The precise and accurate indoor positioning using cellular communication technology remains to be a prerequisite for several industrial applications, including the emergence of a new topic of Integrated Sensing and Communication (ISAC). However, the frequently occurring Non-Line-of-Sight (NLoS) conditions in a heavy multipath dominant industrial scenario challenge the wireless signal propagation, leading to abnormal estimation errors (outliers) in the signal measurements taken at the receiver. In this paper, we investigate the iterative positioning scheme that is robust to the outliers in the Time of Arrival (ToA) measurements. The Iteratively Reweighted Least Squares (IRLS) positioning scheme formulated on the Least Squares (LS) is implemented to reject the outlier measurements and reweight the available ToA samples based on their confidence. Our positioning scheme is validated under 5G frequency bands, including the C-band (3.7 GHz) and the mmWave-band (26.8 GHz) in a Ray-Tracing enabled industrial scenario with different emulation setups.

Reducing latency in Time-Sensitive Networking (TSN) networks is critical to fulfil real-time communication requirements, ensuring timely data delivery, and maintaining system responsiveness. Minimizing latency enhances the reliability of industrial automation, multimedia streaming, and other time-critical applications, ultimately optimizing overall network performance and user experience. One of the most critical points lies in the wireless segments, which cannot be considered as deterministic. Specially, when the traffic load between uplink and downlink is unbalanced, it is critical to allocate resources based on the volume of such traffic and on the channel state, both significantly impacting on packet latency. In this paper we present and compare a set of approaches to scheduling time slots within a wireless frame for communication between the uplink (UL) and downlink (DL) in a TSN network. The primary objective is to reduce latency in wireless transmissions, particularly in scenarios with stringent timing requirements. By optimizing the allocation of time slots between UL and DL, our proposed scheduling algorithm aims to minimize queueing delays while ensuring efficient utilization of network resources. The results highlight the significant reduction achieved in terms of queueing latency and packet loss through our scheduling strategy, thereby enhancing the reliability and timeliness of wireless links in TSN networks.

The 5th generation (5G) and beyond network offers substantial promise as the ideal wireless technology to replace the existing inflexible wired connections in traditional factories of today. 5G network slicing allows for tailored allocation of resources to different network services, each with unique Quality of Service (QoS) requirements. This paper presents a novel solution for slice-aware radio resource allocation based on a convex optimisation and control framework for applications in smart factory wireless networks. The proposed framework dynamically allocates minimum power and sub-channels to downlink mixed service type industrial users categorised into three slices: Capacity Limited (CL), Ultra Reliable Low Latency Communication (URLLC), and Time Sensitive (TS) slices. Given that the base station (BS) has limited transmission power, we enforce admission control by effectively relaxing the target rate constraints for current connections in the CL slice. This rate readjustment occurs whenever power consumption exceeds manageable levels. Simulation results show that our approach minimises power, allocates sub-channels to users, maintains slice isolation, and delivers QoS-specific communications to users in all the slices despite time-varying number of users and changing network conditions.

As the number of wireless technologies (4G, 5G, 802.11ax and other) have been rapidly increasing, so have the number of wireless networks concurrently deployed on a given coverage area. As a result, the judicious selection of the network that maximizes the quality perceived by a user terminal has become a significantly relevant problem. Contextual Multi-Armed Bandits (CMAB) are viable models to approach the problem. While multiple CMAB algorithms have been designed, most of them are only suited for stationary environments. This work proposes a new set of network selection algorithms that relate the traffic type (used as contextual information) to the perceived quality of the available networks for non-stationary scenarios. Results show significantly improved performance when compared to non-adaptive approaches.

Receive spatial modulation (RSM) has been proposed as an effective transmission technology for next-generation wireless communications systems because of its reduced complexity and low energy consumption at the receiver end. Compared to conventional multiple-input multiple-output (MIMO) transceivers, which require one radio-frequency (RF) chain and analog-to-digital converter (ADC) per receive antenna, RSM can be implemented with one amplitude detector per antenna and a single RF chain, with mild performance degradation in terms of spectral efficiency (SE). However, its implementation using zero-forcing precoders is inadequate in mmWave channels due to the lack of propagation scattering and, hence, rank deficiency in the channel matrix. This has been only partially solved in the past using receiver antenna selection (RAS), which requires additional receive antennas. On the other hand, using reconfigurable intelligent surfaces (RIS), which can effectively create scatter and enhance the channel matrix rank, is an affordable solution that can also cope with shadowing situations and the higher path losses associated with mmWave bands. We propose using a RIS in a single-user MIMO communication with RSM to improve the downlink transmission. This paper shows that RIS-assisted RSM communication is more than a good option in mm Wave channels in terms of bit error rate due to the multipath induced in the channel and the link budget boosting.

Managing a massive number of terminals in a contention-based multiple access is challenging due to its intrinsic limited efficiency. For example, in the random access channel considered in LTE-A and 5G NR, Base Station (BS) is just aware of the collided and non-collided preambles. Several time-based protocols have been investigated to redistribute the overload under high terminal activity, thus avoiding the congestion. In this work, we explore the use of the spatial domain by means of a hierarchical codebook-based beamforming, where the BS selects the appropriate beams as a function of the number of non-collided and collided preambles. Since the activity and placement of terminals may be dynamic over time, the sequential selection of parameters can benefit from a reinforcement learning (RL) framework. We propose an algorithm that can exploit both domains, temporal and spatial, with the goal of reducing collisions and enhancing transmission delay. Our approach is able to efficiently learn whenever there is a non-homogeneous spatial distribution of terminals and adapt the spatial beams accordingly.

