/ with respect to a receiver without equalization and a zero-level decision threshold. In addition, we discover that, in indoor environments, the 2-bit GMSK detector performs roughly the same as the 1-bit detector. The threshold optimization is also effective in the presence of channels affected by fading. To support this statement, we report the performance of the 1-bit differential detection scheme combined with antenna selection diversity in the presence of a two-ray log-normal and Rayleigh fading channel.

In earlier work, the performance (in terms of data eye closure) of a threshold detector in 2- and 4-PSK modulation schemes has been analyzed for wireless indoor systems using narrowbeam antennas. Here, assuming the channel is known, a very efficient implementation of the Viterbi algorithm (VA) is included in the receiver, and a bit-error rate (BER) criterion is used to evaluate the receiver robustness to channel conditions. In contrast to the earlier work, it is seen that 4-PSK signals with VA detectors are indeed more robust than 2-PSK signals to channel conditions.

We evaluate the performance, in terms of bit-error rate, of 1- and 2-bit differential detectors for Gaussian minimum-shift keying (GMSK) signals by using a very fast numerical technique which makes use of the saddle point approximation. Moreover, the performance of each detector is optimized by using a closed-form expression of the optimum threshold in the slicer.

This paper presents a reduced complexity Viterbi algorithm for use as sequence estimator for linear intersymbol interference channels with coarsely located coefficients. In particular, the complexity does not depend on the channel impulse response length but only on the number of nonzero coefficients. No approximations are used in the algorithm. We consider a multipath environment producing time spreads.

We discuss the real time classification of high speed (/spl ges/4800 b/s) voiceband data signals using blind or self-recovering equalization techniques. After equalization, the signals are classified, by means of their constellation magnitude, using a new classification scheme which computes the probability that the unknown test signal belongs to each of several predetermined classes. Heuristic rules are applied to these probability functions to perform the actual signal detection. Even in the presence of added channel impairments, the use of this new approach resulted in an overall classification accuracy of greater than 98%, measured using 5100 test segments collected from 6 classes of signals produced by V.29, V.32, and V.33 modems. Classification times range from median values of 0.090 s and 0.219 s for the V.29 modem at 4800 and 7200 b/s, respectively, up to a worse case time of 3.33 s for the 9600 b/s default class, chosen only if no other signal is detected within a prescribed amount of time.

The problem of distinguishing speech from voiceband data is treated. A discrimination function based on the sign of the autocorrelation at lag two of the incoming signal and the second-order moment of the complex low-pass signal is presented. The algorithm has been applied to many types of voiceband data signals and, within a window of 32 ms, correctly classifies them. For the limited number of speech signals available, the amount of misclassification of speech as voiceband data was observed to be about 1%.>

To eliminate multipliers in the hardware implementation, filters with the coefficients that are given by the sum or difference of two power-of-two terms are designed. For a minimax criterion, a global optimization procedure known as simulated annealing has been used to determine the coefficients. Significant improvement in the filter performance is gained over methods that simply round the infinite precision solution. The algorithm also allows the maximum value of the coefficient wordlength beyond which filter performance does not improve to be found. A number of design examples involving typical video specifications, such as deinterlacing filters and luminance/chrominance separation filters, are reported. The method proves to be very effective, yet the designs are within the dimensional limits of the filters used in current industrial applications.>

After an ad hoc extension of the multilayer perceptron model to complex signals, a blind neural network equalizer is proposed. Several experimental results are also reported which prove the effectiveness of this approach for equalizing a digital satellite radio channel in the presence of mild nonlinearities and intersymbol interference. Moreover, the proposed method works without any knowledge about the nonlinear nature of the channel.>

Results on the application of the simulated annealing (SA) algorithm to the problem of finding the coefficients of a digital filter with very coarse coefficients values (namely, power-of-two) are presented. For a minimax criterion in the frequency response, the algorithm was found particularly useful for designing a cascade-form FIR (finite impulse response) filter whose performance is known to be superior to that of direct-form filters. Because the SA algorithm is a global optimization method, all stages are designed simultaneously, thus avoiding the classical iterative procedure. The final result is better performance at a higher computational cost.>

A very versatile algorithm for the design of finite-wordlength filters is described. It is a simulated annealing algorithm, derived directly from the simulated annealing algorithm for functions of continuous variables which searches over discrete values of the filter coefficients. It has very fast development time and produces filters with good performances. Its only drawback is a very long execution time. Three examples of filter design are included.>

Due to the feedback architecture of the standard CCITT and ANSI 32-kb/s ADPCM (adaptive digital pulse-code modulated) coders, large transitional errors occur when characteristics of the input signal suddenly change. This particularly holds for FSK modems that transmit a single-frequency signal between actual characters. A mechanism that identifies these transitions and reduces errors is presented.>

Two approaches are presented for accommodating 9.6 kb/s modem signals (e.g. V.29) through 32 kb/s ADPCM (adaptive digital pulse-code modulation) links. These are small changes in the existing algorithm and coding with ADPCM incorporating a 5-bit, rather than 4-bit quantizer. For each approach, tradeoffs between performance and implementation complexity are described.>

New classes of nonrecursive linear digital filters are proposed as alternatives to conventional methods for digital signal processing devices. In fact, the traditional approach, where signal samples are represented by 8-15 bit words, can be very expensive to implement due to the complexity of multibit multipliers and adders. Filter structures consisting of a transversal filter with tap coefficients restricted to - 1, 0, or + 1 and cascaded with simple recursive sections are proposed. Using a mean square error criterion, dynamic programming methods to select optimum sets of coefficient values for the taps are presented and evaluated. It is shown that these structures lend themselves to very simple hardware implementations and offer a valid alternative to the conventional filtering approach. Designs for several example filters are presented, and their implementation complexity is examined.

FIR filters with powers-of-two coefficients are attractive for cost-effective implementations. The performance of one such structure, the difference routing digital filter [8], is discussed. Using an SNR criterion, an optimal algorithm to select the value of the filter coefficients is presented. Results indicate that a 2-3 dB improvement in the SNR can be obtained with this new approach. In addition, the study gives some insight into the relationship between the filter sampling rate, the number of coefficients, and the size of the coefficient alphabet. In particular, it is seen that a tradeoff between the filter sampling rate and the size of the coefficient alphabet exists.