Pilot contamination is considered as a bottleneck in the massive multi-input multi-output (MIMO) systems. In a previous work, we proposed a novel iterative algorithm, dubbed channel Zooming Algorithm (CZA), to ensure the mitigation of pilot contamination effect. For this, we assumed that each cell is assigned a set of orthogonal pilot sequences and that these same pilot sequences are reused in other cells. In this paper, we propose a novel strategy of pilot design, based on the divide-and-conquer approach (DCA), aiming to halve the contamination power observed by the channel estimate and to conquer the remaining pilot contamination through the iterations of the CZA. More precisely, instead of being contaminated by a given number of contaminants, as in the initial approach of the CZA, the user, in the proposed approach, is contaminated by a twice the number of contaminants, while halving the pilot contamination power coming from each one of them. We confirm the effectiveness of the proposed scheme with analytical and simulation results and show that the CZA algorithm is more efficient and faster to eliminate the contamination in this case.

In this paper, we extend the joint use of the Time Reversal (TR) precoding technique and the Ping-Pong Optimized Pulse Shaping (POPS) waveform optimization algorithm to design optimal transmit and receive waveforms for Multiple Input Single Output-Orthogonal Frequency Division Multiplexing (MISO-OFDM) systems. The design process banks on a full characterization of the scattering function of the TR-MISO channel, followed by the implementation of the POPS approach. Numerical analysis reveal a significant gain, brought by the optimized waveforms in TR-MISO-OFDM systems, in terms of Signal to Interference plus Noise Ratio (SINR), compared to the optimized waveforms in TR-SISO-OFDM systems and the PHYDYAS waveform in TR-MISO-OFDM systems.

This paper presents a new adaptation of a Gaussian echo model (GEM) to estimate the distances to multiple targets using acoustic signals. The proposed algorithm utilizes m-sequences and opens the door for applying other modulations and signal designs for acoustic estimation in a similar way. The proposed algorithm estimates the system impulse response and uses the GEM to limit the effect of noise before applying deconvolution to estimate the time of arrival (TOA) to multiple targets with high accuracy. The algorithm was experimentally evaluated for different scenarios with active (trans-mitters) and passive (reflectors) targets at proximity. In the case of closely spaced static passive targets, results show that 90% of the ranging errors are below 7 mm. When tracking two moving active targets approaching very close proximity, results show that 90% of the ranging errors are less than 10 mm.

The Evolved Variational Message Passing algorithm (E-VMP) and the Cooperative Robust Geometric Positioning Algorithm (C-RGPA) are two novel techniques for cooperative localization in wireless networks. They can perform an accurate location with less computational and time complexity compared to other cooperative localization algorithms. On the other side, limitations on the computational power and battery life present a critical constraint when executing these algorithms. For this reason, we propose in this paper applying these algorithms based on coalitions formation game in order to reduce communication costs. According to our simulation results, the two resulted proposed techniques give accurate location estimates compared to other cooperative localization techniques on the one hand and optimize the power and battery consumption on the other hand.

The necessity of supporting the expected 5G's services, which reveal major limits to ensure strict synchronism and orthogonality, has brought researchers to conceive new waveforms. Recently, the Ping-pong Optimized Pulse Shaping (POPS) algorithm [1] has been introduced as a powerful tool to efficiently design waveforms candidates for 5G. In this paper, we characterize a new design of PHYDYAS waveforms, namely POPS-PHYDYAS, which it is based on the mix of the POPS algorithm and the PHYDYAS waveform [2]. These new waveforms ensure higher SINR level compared to the original PHYDYAS waveforms, as they are conceived by Mirabbasi-Martin [3]. Performances of POPS-PHYDYAS are compared to several 5G waveforms in terms of SIR, OOB emissions and BER.

A major trend of the current research in 5G is to find well time and frequency localized waveforms, dedicated to non‐orthogonal wireless multi‐carrier systems. The ping‐pong optimized pulse shaping (POPS) paradigm was proposed as a powerful technique to generate a family of waveforms, ensuring an optimal signal to interference plus noise ratio (SINR) at the receiver. In this paper, we derive, for the first time, the analytical expression of the SINR for FBMC/OQAM systems. We then adopt the POPS algorithm in the design of optimum transmit and receive waveforms for FBMC/OQAM, with respect to the SINR criterion. For relatively high dispersions, numerical results show that the optimized waveforms provide a gain of 7 dB, in terms of SINR, compared to the PHYDYAS waveform. They also show that the obtained waveforms offer better out‐of‐band (OOB) emissions with regard to those of the IOTA waveform. Furthermore, we notice that FBMC/OQAM systems present a gain of 4 dB in SINR, compared to FBMC/QAM systems, when both operate at their time‐frequency lattice critical densities. However, FBMC/QAM systems can guarantee, with a reduced computational complexity, a comparable performance to FBMC/OQAM systems, in terms of SINR, when their spectral efficiency is relatively reduced by less than 5%.

In this paper, we propose a nodes identification scheme based on embedded signaling for relay systems where a data sequence transmitted by a source node is forwarded by a selected relay node before reaching the destination node. In the proposed identification scheme, source and relay nodes incorporate precoding sequences, based on codewords generated from block codes, into the data sequence. A soft decoding at the destination node allows it to efficiently recover in one step the identities of transmitting source and relay nodes of received packets. The proposed scheme is an alternative to classical explicit identification scheme based on exchanging signaling information before the data exchange and including identities in the data sequences. We also propose a blind estimation technique allowing the destination to estimate the phase of the channel. We consider the Opportunistic Relay Selection (ORS) and the Partial Relay Selection (PRS) to select relay nodes. Numerical results confirm the performance of the proposed identification scheme.

In this paper, we propose a geometric positioning technique for cooperative localization in Wireless Networks. The proposed technique is based on building geometric constraints from radio observables. These constraints are then merged to estimate the true position. In this paper we address situations where blind nodes, due to the lack of radio observables, cooperate to estimate their positions. Compared to other techniques, Monte Carlo simulations illustrate interesting performances in terms of positioning accuracy and computation complexity and runtime.

This paper investigates the efficiency of the combination of the Ping-pong Optimized Pulse Shaping-Orthogonal Frequency Division Multiplexing (POPS-OFDM) algorithm with the Time Reversal (TR) technique. This algorithm optimizes the transmit and receive OFDM waveforms with a significant reduction in the system Inter-Carrier Interference (ICI)/Inter-Symbol Interference (ISI) and guarantees maximal Signal to Interference plus Noise Ratio (SINR) for realistic mobile radio channels in 5G Systems. To this end, we characterize the scattering function of the TR channel and we derive the closed-form expression of the SINR as a Generalized Rayleigh Quotient. Numerical analysis reveals a significant gain in SINR and Out-Of-Band (OOB) emissions, brought by the proposed TR-POPS-OFDM approach.