We consider a point to point large-scale multipleinput multiple-output (MIMO) system operating in the millimeter wave (mmWave) band and an outdoor scenario. Novel transmit and receive spatial modulation (SM) schemes are proposed for uplink (UL) and downlink (DL) data transmission phases based on a novel energy efficient hybrid user terminal architecture. The analog circuitry of the proposed hybrid architecture is divided into two stages: phase shifters and analog switches. The phase shifting stage assures high gain and overcomes the severe path-loss caused by outdoor mmWave propagation. The analog switching stage smartly allocates the antennas to be used at the phase shifting stage and combats the spatial correlation. We provide the analysis of the spectral efficiency (SE) of the UL and DL systems. Next, we propose a reduced complexity algorithm that jointly optimizes the analog beamformer and combiner design of the UL and DL circuitry to maximize the energy efficiency (EE). Finally, we compare and evaluate the performance of the proposed algorithm in terms of the SE and EE assuming both stochastic and realistic channel models.

In this paper, we consider the downlink of a multi-user multiple-input-multiple-output system operating at the millimeter wave band in an outdoor environment. In this band, receive spatial modulation (RSM) schemes have been shown to achieve good spectral efficiency-energy consumption trade-off for the single-user case by exploiting new transceiver architectures that use a single radio-frequency (RF) chain at the user terminal (UT). In this work, we propose a novel RSM scheme for multiple RF chains at the UT. With the goal of maximizing the spectral efficiency (SE), we consider analog switches at the UT that select which antennas are active. To minimize the power consumption at the BS, we include analog switches that control the ON/OFF status of RF chains such that the SE is higher than a given threshold. Moreover, we extend the RSM concept to multiple users transmission. Specifically, we propose an algorithm that jointly optimizes the number of users, set of antennas and transmit power allocated to each user to maximize the sum SE. Simulation results show that RSM outperforms conventional modulation (no spatial symbols are transmitted) in terms of spectral and energy efficiency. Moreover, the proposed algorithms tightly approach the exhaustive search and outperform the prior art in terms of performance and convergence.

Orthogonal Frequency Division Multiplexing (OFDM)-based networks rely on time synchronization to obtain their best performance. Time synchronization with neighboring nodes can be satisfied by increasing the cyclic prefix (CP) length (at the expenses of spectral efficiency reduction) We show that by optimizing the transmit pre-compensation and receive post-compensation we can meet the time synchronization constraints and keep the CP at its minimum value. This concept is applied to paired-bands Frequency Division Duplexing (FDD) systems which tend to show inefficient occupancy of the uplink (UL)-band due to the traffic asymmetry. We consider the possibility of deploying multiple Time Division Duplexing (TDD) small eNBs (SeNBs) in the unused UL spectrum. In this scenario, time synchronization with macro eNB (MeNB) and neighboring SeNBs becomes essential. Two algorithms are proposed in order to ensure orthogonality of OFDM transmissions network-wide.

In this paper, we consider the downlink of a massive multiple-input-multiple-output (MIMO) single user transmission system operating in the millimeter wave outdoor narrowband channel environment. We propose a novel receive spatial modulation architecture aimed to reduce the power consumption at the user terminal, while attaining a significant spectral efficiency and low bit error rate. The energy consumption reduction is obtained through the use of analog devices(amplitude detector), which reduces the number of radio frequency chains and analog-to-digital-converters (ADCs). The base station transmits spatial and modulation symbols per channel use. We show that the optimal spatial symbol detector is a threshold detector that can be implemented by using one bit ADC. We derive closed form expressions for the detection threshold at different signal-to-noise-ratio (SNR) regions. We derive expressions for the average bit error probability in the presence and absence of the threshold estimation error showing that a small number of pilot symbolsis needed. A performance comparison is done between the proposed system and fully digital MIMO showing that a suitable constellation selection can reduce the performance gap.

This paper develops and evaluates precoding techniques for coordinated joint transmission in visible light communications (VLC). A multi-user multiple-input single-output (MISO) setup is adopted. Transmitters are equipped with light emitting diode (LED) arrays, while receivers incorporate a single photodetector (PD). We design zero forcing (ZF) linear precoders considering, as figure of merit, the weighted sumrate for multilevel pulse amplitude modulation (PAM) and take into account the optical power constraints. We present two approaches. First, we formulate the design as a convex optimization problem and find its exact solution. Second, by considering certain approximations, we find an alternative precoder that despite being suboptimal can be computed in an almost closed-form, achieving a good trade-off between performance and complexity. Finally, we demonstrate that the proposed approaches largely outperform the conventional pseudo-inverse precoding and single-user TDMA approaches.

New short-length single-direction frame structures are proposed for 5G time division duplex (TDD) systems, where the transmit direction [i.e., either downlink (DL) or uplink (UL)] can be independently chosen at each cell in every frame. Accordingly, high flexibility is provided to match the per-cell DL/UL traffic asymmetries and full exploitation of dynamic TDD is allowed. As a downside, interference management becomes crucial. In this regard, this paper proposes a procedure for dynamic TDD in dense multiple-input multiple-output small cell networks, where the transmit direction selected per small cell (SC) is dynamically optimized together with the user scheduling and transmit precoding. We focus on the maximization of a general utility function that takes into account the DL/UL traffic asymmetries of each user and the interference conditions in the network. Although the problem is non-convex, it is decomposed thanks to the interference-cost concept and then efficiently solved in parallel. Simulation results show gains in DL and UL average rates for different traffic asymmetries and SC/user densities as compared to existing dynamic TDD schemes thanks to the proposed joint optimization. The gains become more significant when there is high interference and limited number of antennas.

This paper proposes a joint user scheduling and transmit direction selection procedure for dynamic TDD in 5G dense small cell networks, where the transmit direction (i.e. downlink (DL) or uplink (UL)) selected per small cell is dynamically optimized together with the user scheduling at every frame. We focus on the maximization of a general utility function that takes into account the DL/UL traffic asymmetries of each user and the interference conditions in the network. After relaxation of the integer variables that subsume the user scheduling and transmit direction selection, the problem is decomposed and efficiently solved in parallel at every frame. Simulation results show significant gains in DL and UL average rates for different traffic asymmetries, network densities, and user densities as compared to existing schemes for dynamic TDD.

This paper presents long-term resource provisioning schemes for dense multi-cell OFDMA-based networks, where multiple cells with possibly overlapping coverage areas compete for the same set of resources. The optimization is done over the long term, being independent of the specific users connected to each cell but dynamic enough to follow significant variations of the traffic load. In this sense, we focus on the average resource utilization (RU) and propose schemes to minimize the maximum RU of all cells. Firstly, we consider orthogonal resource usage among cells. Optimal closed-form expressions for the long-term resource provisioning are derived for this case. Secondly, we assume that resources can be reused at non-overlapping cells. In this case, the resource provisioning is solved in two steps: i) the number of resources required per cell is obtained by discretizing the optimal solution of a convex problem, and then ii) the specific resources to be utilized by each cell are determined by using graph coloring. In contrast to previous works, graph coloring can be applied to get an implementable solution for any condition of the cell loads. Simulation results show a significant reduction of the maximum RU, which translates into an increase of the served traffic and a reduction of the packet delay, as compared to static resource provisioning schemes.

We propose a novel stochastic radio resource allocation strategy for the uplink that achieves long-term fairness in terms of similar bitrates considering backhaul and air-interface capacity limitations. We focus on a single cell scenario based on WCDMA technology. We propose to use a maximin criteria to introduce fairness among the different users' throughputs. An stochastic approximation is implemented to obtain an online algorithm where the Lagrange multipliers are estimated at each scheduling period. Our results show that the proposed scheme achieves higher fairness among the users and, in some cases, a higher sum-rate compared with the well-known proportional fair scheduler.

Recent results have elucidated the benefits of using improper Gaussian signaling (IGS) as compared with conventional proper Gaussian signaling (PGS) in terms of achievable rate for interference-limited conditions. This paper exploits majorization theory tools to formally quantify the gains of IGS along with widely linear transceivers for multiple-input multiple-output (MIMO) systems in interference-limited scenarios. The MIMO point-to-point channel with interference is analyzed, assuming that received interference can be either proper or improper, and we demonstrate that the use of the optimal IGS when received interference is improper strictly outperforms (in terms of achievable rate and mean square error) the use of the optimal PGS when interference is proper. Then, these results are extended to two practical situations. First, the MIMO Z-interference channel (Z-IC) is investigated, where a trade-off arises: with IGS, we could increase the achievable rate of the interfered user while gracefully degrading the rate of the non-interfered user. Second, these concepts are applied to a two-tier heterogeneous cellular network where macrocells and small cells coexist and multiple MIMO Z-ICs appear.

The degrees of freedom (DoFs) of the K-user multiple-input multiple-output (MIMO) interference channel are studied when perfect, but delayed channel state information is available at the transmitter side (delayed CSIT). Recent works have proposed schemes improving the DoF knowledge of the interference channel, but at the cost of developing transmission involving many channel uses (long delay), thus increasing the complexity at both transmitter and receiver side. This paper proposes three linear precoding strategies, limited to at most three phases, based on the concept of interference alignment, and built upon three main ingredients: delayed CSIT precoding, user scheduling, and redundancy transmission. In this respect, the interference alignment is realized by exploiting delayed CSIT to align the interference at the non-intended receivers along the space-time domain. Moreover, a new framework is proposed where the number of transmitted symbols and duration of the phases is obtained as the solution of a maximization problem, and enabling the introduction of complexity constraints, which allows deriving the achievable DoF as a function of the transmission delay, i.e., the achievable DoF-delay trade-off. Finally, the latter part of this paper settles that the assumption of time-varying channels common along all the literature on delayed CSIT is indeed unnecessary.

This paper addresses distributed interference management in downlink of multi-cell multiple- input multiple-output (MIMO) time division duplex (TDD) networks. Each user is associated with a user-centric cluster of base stations (BSs), which cooperatively serve the user through CoMP joint transmission. Clusters of different users possibly share some BSs such that they may overlap, being coupled by interference and transmit power constraints at each BS. Our objective is the design of BSs clustering and precoding matrices per-user in order to maximize the weighted sum-rate of the system by controlling the interference and the power spent at BSs. In contrast to previous works where all channel matrices in the system are needed, we propose a distributed procedure whereby only channel matrices towards a limited number of candidate BSs per user are required while interference is still controlled by using the signal received from an uplink transmission. For an LTE-compliant dense deployment of 2×2 MIMO BSs/users, results show gains of 6-16% in terms of sum-rate and 49-84% in terms of 5%-tile per-user rate (depending on the maximum cluster size) as compared to distributed BS-disjoint clustering schemes.