Conventional orthogonal frequency division multiplexing (OFDM) may turn to be inappropriate for future wireless cellular systems services, because of extreme natural and artificial impairments they are expected to generate. Natural impairments result from higher Doppler and delay spreads, while artificial impairments result from multisource transmissions and synchronization relaxation for closed-loop signaling overhead reduction. These severe impairments induce a dramatic loss in orthogonality between subcarriers and OFDM symbols and lead to a strong increase in intercarrier interference (ICI) and intersymbol interference (ISI). To fight against these impairments, we propose here an optimization of the transmit/receive waveforms for filter-bank multicarrier (FBMC) systems, with hexagonal time-frequency (TF) lattices, operating over severe doubly dispersive channels. For this, we exploit the Ping-pong Optimized Pulse Shaping (POPS) paradigm, recently applied to rectangular TF lattices, to design waveforms maximizing the signal-to-interference-plus-noise ratio (SINR) for hexagonal TF lattices. We show that FBMC, with hexagonal lattices, offers a strong improvement in SINR with respect to conventional OFDM and an improvement of around 1 dB with respect to POPS-FBMC, with rectangular lattices. Furthermore, we show that hexagonal POPS-FBMC brings more robustness to frequency synchronization errors and offers a 10 dB reduction in out-of-band (OOB) emissions, with respect to rectangular POPS-FBMC.

In relay wireless systems, a data packet transmitted by a source node is forwarded by one or many relays nodes before reaching the destination node. In actual technologies, the destination recovers the identities of the sources and relays of received signals by using signaling information exchange before the data exchange and by including identities information (addresses) in data sequences. In this paper, we propose a novel nodes identification scheme, where a precoding sequence is embedded into the data sequence at each source and relay node, in a multi-sources multi-relays wireless system. The precoding sequences are Maximum Length Sequences (MLS). We propose to efficiently reduce the computational complexity at the receiver by using the Fast Walsh Hadamard Transform (FWHT). The proposed technique allows the destination node to recover the nodes identities without using additional signaling bits. Numerical results validate the proposed identification scheme performance.

In this paper, we are interested in the optimal redistribution of the available budget in average transmit power per packet among potential packet transmission attempts for improved Automatic Repeat reQuest (ARQ) protocol. A conventional ARQ protocol was combined in [5], with both Adaptive Modulation and Coding (AMC) and Power Control (PC) to improve spectral efficiency, while satisfying an average transmit power constraint. The optimal power level as well as the most adequate modulation and coding scheme (MCS) are jointly selected, as a function of the channel state. However, the selected power level remains the same for all retransmission attempts of the same packet. We propose in this paper to wisely distribute this optimally selected power budget among potential retransmissions of a given packet, such that throughput is further maximized, while keeping a fixed average power spent by packet. To do this, a heuristic algorithm based on a dichotomic search approach is performed. The enhancement in performance brought by the improved version of the ARQ protocol to the joint AMC-PC-ARQ scheme is then assessed.

In this paper, we consider a downlink coordinated multi-cells multi-users network, in which each User Equipment (UE) knows its Channel State Information (CSI) perfectly and feeds back its quantized composite channel to the distributed Base stations (BSs) through a limited feedback. We propose a cooperative beamforming design, considering quantized composite channels, that reduces the inter-cell interference for both cases of perfect and outdated quantized CSI and an optimal power allocation that maximizes the system sum rate. Furthermore, we propose a bit labelling of codebooks, used for channel quantization, that outperforms the random labelling under channel feedback errors and delay. We analyze also the sum rate loss due to the outdated and quantized channel knowledge at the transmitter.

This work proposes a method to optimize the resource block allocation in the cloud radio access network for a long term evolution system. This approach consists in three steps. First, the baseband unit collects the required information about users. Then, it optimizes the resource block allocation by carrying out a genetic algorithm. After that, it sends the solution to the remote heads. The simulations results show that the performance of the proposed system is significantly higher with respect to universal frequency reuse.

According to 3GPP standards, the Single Carrier Frequency Division Multiple Access (SC-FDMA) was adopted for Uplink transmission in LTE networks. As multiple mobiles may have access to neighboring base stations simultaneously, the inter-cell interferences are inevitable with this technique and the system throughput is impacted. To mitigate the inter-cell interference and improve, therefore, the system performance, severe schemes have been proposed. However, these schemes target either adapting the power control in mobile stations (e.g. Fractional Power Control technique) or improving the Resource Block (RB) allocation (e.g. Universal Frequency Reuse technique). In this paper, we propose two new techniques to reduce the inter-cell interferences namely: (i) Dynamic Fractional Power Control and (ii) a Resource Block Allocation based on Genetic Algorithm. In addition, we advocate that, by combining these technique, the system can achieve a better throughput.

Adaptive modulation and coding (AMC), power control (PC) and automatic repeat request protocols (ARQ) represent very important link adaptation (LA) techniques for future generations of wireless communication systems. In order to improve the efficiency of these systems, some combination schemes of these LA techniques have been proposed in the literature. Most of these schemes were interested in the combination of only two among the three LA techniques. We have proposed in [8] a novel combination scheme where all of the three LA techniques were optimally combined. The optimality criterion was the maximization of the average throughput efficiency, while meeting an average transmit power constraint, in order to reduce multiple access interference. QoS-sensitive services, like video streaming and IP voice, require a QoS constraint or, equivalently, a packet error probability (PEP) constraint. In this paper we are interested in the optimal combination of the three LA techniques, while satisfying a required PEP performance. More specifically, we derive the optimal AM switching thresholds as well as the optimal transmit power level, in order to achieve the highest average throughput efficiency, given the fading channel conditions and the required error performance. To assess the offered performance gain, the proposed LA scheme is compared to conventional scheme using exclusively AM in combination with ARQ without guaranteeing any QoS. Numerical and simulation results show significant average transmit power gains, with respect to AM-ARQ scheme, while still guaranteeing a satisfying error performance.

In cooperative wireless systems, a data packet transmitted by a source node is forwarded by relay nodes before reaching the destination node. In actual technologies, the destination recovers the identities of the sources and relays of received signals by using signaling information exchange before the data exchange and by including identities information (addresses) in data sequences. This leads to a waste of energy and spectral resources as well as an additional transmission delay. In this paper, we propose a novel blind nodes identification scheme in a cooperative wireless system where a relay node is selected to forward a source node data sequence. Two different relay selection schemes are considered: the Opportunistic Relay Selection (ORS) and the Partial Relay Selection (PRS). The proposed identification scheme is based on embedding precoding sequences into the data sequence at each source and relay node. The choice of the precoding sequences and the destination processing are based on classical coding theory. The proposed identification scheme allows the destination to recover hierarchically the relay nodes and the source nodes by allocating to them different modulation alphabets. Our technique is efficient since it avoids explicit signaling information exchange and allows the destination node to recover the nodes identities without using additional signaling bits. Numerical results validate the proposed identification scheme performance.

Because of its spectrum-sharing nature, a CR network inevitably operates in interference-intensive environments. One challenge is how to maintain the interferences generated by the cognitive transmissions to the primary network below an acceptable threshold level. In this paper, we firstly propose an efficient primary users identification, using compressive sensing (CS). Our focus is on the angular sparsity of the received signal given an unknown number of primary user source signals impinging upon the antenna array from different directions of arrival (DOA). Given multiple snapshots, multiple measurement vectors (MMV) are available at the secondary base station and considered for primary channel detection over the angular domain using the regularized M-FOCUSS algorithm. Then, we develop novel methods for paths separation and primary channels estimation based on their autocorrelation matrix properties. Through simulations, we show that the recovery performance of the proposed approach in terms of false alarm and average minimum square error (MES) between the true and the estimated primary channel, is better than the conventional maximum to minimum eigenvalue (MME) detector.