Self-organizing network is a new capability envisioned for the near-future wireless cellular networks. Among the different use cases, here we tackle the coverage optimization with the objective of adjusting the power devoted for the pilot signal as a function of the load of the different small Node Bs (SNBs). The optimization is done with the objective of minimizing the total transmitted power for the pilot signals in the network, leading to a switch on/off SNBs solution as a particular case. In this paper we present a decentralized algorithm that is executed at UEs and SNBs, exploiting the messages reported by UEs.

Retrospective Interference Alignment is a linear precoding strategy that seizes delayed channel state information at the transmitters (CSIT), improving the degrees of freedom (DoF) that can be achieved without CSIT for both the broadcast and interference channels. However, little is known for other channel configurations. This work studies the multiple-input multiple-output interference broadcast channel (IBC) with delayed CSIT, 2 cells and 2 users per cell. Although some of the schemes designed for other channels may be applied, they do not exploit the specific topology of the IBC. In this regard, we proposes a precoding strategy that includes the concept of redundancy transmission, and takes into account that users of each cell are served by a common transmitter. Assuming that transmitters and receivers are equipped with M, N antennas, respectively, state-of-the-art achievable DoF are improved for ρ = M over N > ρA, with ρA≈ 3.5414.

Cellular networks need the densification of small eNBs (SeNBs) to face the tremendous data traffic demand growth, implying an interference increase and making transmit coordination a key enabler. This article proposes a decentralized coordinated precoding (D-CoP) for downlink (DL) weighted sum-rate maximization in dense MIMO TDD small cell networks (SCNs). Each SeNB designs its own precoding matrices based on channel state information (CSI) of the served users and knowledge of the interference-cost matrix that allows managing interference towards unintended users. A protocol is proposed to acquire the interference-cost matrix by processing the uplink (UL) received signal provided that: (1) channel reciprocity can be assumed and (2) all users participating in DL can transmit in UL with an adequate transmit filter. In contrast to existing transmit coordination techniques, D-CoP is fully scalable, avoids estimation of the interfering channels, and does not require information exchange between SeNBs. In case all parameters are perfectly acquired, an iterative algorithm is presented with demonstrated monotonic convergence when all SeNBs update its transmit precoders simultaneously. Further, the problem is reformulated in order to derive a robust D-CoP under imperfect CSI conditions. Finally, simulations in 3GPP LTE-Advanced SCNs show significant user packet throughput gains, without increasing the complexity associated to transmit coordination. Robustness to imperfect CSI and non-ideal channel reciprocity is shown through simulations.

A precise knowledge of the MIMO channel between the serving node and the user equipment (UE) is important for attaining good data rates in downlink transmissions (DL) in cellular systems. The interfering point-to-multipoint (I-P2MP) channel, consisting of multiple transmitters coexisting in the same area, where each transmitter is intended to serve multiple users, is a model that subsumes most of the scenarios that can be found in wireless cellular networks with a dense deployment of small cells (SCs). In conventional channel estimation procedures, resources allocated to each SC for training tend to be orthogonal, negatively impacting in the efficiency of the whole system. Reusing resources for training allows releasing resources for data transmission, but at the cost of degrading the channel estimation due to interference. We propose a decentralized algorithm for interference management that enforces the coordination among SCs in the design of the training sequences for de DL. Results in this work elucidate how to reuse resources for training and significantly improve the throughput of the system.

The optimal transmission scheme for a multiple-input multiple-output point-to-point channel (MIMO-P2P) is dependent on the type of received interference, which can be either proper or improper. We will show that the presence of improper interference is beneficial in terms of improving the achievable rate compared to a case with proper interference. These benefits are due to using widely linear precoder and receiver. Additionally, we investigate a cellular scenario where two types of users are coexisting, ones that are receiving proper interference while others which might be receiving improper interference, trying to devise the best transmission scheme to be adopted. We propose an improper Gaussian signaling-based scheme that allows controlling system performance and fairness in terms of bitrate through a single parameter.

This work investigates the degrees of freedom (DoF) of the K-user multiple-input single-output (MISO) interference channel (IC) with imperfect delayed channel state information at the transmitters (dCSIT). For this setting, new DoF inner bounds are provided, and benchmarked with cooperation-based outer bounds. The achievability result is based on a precoding scheme that aligns the interfering received signals through time, exploiting the concept of Retrospective Interference Alignment (RIA). The proposed approach outperforms all previous known schemes. Furthermore, we study the proposed scheme under channel estimation errors (CEE) on the reported dCSIT, and derive a closed-form expression for the achievable DoF with imperfect dCSIT.

The degrees of freedom (DoF) of the 3-user multiple input multiple output interference channel (3-user MIMO IC) are investigated where there is delayed channel state information at the transmitters (dCSIT). We generalize the ideas of Maleki et al. about Retrospective Interference Alignment (RIA) to be applied to the MIMO IC, where transmitters and receivers are equipped with (M, N) antennas, respectively. We propose a two-phase transmission scheme where the number of slots per phase and number of transmitted symbols are optimized by solving a maximization problem. Finally, we review the existing achievable DoF results in the literature as a function of the ratio between transmitting and receiving antennas ρ = M/N. The proposed scheme improves all other strategies when ρ ∈ (1/2, 31/32].

We consider a system where multiple users are connected to a small cell base station enhanced with computational capabilities. Instead of doing the computation locally at the handset, the users offload the computation of full applications or pieces of code to the small cell base station. In this scenario, this paper provides a strategy to allocate the uplink, downlink, and remote computational resources. The goal is to improve the quality of experience of the users, while achieving energy savings with respect to the case in which the applications run locally at the mobile terminals. More specifically, we focus on minimizing a cost function that depends on the latencies experienced by the users and provide an algorithm to minimize the latency experienced by the worst case user, under a target energy saving constraint per user.

The degrees of freedom (DoF) of the 3-user multiple-input multiple-output (MIMO) interference channel (IC) with full channel state information and constant channel coefficients are investigated when (p,p+1) antennas are deployed at the transmitters and receivers, respectively. The point of departure of this paper is the work of Wang et al., which conjectured but did not prove the DoF for the antenna settings with p>1. Here the achievability of the DoF outer bound is formally proved using linear methods, thereby avoiding the use of the rational dimensions framework. The proposed transmission scheme exploits asymmetric complex signaling together with symbol extensions in time and space interference alignment concepts. While the paper deals with the p=2,3,\ldots,6 cases, providing the specific transmit and receive filters, there are also provided the tools needed for proving the achievability of the optimal DoF for p>6, whose DoF characterization is conjectured.

This paper proposes distributed inter-cluster interference management procedures for 1 Coordinated Multi-Point (CoMP) Time Division Duplexing (TDD) cellular networks, in which a set of base stations (BSs), that form a cluster, cooperate in the downlink (DL) and uplink (UL) transmissions to communicate with a group of users while causing interference to users in neighbor clusters. In order to reduce the complications associated to the estimation of the interfering channels, we describe new iterative procedures based on channel reciprocity that avoid such estimation by exploiting the received signal in the UL, provided that transmit and receive filters in DL and UL are properly designed. Simulations show that proposed techniques attain significant DL and UL spectral efficiency gains. Furthermore, an analysis of imperfect channel state information (CSI) at both ends is included, evidencing the robustness of the proposed procedures. Considerations on convergence are included.

The multiple-input multiple-output (MIMO) X channel with rank-deficient channels is considered. We characterize the total degrees of freedom (DoF) by defining an outer bound which is attained by the proposed precoding scheme. The total DoF are described in closed-form when all transmitters and receivers have M and N antennas, respectively. For an arbitrary number of antennas, the total DoF are obtained as solution of a linear programming problem. Results elucidate that, unlike point-to-point MIMO systems where DoF increase with the rank of the channel, the total DoF in a multipoint-to-multipoint MIMO system can increase up to a certain point if channels are rank-deficient. Hence, we corroborate the relevance of knowing the rank-deficiency in the MIMO X channel, a property already observed in the MIMO Interference channel.

This paper proposes a decentralized algorithm for interference coordination in LTE-A networks, based on the exchange of information (pricing) at control plane level. In our approach, every user equipment (UE) report the maximum modulation and coding scheme (MCS) that can be used within several sets (sub-bands) of available resource blocks, along with a parameter (cost) that measures the MCS degradation due to the transmission from an interfering neighbor. Through the exchange of pricing messages, the higher costs are distributed to the dominant interferers; and the selection of the MCS and operational sub-band is based on the current link conditions along with the received pricing messages. We evaluate the algorithm in a cellular area covered by a macro base station (MBS) and multiple active femtocells. We also measure the degradation due to the quantization of the exchanged cost values. The results demonstrate significantly enhanced performance as compared to the non-coordinated case.

A relay station (RS)-based cellular system deployment is considered, where multiple base stations (BS) cooperate in the BS-RS in-band transmission for the downlink. With the joint optimization of the resources allocated to the wireless backhaul and to the RS-MS access, it is possible to exploit the benefits of networked-MIMO along with combating the pathloss and shadowing effects, and thus obtain significantly enhanced spectral efficiency and coverage homogeneity. The problem is shown to be convex under conventional QoS objective functions. Suboptimal low complexity solutions are also proposed and evaluated.

We derive a linear transmit precoding scheme based on interference alignment at the transmitters and zero-forcing at the receivers, for the MIMO X channel based on the Generalized Singular Value Decomposition (GSVD) that is able to attain the outer bound on the degrees of freedom (DoF) region for any antenna configuration, except when all terminals have one antenna. Additionally, the proposed scheme is able to enhance the transmission rate in terms of high SNR offset.

Recent results elucidate the optimality of the interference alignment concept in attaining the degrees of freedom of the MIMO X channel. However, in the low-medium SNR regime optimizing the weighted sum-rate seems more meaningful. Since the MIMO X channel subsumes the MIMO interference channel, MIMO multiple access, parallel MIMO point-to-point and MIMO broadcast channel, it is desirable to have a procedure that designs the linear transmitters and receivers in all cases. In this work we have observed that an algorithm based on alternate optimization, along with the proper initialization, is able to provide MMSE precoders attaining the degrees of freedom and significant gains in terms of SNR offset with respect the conventional interference alignment solution.