The 3rd Generation Partnership Project (3GPP) has started to investigate feasibility of machine type communication terminal class in Long Term Evolution (LTE) networks in the Release 12 to address the requirements of the Internet of Tings (IoT) targeting low-end device market with improved coverage. Along with that, the 3GPP has defined reference signals to support device discovery, communication and synchronization. These signals are transmitted by either an eNB within the coverage area, or a peer User Equipment (UE) in partial and out of coverage scenarios. The regular LTE synchronization signals, built from Zadoff-Chu (ZC) sequences and M-sequences, are reused in Rel-12. In this paper, we deal with low- complexity synchronization approach based on ZC sequences and tailored to LTE signal. The presented approach carries out Simply-Differential (SD) correlation-based metric that allows the detection of a ZC sequence pattern within the received signal. The SD metric correlates the received signal and compensates the output with an adjustment frequency whose value depends on the training ZC sequence. To reduce the huge computational load resulting from differential correlation operations, a recursive implementation of the SD metric is proposed. The performance is here evaluated in terms of theoretical probability of correct detection and compared to the experimental rate of correct detection to validate the analysis. The obtained results show good match between analytical and experimental probabilities.

In wideband communication systems, Multi-Input Multi-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) has been proposed as an efficient technique to enhance the link reliability and the spectral efficiency. However, the high Peak to Average Power Ratio (PAPR) of the output signals degrades the advantage of the MIMO-OFDM systems. In order to overcome this issue, several methods requiring the explicit transmission of Side Information (SI) bits have been investigated in the literature. Nevertheless, the wrong estimation of the SI leads not only to a damage on the total signal recovery but also to a loss of the entire OFDM sequence which, causes severe degradation in the system performance. Additionally, the transmitted bits must be channel-encoded as they are particularly susceptible to the error performance of the OFDM system, which highly increases the complexity and the end-to-end latency. Therefore, we propose in this paper a blind and reduced complexity technique for MIMO-OFDM systems under high frequency selective channels. At the transmitter side, the proposed method exploits a new form of embedded signaling such as the use of the Zadoff-Chu matrix transform. Regarding the receiver side, the proposed method exploits simultaneously an enhanced Alamouti decoder scheme and an optimized estimation process that is based on calculating the high order statistic of the received signal. Finally, performances evaluation show the usefulness of the proposed methods in Long Term Evolution (LTE) standards.

Recently, Orthogonal Frequency Division Multiplexing (OFDM) has gained more attention as an effective technique for high data rate future wireless communication systems. In order to provide maximal spectral efficiency, the prototype waveform, used in these systems, must guarantee orthogonality even the rapidly time-varying and strongly delay-spread characteristics of the channel propagation. However, its performance gain degrades in the presence of the system Inter-Carrier Interference (ICI) and Inter-Symbol Interference (ISI) which make it essential to develop an efficient technique to overcome these interference over the time-frequency dispersion of the radio mobile channel. In this paper, we propose a Ping-pong Optimized Pulse Shaping-OFDM (POPS-OFDM) algorithm that maximizes the received Signal to Interference plus Noise Ratio (SINR) by systematically optimizing the OFDM waveforms at the Transmitter (TX) and Receiver (RX) sides. We derived the exact closed-form expression of the SINR of the considered multicarrier system and the optimized waveform is searched as a linear combination of several of the most localized Hermite functions. The results confirm the advantage behind the POPS-OFDM algorithm in enhancing the performance compared to multicarrier systems using conventional waveforms. Simulations are given to support our claims.

In this paper, we propose the use of differential space-time block coding to improve the synchronization for Wireless Local Area Networks (WLAN) without any channel estimation requirement. We study the application of an efficient synchronization technique recently proposed for 2×1 MISO-OFDM systems in the IEEE 802.11n WLAN for 2×1 and 2×2 MIMO configurations. The proposed technique exploits a preamble of two identical parts and splits the synchronization processing into two stages: an auto-correlation based coarse stage and a cross-correlation based fine stage. The coarse synchronization aims to detect a repetitive pattern within the received signal in order to roughly localize the preamble start. Then, to benefit from the spatial diversity, differential decoding must be achieved before carrying the fine synchronization. The cross-correlation based fine metric is calculated over a short interval centered on the coarse time estimate, which provides accurate preamble start estimation with relatively reduced computational load. As a byproduct, the fractional part of the frequency offset is also estimated through the evaluation of the timing metric at the estimated preamble start. Simulation results show that, when applied to the IEEE 802.11n signal, the proposed synchronization scheme provides better detection performance compared to the considered benchmark.

In this paper, we consider a downlink Multiple-Input-Multiple-Output (MIMO) underlay cognitive radio network where unlicensed Secondary Users (SUs) share the Primary Users (PUs) spectrum. We assume that the channels from the Secondary Base Station (SBS) to each receiver are known to the SBS. We propose a beamforming matrix design to ensure that the transmitted signal does not cause harmful interference to the PUs and SUs. Furthermore, we study the optimal power allocation that maximizes the sum rate of the secondary system when the channel is not perfectly known at the SBS. Simulations results show the performance of our system in terms of sum rate of the secondary users in both cases of perfect and imperfect knowledge of Channel State Information (CSI) at the SBS.

Due to high mobility situations that are commonly envisaged for the next Fifth Generation (5G) of mobile communication systems, the wireless propagation channel becomes a time-frequency variant, where the time dispersion emerges from the multipath characteristic and the time-selectivity arises from the Doppler spread. This aspect can dramatically damage the waveforms orthogonality that is induced in the Orthogonal frequency division multiplexing (OFDM) signal. Consequently, this results in oppressive Inter-Carrier Interference (ICI) and Inter-Symbol Interference (ISI), which leads to performance degradation in OFDM systems. To efficiently overcome these drawbacks, we propose Ping-pong Optimized Pulse Shaping-OFDM (POPS-OFDM ) algorithm that maximizes the received Signal to Interference plus Noise Ratio (SINR) by optimizing systematically the OFDM waveforms at the Transmitter (TX) and Receiver (RX) sides. We derived the exact closed-form expression of the SINR of the considered multicarrier system and the optimized waveform is searched as a linear combination of several of the most localized Hermite functions. Then, we go further by testing its robustness against time synchronization errors. The results confirm the advantage behind POPS-OFDM algorithm in enhancing spectacular performance and its robustness compared to multicarrier systems using conventional waveforms. Simulations are given to support our claims.

In this paper, we propose a robust timing and frequency synchronization scheme for MIMO-OFDM systems. Exploiting a preamble of two identical parts and proceeding in two stages, the proposed technique achieves synchronization under non- coherent detection. To take advantage from transmit diversity, we use differential Alamouti space time block coding which provides full- spatial diversity without requiring any channel knowledge in neither the transmitter nor the receiver. Two different replicas of the preamble are generated and sent simultaneously from dual- antenna transmitter. At the receiver side, a coarse synchronization is first carried onto the received signal to roughly localize the preamble respecting the famous Cox and Schmidl algorithm. Second, differential Alamouti decoding must be achieved to recover the transmitted signal. Then, a fine synchronization metric is calculated based on cross-correlating the recovered signal with the local known preamble to detect the exact preamble start. The fine metric is calculated over a short interval around the coarse time estimate which relaxes the computational complexity of this stage. As a byproduct, the fractional part of the frequency offset is estimated using the same timing metric. Computer simulations carried to evaluate the proposed technique show its robustness in the Rayleigh fading channel under non-coherent reception.