This work looks into the extension of the proportional fair (PF) scheduler to the multi-user case, where the source is transmitting several messages under the superposition coding (SC) strategy in a Gaussian Broadcast channel. Jointly with the weighted sum-rate (WSR) scheduling criterion, we derive guidelines for 2-user pairing, based both on SNR and user priority. We compare superposition coding access with frequency division multiple access, while time division is obtained naturally as a result of the user pairing. Results elucidate that the 2-user SC PF always improves the single-user PF in terms of average throughput and delay reduction, and we compare its performance with the 3-user SC PF. Finally, the WSR shows throughput gains similar to the 2-user SC PF for certain configuration of the scheduler.

The computation of the channel capacity of discrete memoryless channels is a convex problem that can be efficiently solved using the Arimoto-Blahut (AB) iterative algorithm. However, the extension of this algorithm to the computation of capacity regions of multiterminal networks is not straightforward since it gives rise to non-convex problems. In this context, the AB algorithm has only been successfully extended to the calculation of the sum-capacity of the discrete memoryless multiple-access channel (DMAC). Thus, the computation of the whole capacity region still requires the use of computationally demanding search methods. In this paper, we first give an alternative reformulation of the capacity region of the DMAC which condenses all the non-convexities of the problem into a single rank-one constraint. Then, we propose efficient methods to compute outer and inner bounds on the capacity region of the two-user DMAC by solving a relaxed version of the problem and projecting its solution onto the original feasible set. Targeting numerical results, we first take a randomization approach. Focusing on analytical results, we study projection via minimum divergence, which amounts to the marginalization of the relaxed solution. In this case we derive sufficient conditions and necessary and sufficient conditions for the bounds to be tight. Furthermore, we are able to show that the class of channels for which the marginalization bounds match exactly the capacity region includes all the two-user binary-input deterministic DMACs as well as other non-deterministic channels. In general, however, both methods are able to compute very tight bounds as shown for various examples.

The two-way relay channel (TWRC) describes the communication between two terminals sharing a common relay. In this work we compare different protocols for the TWRC with a half-duplex relay (forwarding and protocol I) and transmission schemes (network coding relaying with random binning and XOR precoding), when the relay works in decode-and-forward and without channel state information at the transmitters. We provide the optimal resource allocation (in terms of phase duration, data rate and power allocation) when there is an individual or sum-average power constraint over the terminals. Closed-form solutions are derived whenever it is possible, while for others cases we show that the resource allocation can be formulated as a convex problem, which means that the solution can be obtained by low-complexity interior point methods.

Automatic repeat request (ARQ) protocols deal with the situations where the selected data rate is not supported by the current channel realization. The inappropriate selection is motivated by the limited channel state information at the transmitter (CSIT). This work looks into how the ARQ protocols are applied to the half-duplex relay-assisted transmission with decode-and-forward relays by exploiting the ACK feedback channel of the terminals. Two implementations are tackled: 1) only the source or 2) source and relay manage the retransmissions under the pure-ARQ protocol. This work presents an analytical framework for the comparison of both options. The study allows the optimization of the bitrate and amount of resource allocated for the relay transmission phases.

The performance characterization of decentralized wireless networks with uncoordinated sender-destination pairs motivates the study of the totally asynchronous interference channel with single-user receivers. Since this channel is not information stable, its capacity region is determined resorting to information density, although more amenable single-letter inner and outer bounds are provided as well. Aiming at numerical evaluation of the achievable rates, we subsequently concentrate on the inner bound for the Gaussian case. We show that taking Gaussian inputs is not the best choice in general and derive analytical conditions under which other input distributions may be optimal. Essentially, these conditions require the channel to be interference-limited. Finally, the existence of such non-Gaussian distributions with superior performance is validated numerically in different scenarios.

Under limited channel state information at the transmitter the communication suffers from the outage events produced by a data rate selection not supported by the current channel realization. Automatic repeat request (ARQ) protocols are a useful tool to deal with those outage events in delay-tolerant services. This work looks into how automatic repeat request (ARQ) protocols are applied to the half-duplex relay-assisted transmission with a decode-and-forward (DF) relay. The exploitation of ACK feedback channels from destination and relay leads to two possible implementations: 1) only-source manages the retransmission procedure or 2) both source and relay control the retransmissions. We analyze both options under a chase-combining ARQ protocol with limited number of transmission rounds, providing integral expressions for the throughput. This study allows the optimization transmission rate and the amount of resources allocated for the relay transmission.

This paper addresses the design of joint multi-cell resource allocation and scheduling with coordination among neighboring base stations (BS). Considering Nsneighboring sectors, the solution that maximizes the sum-rate in the covered area is found for TDMA and TDMA/OFDMA access. The optimum solution exhibits low complexity as it presents the useful property that its computation admits a decomposition such that each BS is responsible for the selection of the users to be scheduled in its own sector. This result is proved analytically.

While the capacity region of the discrete memoryless broadcast channel is in general unknown, it admits a computable single-letter characterization when it is degraded. In this case, we pose its computation as an optimization problem and analyze its structure. We show that the computation of the capacity region of the two-user discrete memoryless degraded broadcast channel can be characterized as a difference of convex optimization problem, a non-convex problem in general. For this problem, which cannot be solved optimally in polynomial time, we obtain necessary conditions for optimality which substantially reduce the set of potential capacity-achieving candidate distributions. As an application of this result, the capacity region of the BEC-BSC degraded broadcast channel is derived by maximizing the achievable rates over this set of reduced dimensionality.

In this paper, the achievable rate of a K-user interference channel with single antenna at individual node is studied. Interference alignment and zero forcing are applied at the transmitter and receiver, respectively. It is well known from the paper [1] of Cadambe and Jafar that a multiplexing gain (degrees of freedom) of K/2 is achievable. We propose two new pre-coding methods and study how they enhance the achievable rate in terms of the high SNR offset, while maintain the optimality of degree of freedom the Cadambe-Jafar scheme achieved.

Cooperative transmission has emerged as an effective tool to deal with channel impairments. In this work we study the applicability of amplify-and-forward cooperative transmission in the downlink of a TDMA cellular system where idle terminals act as relays. The base station may have a multiple antenna configuration, whereas all terminals are equipped with a single antenna. Although cooperation can be viewed as a virtual MIMO system, it further allows dealing with shadowing and pathloss. In order to improve the spectral efficiency loss incurred by the half-duplex relays, in this work we consider the reuse of the relay time slot by simultaneous transmissions from the active relays in the cell. We are able to model the interfering power received by each destination in that slot. The only system parameters adjusted to control the interference are the number of interfering relay terminals and a cell-wide .target SNR in the relay-destination link. This way, it is shown that cooperative transmission is able to provide significant gains in terms of throughput over the direct transmission under round-robin packet scheduling and uniform distribution of terminals by controlling the rate of each transmission (rate control).

The compress-and-forward (C&F) cooperative relaying strategy is known to outperform decode-and-forward (D&F) when the relay is close to the destination. In this paper, we derive achievable rates on Gaussian vector channels with cooperative C&F relaying. In order to extend previous information-theoretic results from the scalar to the vector Gaussian channel, we exploit recent results in distributed source coding. Like in source coding with side information at the decoder, the relay applies a conditional Karhunen Loeve transform (CKLT) to its observed signal, followed by a separate Wyner-Ziv encoding of each output stream with a different rate and under a sum-rate constraint. However, these Wyner-Ziv coding rates are such that the total mutual information between the source and destination is maximized. This differs from the conventional source coding approach in which the rates are selected to minimize the total squared distortion, leading to the well-known reverse-waterfilling algorithm. We show that the maximization of the C&F mutual information is also a convex problem. The optimum Wyner-Ziv coding rates have a simple analytical expression, and can be obtained by a waterfilling algorithm. Finally, we illustrate these results by simulations of MIMO-OFDM relaying in a system similar to IEEE802.16.

The computation of the channel capacity of discrete memoryless channels is a convex problem that can be efficiently solved using the Arimoto-Blahut (AB) iterative algorithm. However, the extension of this algorithm to the computation of capacity regions of multiterminal networks is not straightforward since its computation gives rise to non-convex problems. In this context, the AB algorithm has been only successfully extended to the calculation of the sum-capacity of the discrete memoryless multiple-access channel. However, the computation of the capacity region still requires the use of computationally demanding random search algorithms or brute force (full search) methods. In this paper, we first give an alternative reformulation of the problem that identifies the non-convexity as a rank-one constraint. We then propose an efficient algorithm to compute outer and inner bounds on the capacity region by relaxing the original problem and then by projecting the relaxed solution onto the original space variable via a minimum divergence criterion. There exists a class of channels for which the proposed algorithm can be shown to compute exactly the capacity region. As an illustration, we analyze two particular channels, the binary adder MAC and the binary switching MAC, in detail. In the general case, the algorithm is able to compute very tight bounds as shown by simulation.

This work explores ways to boost the spectral efficiency of transmission schemes based on amplify-and-forward (AF) cooperation. While AF has usually been considered to suffer from bandwidth expansion due to the increased use of transmission resources, in a multiuser environment it is possible to overcome this limitation by either spatially reusing the transmissions from different relay terminals, or by using multiple relays. These two possibilities are not mutually exclusive and are studied below in the context of TDMA transmissions for the downlink. It is shown that under mild assumptions the interference generated during the relay transmission phases can be statistically modeled. The outage events generated by this interference are mitigated by an adaptive transmission rate scheme that maximizes the system throughput. This low complex implementation of multiuser AF provides significant throughput gains over a conventional TDMA non-cooperative scenario.

Cooperative transmission has emerged as an effective tool to combat fading by improving the diversity gain. Although this technique can be viewed as a "virtual" MIMO system, when implemented under orthogonal access it does not allow multiplexing gains. In this work we have studied a possible application of the cooperative transmission in a TDMA centralized cellular system in the downlink. In order to reduce the inefficiency, we have considered the spatial reuse of one relay slot by simultaneous active relays in the cell. To this end we have modeled the interfering power received by each destination in the relay link. It is shown that cooperative transmission with amplify and forward strategy is able to provide significant throughput gains for user-relaying over the direct transmission under TDMA

The main difficulty for the location of terminals in wireless communications systems is the non line of sight (NLOS) situation caused by obstacles in the transmitted signal path, between the base stations and the user equipment. This NLOS situation biases TDOA measures, resulting in a biased final position. However, not all of the base stations may be in NLOS. Determining which base stations are in LOS can improve the accuracy of the system. It is feasible to estimate the reliability of the measures through the study of signal parameters like the delay spread, received power or previous position estimates. The objective of this paper is to analyze the improvements in positioning accuracy by tracking the terminal with an unscented Kalman filter (UKF) incorporating knowledge of NLOS-LOS situation. The evaluation of the approach has been carried out with measures taken in real scenarios.