Cooperative multiband spectrum sensing presents the next generation of cognitive radio networks, where multiple bands are sensed and accessed to improve spectrum maintenance and to enhance the network throughput. In order to concretize this concept, several uniform cooperative spectrum sensing techniques have been proposed in literature which suffers from a high complexity computation over the global sensing scheme. To overcome this limitation, this work proposes a robust and efficient spectrum sensing technique. The proposal investigates a new alternative of Single-Pixel-Camera adaptation of the cooperative multiband spectrum sensing for Cognitive Radio. Instead of using the conventional uniform band measurements, we investigate a non-uniform approach, where the time of sensing is reduced by using a hard and soft decision metric. Moreover, this approach allows to enhance the performances in terms of spectrum sensing. Simulation results are given to support our claims.

Wireless mesh networks (WMNs) have been developed to answer the needs of many wireless applications. A major limiting parameter of the performance of WMNs is the interference between the several communications that occur simultaneously in the same network. To address this limitation, an adequate scheduling algorithm has to be implemented. Hence, this paper focuses on the scheduling problem under the physical interference model. This problem is known to be NP-Hard problem. In this paper we develop and propose two efficient scheduling algorithms. We evaluate their performances by simulation in terms of spatial reuse and we compare their performance with known previously-proposed algorithms. We show that our proposed algorithms provide high performances with low complexity.

In 3GPP Long Term Evolution (LTE) system, cell search must be first performed to allow the connection between the user equipment and the serving cell. In this paper, we investigate sector search, which is a part of the cell identifier, as well as timing synchronization based on the standardized Primary Synchronization Signal (PSS) generated from known Zadoff-Chu sequences. To this aim, an initial reduced complexity metric is first calculated to provide a coarse PSS start estimate. Then, to determine the sector identifier and fine tune the PSS start estimate, the received signal is cross-correlated to the known PSS candidates. The fine metric, which exhibits high sharp peak, allows detecting the PSS start and the sector identification. Unlike the conventional methods that perform the cross-correlation over all demodulated OFDM symbols, the proposed one carries it over a short interval centered on the coarse estimate, which greatly reduces the complexity. Simulation results show that the proposed approach provides satisfactory performance in terms of time estimation accuracy and successful sector identification rate. For practical SNR values, it also outperforms the considered benchmarks in the frame of LTE systems primary synchronization.

In this paper, we investigate limited feedback precoding for stacked space-time architectures over Rayleigh fading MIMO channels, for the cases where the components are taken from orthogonal or algebraic non-orthogonal designs. Stacked constructions allow to achieve high spectral efficiency. Our precoding approach enables an efficient decoding of the component codes and an improvement of the array gain. We use at the receiver a VBLAST signal processing which is based on a successive component interference suppression. For selecting the optimum precoding matrix among grassmannian codebook matrices, we consider a criterion based on maximizing the minimum signal to interference and noise ratio over all components of the stacked design. Simulations show that limited feedback precoding for a stacked algebraic design performs better than precoding for the cases of stacked Alamouti design and of spatial multiplexing scheme for the same number of transmit and receive antennas, the same spectral efficiency and the same number of bits on the feedback link.

In this paper, we study the problem of power control in a wireless ad hoc system. We consider multiple links of two hops relating source to destination. We propose to use a utility function corresponding to an approximation of the capacity of each link at high Signal to Interference plus Noise Ratio (SINR). We study analytically the problem of maximizing the sum utilities. We assume that users adjust their powers in an interference aware manner and propose a solution based on a distributed pricing power allocation algorithm. Then we prove its convergence to a unique optimal point. The overall approach's efficiency is illustrated via several simulations.

Selected Mapping (SLM) is a promising technique dedicated to reduce the Peak-to-Average Power Ratio (PAPR) in OFDM systems. In this technique, different representations of OFDM symbols are generated by rotating the original frame using different phase sequences. Then, the signal having the minimum PAPR is selected and transmitted. To compensate the effect of the phase rotation at the receiver side, it is necessary to transmit the index of the selected phase sequence as an explicit Side Information (SI). In this paper, we propose a novel robust blind SLM technique that avoids sending any explicit (SI), where the selected signal index (SI) is embedded in the transmitted data by using an adequate transformation such as the Hadamard one. Furthermore, in order to recover the used (SI) index, we propose an optimized scheme which exploits mainly the higher-order statistics moments and cumulants of the received signal. We show that our proposed method guarantees a reliable signal recovery at the receiver side and dramatically reduces the PAPR level at the transmitter side. Simulation results are given to support our claims.

Orthogonal Frequency Division Multiplexing (OFDM) technique is a promising modulation scheme for high performance broadband wireless communications. This technique suffers from a major drawback which is the high Peak to Average Power Ratio (PAPR) of the output signals. In order to resolve this issue, several methods that require the transmission of explicit side information (SI) have been proposed. In this paper, we propose two robust blind techniques that offer the possibility to avoid the transmission of any explicit (SI). First, we investigate a new technique refered as Blind Dummy-Zero-Insertion (DZI) which uses an adequate embedded signaling, consisting of a special matrix mask. Second, in order to enhance the signal detection process and the PAPR gain, we combine the proposed technique with the SLM method as Combined-SLM-DZI. Both methods employ an optimized scheme, during the estimation process, based on calculating the energy of the received signal. Performance evaluation shows the advantage of the proposed methods on the PAPR reduction and also proves the perfect signal recovery at the receiver side.

In this paper we propose novel efficient algorithms that allow optimal waveform design for multicarrier systems, specifically for the Orthogonal Frequency Division Multiplexing (OFDM) based systems. We start from the rapidly time-varying and strongly delay-spread characteristics of the prorogation channel that are used for such transmission systems and include them in the closed-form expression of the Signal to Interference plus Noise Ratio (SINR) of the considered multicarrier system. Using our algorithms for maximizing the derived SINR expression leads to obtain the optimal waveforms at both the Transmitter (Tx) and the Receiver (Rx) sides, that significantly reduce the system Inter-Carrier Interference (ICI)/Inter-Symbol Interference (ISI) and guarantee maximal SINRs for realistic mobile radio channels. Our proposed algorithms allow to design waveforms at the Tx/Rx sides that are adapted to the channel propagation conditions and hence result in spectacular performance enhancement compared to multicarrier systems using conventional waveforms. Simulation results are given to support our claims.

In this paper, we propose a novel optimized blind selected mapping (SLM) technique that avoids the need of the use of any side information (SI) through the joint exploitation of a set of rotated and unrotated QAM constellation of the Orthogonal Frequency Division Multiplexing (OFDM) signal and that consequently performs the role of an inherent embedded signaling for the OFDM system. Furthermore, in order to efficiently recover the transmitted sequence, we propose a set of decision schemes that banks on the Max-Log-Maximum A Posteriori (MAP) algorithm from which we investigate hard and soft decision processes. Our proposed method guarantees a reliable and perfect signal recovery at the receiver side and dramatically reduces the peak-to-average power Ratio (PAPR) level at the transmitter side. Simulation results are given to support our claims.

Eigenvalue based detection is one of the most promising blind spectrum sensing techniques in cognitive radio. However, it suffers from computational complexity resulting from sample covariance matrix computation and eigenvalue decom-position. In this paper, we propose a reduced-complexity blind detection algorithm to detect the presence of a main direction in terms of energy. Instead of eigenvalue decomposition, our method is based on a series of beamforming using simple beam patterns to reduce computational complexity. Simulation results show that our method provides acceptable performances compared to the well-known Maximum to Minimum Eigenvalue (MME) method with a considerable gain in computational complexity.

This paper applies a recently proposed efficient technique that has been conducted regarding timing synchronization in OFDM systems, to the IEEE 802.11a/g standards. The time synchronization is fulfilled using the structure specificity of the short training sequence of IEEE 802.11a/g preamble. Two versions of the applied technique are considered: a single-stage brute force approach, which carries differential correlation exclusively, and a two-stage reduced complexity approach comprising coarse and fine stages. The coarse synchronization is achieved using sliding correlation, characterized by its low computational load, whereas the fine synchronization is realized by differential correlation, characterized by its high computational load and carried around the coarse time estimate. In the two stage approach, the combined use of sliding correlation and differential correlation, carried for short interval, results in an overall reduced complexity approach. Simulation results show that, applied in the IEEE 802.11a/g norm, both of the considered approaches provide accurate time synchronization in the AWGN and multipath channels. Moreover, the two-stage version has a low computational load, which makes it suitable for fast symbol timing synchronization in bursty IEEE 802.11a/g OFDM systems.

This paper investigates space-frequency (SF) coding for non-coherent (NC) Multiple Input Multiple Output (MIMO)-Orthogonal Frequency Division Multiplexing (OFDM) fading links, where neither the transmitter nor the receiver knows the channel. Our strategy consists in distributing the convolutional encoded and interleaved bits over the different transmit antennas, OFDM tones and OFDM symbols. The combination of the convolutional coding and bit interleaving with the SF coding can exploit the maximum spatial/frequency diversity over frequency-selective channels. In order to reduce the decoding complexity, we divide the OFDM symbol into several groups and apply differential encoding and decoding between adjacent groups. The proposed NC SF matrix is designed as a combination of a differential Cayley code and a systematic NC SF code, which leads to a simple decoding rule over the multipath channel. We show through asymptotic Pairwise Error Probability (PEP) analysis and simulation results that our encoding strategy can provide full diversity gain and achieves better performance in terms of spectrum efficiency and symbol error rate than all three the systematic NC-SF coding, the Cayley differential SF coding and our proposed SF coding without convolutional encoding and bit interleaving.

In this paper, we propose a novel approach for multiple antenna spectrum sensing based on compressed sensing. Our focus is on the angular sparsity of the received signal given an unknown number of primary user source signals impinging upon the antenna array from different Directions Of Arrival (DOA). Given multiple snapshots over a small time period, multiple measurement vectors are available and a joint sparse recovery is performed to estimate the common sparsity profile over the angular domain. In this estimation process, we employ the regularized M-FOCUSS algorithm [1], which is the noisy multiple snapshot extension of the iterative weighted minimumnorm algorithm, called FOCUSS. The contribution of this paper is to take advantage of the sparse primary user DOA estimation within the detection framework of multiple antenna spectrum sensing. In this scope, an accurate sparse reconstruction is not required and a coarse estimation using a reduced number of snapshots is sufficient to decide about the number of present primary users reflected by the angular sparsity order of the received signal. A simulation study shows significant constant false alarm rate performance gain of the proposed approach compared to the conventional maximum to minimum eigenvalue detector especially when the number of PUs increases.

The universal frequency reuse has been targeted for the Long Term Evolution. It leads to a harmful inter-cell interference experienced notably by the cell-edge users. The uplink inter-cell interference coordination becomes among the most important challenges. Throughout literature, many techniques were proposed to overcome this issue. Among these techniques, the soft frequency reuse concept grasped many attentions. Certainly, it succeeded in reducing the interference for edge-cell users by prohibiting the allocation of the same RB to two users in adjacent cells-edge. However, it presents several drawbacks in terms of spectral efficiency and overloaded cell-edge users. The most proposed approaches are based on this scheme. In this context, this study introduces a novel strategy that will avoid these shortcomings. Our idea aims to optimize the resource block allocation by using the genetic algorithm approach and maximizing channel capacity. We exploit information exchanged over the X2interface. Simulation results show the effectiveness of our proposed approach.

Cognitive radio is a promising technique for efficient spectrum utilization in wireless systems. In this paper, we consider an underlay cognitive radio system where a large number of secondary users (SUs) can share the spectrum with a primary user (UP). We assume that M antennas are used at the cognitive base station (CBS) and the CBS does not have the full channel state information (CSI) from secondary users. We propose to study the problem of secondary users scheduling under the assumption of imperfect CSI of the interference channel between the CBS and the primary receiver. In order to minimize the interference to the UP, we propose to generate orthogonal beams to the estimate of the channel between the CBS and the PU. Then, to reduce the amount of required feedback, we propose a scheduling algorithm based on opportunistic beamforming. To further reduce the amount of feedback, a threshold is applied to the signal to interference and noise ratio (SINR) feedback. For the proposed scheme, we develop a statistical analysis for the interference caused to the PU as well as the throughput of the secondary system.

Cognitive radio is an exciting emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum. Such revolutionary and transforming technology represents a paradigm shift in the design of wireless systems as it will offer the ability of radio sensing, self adaptation and dynamic spectrum sharing. In this paper, we are interested in the case where secondary users are allowed to communicate concurrently with primary users provided that they do not create harmful interference to the licensed users. More precisely, the secondary transmission will depend on a variable cost that reliably quantifies the interference power generated by the secondary user at the primary base stations. Here, we aim to improve the unlicensed system performance in terms of throughput. For this aim, we propose to use an adaptive modulation as well as an energy optimization at the unlicensed user in order to maximize its data rate. We show that the system throughput depends on several parameters such as the maximum allowed cost and the number of base stations in the primary network, the secondary user location and its transmission energy.

In this paper, we develop an energy efficient cross-layer design which optimally combines Adaptive Modulation (AMC) and Coding and Power Control (PC), at the physical layer, with type-I Hybrid Automatic Repeat reQuest (HARQ-I) protocol, at the data link layer. The objective is to maximize the average throughput efficiency under a prescribed average transmit power constraint. We have shown in [7] that the optimum transmission strategy is a function of an unknown parameter, referred to λ, which depends on both the average transmit power and the time-varying channel statistics. Since the channel statistics are a priori unknown at the transmitter, we here recourse to an adaptive algorithm, operating in tracking mode, to estimate and track this parameter. In contrast with our previous work, which relied on a block-fading model, we adopt a time-correlated fading channel model based on the Jakes model. We show that the obtained Monte-Carlo simulation results are in perfect agreement with the numerical results based on a perfect knowledge of λ. The obtained results show a significant performance improvement, with respect to a conventional cross-layer design using exclusively AMC at the physical layer and HARQ-I at the data link layer. More precisely, simulation results show that more than 5 dB gain in average transmit power is achieved for low and high average data rates, and no less than 2 dB for medium average data rates.

Cognitive radio holds tremendous promise for increasing spectral efficiency in wireless systems. In this paper, we consider an underlay cognitive radio system where a large number of secondary users (SUs) can share the spectrum with a primary user (PU). We assume that M antennas are used at the cognitive base station (CBS) and the CBS does not have the full channel state information (CSI) from users. We propose to study the problem of secondary users scheduling under the constraint of interference to the PU while maximizing the throughput of the secondary system. In order to reduce the amount of required feedback, our scheduling algorithm is based on opportunistic beamforming. It consists of two steps. In the first step, the cognitive base station constructs N matrices of M beams. The primary user selects the one which minimizes the interference to itself and sends the index of selected beamforming matrix to the CBS. In the second step, the cognitive users having the highest signal to interference and noise ratios (SINRs) are selected for transmission, which can be done with little feedback. Simulation results show that our algorithm achieves a good tradeoff between interference to the PU and secondary system throughput.

A new Genetic Algorithm (GA) based sequence optimization is here proposed. The studied sequence, which we refer to as Encoding Sequence (ES), is used in a recently proposed OFDM preamble-based synchronization technique. The optimal ES is generated offline by differentially correlating the preamble samples to each other respecting a shift. To determine the frame start at the receiver, the ES is correlated to a version of the received signal generated using differential correlation respecting the same shift as in the ES generation. This treatment, carried online, is of high complexity due to the differential correlation operations. To reduce the computational load at the receiver, the idea here is to replace the differential correlation operations, carried during the synchronization process, by simple sign changes. To this aim, we need to derive the best sub-optimal ES, in terms of providing near optimal performance, from a finite QPSK alphabet (#177;1#177;j). Even if this search procedure is carried off-line, considering an exhaustive search over the whole ES candidates within QPSK alphabet results in a prohibitive complexity. As an alternative, we here suggest to use a GA-based approach. Performance comparison of the proposed ES, generated through GA-based search, to the optimal ES, generated from the preamble, and a previously proposed QPSK ES optimized through an iterative algorithm has been conducted. It is demonstrated that compared to the iteratively generated ES, the herein proposed one improves the detection accuracy. The GA-based provides slightly lower detection accuracy with respect to the optimal ES, yet with important reduction in the receiver complexity.

Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) is a promising modulation scheme for high performance broadband wireless communications that suffers from a major drawback, which is the high Peak-to-Average Power Ratio (PAPR) of the output signals. In this paper, we propose a new blind combined Alamouti Space-Time Bloc Codes (STBC) approach inspired from the Selected Mapping (SLM) process to solve this PAPR issue for MIMO-OFDM systems. Our solution is based on a specific STBC patterns from which we construct precoding sequences forming a codebook that ensures the role of an inherent embedded signaling for the MIMO-OFDM system. Furthermore, in order to efficiently recover the transmitted sequence, we propose a set of decision schemes that banks on the Max-Log-Maximum A Posteriori (MAP) algorithm. To significantly improve the obtained results, we add another embedded signaling through a rotated and unrotated QAM constellation set. Both embedded signallings lead to a combined SLM-Alamouti technique for which we investigate a powerful decision process. We show that our proposed method guarantees a reliable and perfect signal recovery at the receiver side and dramatically reduces the PAPR level at the transmitter side. Simulation results are given to support our claims.

In this paper, we consider the transmission coordination among multiple cell sites, namely the Coordinated MultiPoint (CoMP) transmission scheme, where several Base Stations (BSs) cooperate to serve a set of Mobile Stations (MSs) and both BSs and MSs are equipped with multiple antennas. We model this multicell cooperative system under the presence of channel estimation errors that can significantly influence the obtained results. We derive the exact sum rate expression of the multicell cooperative system in the presence of channel estimation errors and we evaluate the performance of the Block-Diagonalization (BD) and Zero-forcing (ZF) beamforming approaches. Furthermore, we investigate a power allocation policy that maximizes the system sum rate in the presence of channel estimation errors. We show that in the multicell cooperative system, the performance of the BD or ZF beamforming approaches in terms of the maximization of the system sum rate, depends essentially on the system configuration parameters (i.e., number of antennas per BS and per MS). Simulation results are given to support our claims.

In this paper, we analytically study the performance of a recently proposed efficient reduced complexity time synchronization approach for orthogonal frequency division multiplexing systems. This method uses a preamble of two identical parts and proceeds in two stages. In the first stage, the repetitive structure of the preamble is exploited to provide the coarse time estimate respecting the algorithm of Cox and Schmidl. In the second stage, a fine metric, based on differential correlation, is carried over a reduced time window centered on the coarse estimate. We here study the performance of the fine stage, assuming a successful coarse stage whereby the fine search window is centered on the correct frame start. We approximate the fine metric by a Gaussian distribution to derive a closed form expression of the frame start correct detection probability. To this end, a statistical characterization of the fine metric is achieved by its mean and variance computation. Simulations are used to validate the results of the analysis. Indeed, the evaluated rate of correct detection perfectly concords with the theoretical probability in both additive white Gaussian noise and multipath channels.

In this paper, we define a multi-access interference (MAI) cost that can assess the extra interference, inherent to relaying use and perceived by the whole cellular network. This MAI cost shadows an implicit and smart power control for CDMA uplink communications. In fact, this cost takes into account not only the reception quality required at the serving base station but also the global interference generated to all others base stations in the cellular system. Here, the optimization goal aims to enhance the system performance, in terms of Packet-Error-Rate (PER), for a required quality of service (QoS). The optimization approach is achieved for both Decode-and-Forward (DF) and Incremental DF relaying schemes, carried out on packet-by-packet basis. A variety of simulation results are obtained using the analytical expressions of Packet-Error-Probability (PEP) that we derive for both DF and IDF schemes. By way of an example, for a target PER of 10-2, our optimized IDF scheme could afford more than 13 dB gain, in terms of MAI cost reduction, over the direct transmission scheme. Furthermore, simulation results underline that the optimized IDF relaying is more powerful than the optimized DF scheme and provides as much as 3 dB gain for some relay positions.

In this paper we propose a reduced-complexity two-stage time and frequency synchronization approach for OFDM systems, operating in multipath channels. The proposed approach exploits a single-symbol preamble with a repetitive structure, composed of two identical m-sequences. The first coarse stage, based on a sliding correlation, finds out the reduced uncertainty interval over which the second fine stage, based on a differential correlation, is performed. The combined use of the sliding correlation, characterized by its low complexity, and the differential correlation, which is much more complex, carried for a limited number of times results in an overall reduced complexity approach. For the time synchronization, the performance is evaluated in terms of correct detection rate of the frame start and the estimation variance. For the frequency synchronization, we focus on the fractional part of the frequency offset which is evaluated in terms of mean squared error. The simulation results prove that, compared to the considered benchmarks, the accuracy of the frame start detection and the fractional frequency offset estimation are greatly enhanced, even at very low SNRs. The proposed two-stage reduced-complexity approach is also compared to the single-stage brute-force approach, where differential correlation is exclusively used, to assess the performance degradation occasioned by the complexity reduction.

In this paper, we propose a novel approach for cooperative systems performance optimization. We are interested on the uplink CDMA communications, known to be both intra-cell and inter-cell interference limited. More precisely, we define a multi-access interference (MAI) cost that reliably quantifies the additional interference generated by a relayed communication to the whole cellular system. For CDMA uplink communications, this MAI cost hides an implicit and smart power control that takes into account not only the reception quality required at the serving base station but also the interference generated to the whole network. Here, the optimization process aims to improve the system performance, in terms of Packet-Error-Rate (PER) for a certain required quality of service (QoS). The optimization process is carried for both Selective Relaying (SR) and Incremental Selective Relaying (ISR) schemes, on packet-by-packet basis. A variety of simulation results are carried using analytical expressions of Packet-Error-Probability that are derived for SR and ISR schemes. We show that, for a target PER of 10-2, our optimized ISR scheme could provide up to 14 dB gain, in terms of MAI cost reduction, over the direct transmission scheme. Additionally, results highlight that our optimized ISR relaying is always more powerful than the optimized SR scheme and provides as much as 4 dB gain in the most favorable cases.

Recently, the 3rdGeneration Partnership Project has standardized a power control mechanism for the uplink of the Long Term Evolution system. This mechanism is based on the fractional compensation of the pathloss, also known as fractional power control. This approach decreases inter-cell interference but may impact the throughput. In this paper, a novel approach power control will be proposed to avoid such throughput loss. This method still uses fractional power control principle, but differentiates between users generating high interference and users generating low interference. Our simulations indicate that the proposed power control has better performance than the fractional power control.

In this paper, we propose to use the Discrete-Time Rake receiver for Cooperative DS-CDMA systems. We compare the Bit Error Rate (BER) performance of the Continuous Time, Discrete Time and Decorrelating Discrete Time Rake receivers (CTR, DTR, DDTR) using Decode and Forward (DF) relaying. The former receiver is the most used and consists in combining the output of correlators locked on the most significant paths. The DTR consists in a matched filter to the discrete equivalent model of the global channel resulting from the convolution of the impulse response of the transmitter shaping filter and the multipath channel. The DDTR is the optimal implementation of the DTR according to maximum a posteriori criterion.

In this paper, we propose a new scheme for data- aided time and frequency synchronization for OFDM systems, based on a single-symbol preamble. The preamble, of useful length $2^{m}-2$, is composed of two consecutive identical m-sequences (with length $2^{m-1}-1$ each). This preamble is extended by a cyclic prefix of convenient length. This stucture is adequate for a two-stage synchronization scheme, namely a reduced complexity coarse synchronization stage, followed by a finer synchronization one. The first stage, based on Cox and Schmidl-like sliding correlation, determines a reduced uncertainty interval over which the fine stage is carried. The second stage is indeed based on a differential correlation, which is more complex compared to the first stage. The combined use of m-sequences and differential correlation offers an almost perfect peak of the computed metric at the preamble start. To assess the performance degradation occasioned by the reduction of complexity characterizing the proposed two-stage approach, we also consider the brute force single-stage approach, where differential correlation is exclusively used. As a byproduct of our two-stage approach, the fractional frequency offset is estimated and its performance is assessed and compared for both two- stage and one-stage approaches. The brute force approach outperfoms all the considered benchmarks. Compared to the reduced complexity scheme, the brute force one provides similar performance, at the expense of a significant complexity overload. Only for SNR lower than $-5$ dB, the brute force scheme presents a slight enhancement with respect to the reduced complexity one. The simulation results show that the proposed method gives better performance than any other considered estimator. Although our technique is expected to be well suited to multipath channels, thanks to the underlying properties of m-sequences, in this paper we focus on the Additive White Gaussian Noise channel.

This paper deals with the problem of code design for non-coherent frequency-selective Multiple Input Multiple Output (MIMO)-Orthogonal Frequency Division Multiplexing (OFDM) fading links, where neither the transmitter nor the receiver knows the channel. A simple and classical approach for non coherent (NC) coding for MIMO-OFDM system consists of coding across antennas and time slots on each OFDM subcarrier. Only, this approach does not permit to exploit the diversity of frequency-selective channels. In our aim to exploit this diversity, we propose in this paper a strategy that consists of coding across antennas and OFDM subcarriers (space-frequency coding) within a single OFDM symbol. Our space-frequency (SF) codes are based on NC Grassmann space-time (ST) codes obtained via an exponential map from coherent ST codes. We determine the asymptotic Pairwise Error Probability (PEP) for each scheme in order to evaluate the diversity and the coding gains. Simulations show that compared with the classical approach, our NC-SF codes can get more diversity gain and better symbol error performance.

In this paper, we evaluate the root mean square error (RMSE) performance of MUSIC ("Multiple Signal Classification") and COMET ("COvariance Matching EsTimator") algorithms in the presence of dispersion in azimuth and elevation. We use a 3D hemishperoid scattering model to describe angle of arrival in azimuth and elevation. We derive a closed- form expression for the joint and marginal probability density function (PDF) of the uplink angle of arrival (AOA) in azimuth and elevation. The base station is elevated to support the macrocellular model where the scatterers are distributed about the mobile (MS). We also compare the PDF of AOA and the simulated histogram.

In order to enhance soft-handover performance in the downlink of DS-CDMA systems, we propose to use different codes at the base stations in the active set to encode the information sequence targeted to a mobile station. For reliable information recovery, in case all links except one happen to be simultaneously in deep fade, self-decodable complementary punctured convolution codes, inspired from Hybrid ARQ III, are used. When turbo-decoding is feasible at the mobile station, new complementary codes, using different interleavers followed by a common systematic recursive convolutional encoder, are proposed for an additional enhancement in performance. Experimental evaluation of the enhancement in performance provided by complementary coding is carried for both Gaussian and multipath Rayleigh fading channels. The proposed coding schemes can provide very significant gains. In some cases, gains around 4 dB can be achieved.

Mobile wave propagation undergoes severe distortions caused by inter symbol interference (ISI) and inter carrier interference (ICI), which are due to multipath and high mobility. OFDM/BFDM techniques have a good ability to overcome ISI limiting quality effects whereas ICI can be increased for severe Doppler spreading. In this paper, we study the use of well localized time-frequency pulse shaping to reduce the effect of these interferences. The linear combination of several of the first most localized Hermite waveforms enables the design of an optimal transmit/receive pulse. By subtracting the interferences coming from some neighborhood symbols that will be treated by a partial equalization scheme, considerable gain in the signal to interference ratio (SIR) is achieved. With a reduced complexity OFDM system, partial equalization of the interference coming from 2-frequency neighbor symbols results in a gain of about 20 dB in the SIR, at high spectral efficiency and severe channel spreading. More gain in the desired ratio is achieved by optimizing the time-frequency spacing of the underlying lattice.

In this paper, we consider a cooperative network with one source, one destination and two relays to bring cooperative diversity. We assume the link between the source and the destination is so bad that we do not consider it. We propose a decode-and-forward (DAF) strategy based on the Alamouti space-time (ST) code. The two relays must recover the transmitted sequence and forward it to the destination. We consider fast time varying channels between the cooperative users and the destination and our objective is to estimate these two channels in order to recover the information sequence at the destination. We propose a data-aided decision-directed Maximum A Posteriori (MAP) iterative channel estimation algorithm. It can profit from an optimum initialization by means of the MAP data-aided channel estimation. Besides, we adapt this iterative receiver to the case where the destination is equipped with two receive antennas to bring more diversity. The validity of the proposed algorithms is highlighted by simulation results.

In this paper, we consider a pulse shaping OFDM/BFDM system operating over a doubly dispersive channel. We propose to search the optimal pulse maximizing the signal to interference ratio (SIR). We show that the impact of interference, composed by both inter-symbol interference (ISI) and inter-carrier interference (ICI), occurring in such a system, depends crucially on time frequency localization of transmit and receive pulses. We propose to maximize the SIR, written as a ratio of two quaternary forms, by altering between transmit and receive pulse spaces both generated by Hermite Waveforms. Numerical results show that optimized BFDM systems can outperform conventional OFDM systems with respect to SIR. In fact, biorthogonality offers more freedom to design pulses improving robustness of the multi-carrier system against channel dispersion.

In this paper, we consider the problem of maximum a posteriori (MAP) equalization of the received signal over a frequency selective channel when the channel is not perfectly known at the receiver. The derivation of the MAP criterion in this case leads to an expression for which no exact implementation exists in the literature. In this paper, we propose to solve the problem by using the expectation-maximization (EM) algorithm. The algorithm we propose has linear-time complexity per iteration. Simulations show that few iterations are required to reach the performance of the MAP equalizer with perfect channel knowledge.

In this paper, we introduce the generalized decorrelating discrete-time RAKE receiver (GD-DTR) for single antenna systems and extend it to multi-antenna (e.g. MIMO) systems. The GD-DTR benefits from the correlated nature of multiple access interference while being robust against channel estimation errors. It is a combination of two other advanced RAKE reception methods namely, the discrete-time version of the generalized RAKE (G-RAKE) receiver and the decorrelating discrete-time RAKE receiver (D-DTR). The G-RAKE was proposed for correlated interference mitigation. The D-DTR improves performance in the presence of channel estimation errors in diffuse channels. Our results show that the performance of the discrete-time G-RAKE (G-DTR) could be worse than a conventional discrete-time RAKE receiver (C-DTR) when there are channel estimation errors in the system. Unlike G-DTR, our proposed GD-DTR provides gains up to 0.7 dB at a raw bit error rate of 10-2in the presence of channel estimation errors compared to C-DTR. For the MIMO case, the gain of the MIMO GD-DTR compared to MIMO C-DTR are 1 dB and 1.1 dB at a raw bit error rate of 10-2in 2 transmit 2 receive antenna (2times2) and 3times3 systems respectively, if there is no correlation between the antennas. For a highly correlated receive antenna case, the gain increases to 4 dB.

A novel transmit power control (TPC) bit estimation technique for FDD-UMTS downlink is proposed. Conventional FDD-UMTS downlink TPC bit estimation algorithm is based on coherent detection, which utilizes pilot bits for channel estimation and uses this estimate to remove the wireless channel effect on TPC bits. However, joint utilization of pilot and TPC bits can improve the detection performance as well as minimize the inherent overhead caused by excessive pilot bits usage in the transmission. In the proposed algorithm, pilot and TPC bits are used collectively for non-coherent detection of the power control command. Power increase and decrease orders are represented by two orthogonal vectors which are made up of pilot and TPC bits. TPC bit error rate (BER) performance comparisons of conventional and proposed algorithms are presented for various multi-path channels and slot formats. It is shown that in all the slot formats and different channel conditions, the proposed algorithm provides superior performances in terms of TPC bit error rate. This performance gain can go up to 15 dB at practical TPC BER (10-2) with certain channel conditions and slot formats.

In this paper, we study the performance of ARQ, HARQ I and HARQ II with code combining in the presence of feedback errors over multipath block fading channels. The performance of HARQ schemes in the presence of coded feedback is also investigated. In addition, it is shown that the derived analytical results are in excellent agreement with those obtained by computer simulations

The paper compares the BER performance of the continuous time, discrete time and decorrelating discrete time Rake receivers (CTR, DTR and DDTR). The former receiver is the most used and consists in combining the output of correlators locked on the most significant paths. The DTR consists in a matched filter to the discrete equivalent model of the global channel resulting from the convolution of the multipath channel with the transmitter shaping filter. The DDTR is an optimum structure of the DTR according to the maximum a posteriori criterion

We derive a low complexity turbo-detector for coded asynchronous DS-CDMA over frequency selective channels. Our detector is a suboptimal variant of the MAP algorithm based on state-reduction and per-survivor processing. In order to reduce the loss due to state-reduction, we propose to use, as a prefilter for the turbo-detector, a multidimensional whitened matched filter (WMF) which leads to a white-noise "minimum phase" channel model. Simulation results show that the use of the WMF yields significant improvement. Thanks to the iterative turbo processing (detection and decoding are iterated several times), the performance loss due to the use of the suboptimum List-type equalizer is in part recovered.

In this paper, we investigate the optimisation of the loop filter for delay tracking loops in direct sequence spread spectrum systems. We search for a good trade-off between reducing noise effects and having a sufficiently reactive loop. This study is done on both the initial tracking phase, where the loop must compensate acquisition errors, and the permanent one, where the loop must follow delay evolutions.

Due to power control delay, the received power can fluctuate between the instant when it is measured and the instant when the power control command is applied at the transmitter. We propose to predict the received power by taking into account the possible variation of both the transmitter power and path amplitudes.

In this letter, we propose to assess the extra power needed in wide band code division multiple access (WB-CDMA) systems due to perfect power control. First, we derive analytically the expression of the average of this extra power. Then we study its evolution with respect to the number of paths, their average power and their delay spacing.

We investigate the optimisation of the random access channel (RACH) of the UMTS FDD system in terms of generated interference. Conditional on open loop measurements, we search the best initial energy of the RACH in order to reduce the multiple access interference while keeping a reasonable mean access time.

In this paper, a maximum likelihood delay acquisition algorithm is proposed. It consists in minimising the mean square error between the received signal and an estimated one based on a number of paths and a set of delay hypotheses. Unlike the conventional acquisition algorithm, the proposed approach is able to detect, with high probability, paths with delays as close as one fourth of the chip period.

We propose an optimum turbo channel estimation algorithm for OFDM systems on highly selective fading channels. This algorithm performs an iterative estimation of the multiplicative fading channel according to the maximum a posteriori criterion. It requires a convenient representation of the highly time and frequency selective fading channel based on the Karhunen-Loeve expansion theorem. It also optimally takes into account the coded structure of the data symbols in the estimation process thanks to the Bahl (1974) algorithm.

A discrete time implementation of the RAKE receiver (DTR) is proposed. The suggested approach works without knowledge of the path delays and their number. It is based on a global estimation of the multipath channel convolutioned with the shaping filter. Since the DTR performance is very sensitive to the channel estimation quality, we suggest a disregarding method for the least significant estimated channel coefficients while taking into account the known impulse response of the shaping filter. The performance of the DTR and the conventional RAKE are then compared.

We propose a new approach to study the performance of coherent and noncoherent delay lock loop in the AWGN channel. The analytical expression of the mean square tracking error is derived for the coherent scheme and compared to the noncoherent one. The impact of acquisition errors and the effect of the early late gate spacing are also investigated.

We consider block and convolutional codes for improving the reliability of data transmission over the binary precoded noisy (1-D) partial response channel. We concentrate on a class of codes for which the maximum likelihood decoder, matched to the encoder, precoder, and the channel has the same trellis structure as the encoder. Thus, doubling the number of states due to the channel memory is avoided, We show that the necessary and sufficient condition to belong to this class is that all codewords be of the same parity. The Reed-Muller and Golay codes belong to this class.