This paper deals with the design of non-regenerative relays in cooperative transmission schemes. The conventional nonregenerative approach is the amplify and forward (AF) approach, where the signal received at the relay is simply amplified and retransmitted. In this paper, we propose an alternative design which maximizes the capacity for nonregenerative cooperative transmission, when channel state information is available at the relay station. Therefore, the relay units are not simple amplify and forward units, but still they are not required to demodulate or remodulate the symbols transmitted by the base station as in regenerative relaying schemes. We compare the performance so obtained with the performance for the conventional AF approach, and also with the performance of regenerative relays and direct noncooperative transmission.

Broadcast transmission mode in ad hoc networks is critical to manage multihop routing or providing medium access control (MAC)-layer fairness. In this paper, it is shown that a higher capacity to exchange information among neighbors may be obtained through a physical-MAC cross-layer design of the broadcast protocol exploiting signal separation principles. Coherent detection and separation of contending nodes is possible through training sequences which are selected at random from a reduced set. Guidelines for the design of this set are derived for a low impact on the network performance and the receiver complexity.

An iterative game theory based algorithm is proposed to allocate the resources in cooperative schemes for the downlink. Both amplify-and-forward (AF) and decode-and-forward (DF) cooperative schemes are considered with cellular reuse of the relay slot. Multiple antennas can be used at the involved stations. Using the algorithm proposed, the simultaneous relay powers are decided in a decentralized way using mean channel level measures and mean values of noise and interference power. The cell capacity gain for the cooperative schemes using the decentralized algorithm is evaluated by means of simulation for both the AF and DF approaches.

Broadcast transmission mode in ad hoc networks is critical to supporting probing and routing procedures. In this paper, we present a novel topology-transparent protocol for broadcasting, which guarantees a minimum average throughput per neighbour. The scheme follows a physical-MAC cross-layer design based on retransmission combining. MAC layer performance is analysed. Coherent detection and separation of contending nodes is possible through training sequences which are selected at random from a reduced set. Guidelines for the design of this set are derived for a low impact on network performance and receiver complexity.

The main impairment for the location of terminals in a wireless communications system is the non-line-of-sight (NLOS) condition which is mainly due to blocking of the transmitted signal by obstacles. It is well known that NLOS biases time-of-arrival (TOA) and time-difference-of-arrival (TDOA) estimates, therefore providing a biased position. The paper analyzes the improvements in positioning accuracy by tracking the bias of the time measures with the Kalman filter proposed for location estimation. The evaluation of the approach has been carried out with measures taken in real scenarios, for positioning techniques based on TDOA and TOA+AOA (angle of arrival) measurements.

The performance of downlink coded cooperative transmission in mobile communication systems is evaluated. Cooperative transmission is seen as a "virtual" MIMO system where multiple transmit antennas are provided by a relay station and the base station, and different space-time block coding schemes are considered. Regenerative and non-regenerative systems are considered for the cooperative schemes. The use of rate compatible puncture turbo codes as forward error correction codes allow the system to be tested under the hybrid-type II automatic repeat request protocol. Results in terms of throughput show the benefits of coded cooperation over direct transmission.

Recent information-theoretic work has shown the potential capacity increase of multiple-input multiple-output (MIMO) systems compared to single-input single-output (SISO) systems. The singular value decomposition (SVD) has proven very useful in MIMO communication systems but its performance depends on the accuracy of the channel state information (CSI) at both sides of the link. This paper presents a study on the influence of channel estimation errors and noise on the probability of error of the system when no error correction mechanisms are provided.

This paper deals with the problem of nonline-of-sight (NLOS) in wireless communications systems devoted to location purposes. It is well known that NLOS biases time of arrival (TOA) and time difference of arrival (TDOA) estimates thus reducing accuracy of positioning algorithms. In order to achieve positioning error reduction the Kalman filter proposed for location estimation includes the time measurement bias for each base station (BS) as additional parameters to be estimated. The use of the Kalman filter allows then tracking, not only the position and speed of the mobile, but also the bias due to NLOS, yielding an accurate location prediction algorithm.

A particular property of the matched desired impulse response receiver is introduced, namely, the fact that full exploitation of the diversity is obtained with multiple beamformers when the channel is spatially and timely dispersive. This particularity makes the receiver specially suitable for mobile and underwater communications. The new structure provides better performance than conventional and weighted VRAKE receivers, and a diversity gain with no need for additional radio frequency equipment. The baseband hardware needed for this new receiver may be obtained through reconfigurability of the RAKE architectures available at the base station. The proposed receiver is tested through simulations assuming UTRA frequency-division-duplexing mode.

The objective of this paper is to determine the potentialities of an optimal detection scheme within the framework of mobile location. A method for detecting the first arriving path from a multipath environment as a mean of enhancing subscriber location is described. A binary hypothesis test is performed, some expressions for Constant False Alarm Rate (CF AR) detectors are derived and their performances are evaluated for different configurations. The use of Generalized Likelihood Ratio Test (GLRT) is also commented and some preliminary results are shown.

The objective of this paper is to determine the potentialities of an optimal detection scheme within the framework of subscriber location. The use of a generalized likelihood ratio test (GLRT) for detecting the first arriving path from the estimated channel observations in a multipath environment in severe NLOS conditions is described, and a high-resolution estimation algorithm for the time of arrival (TOA) is presented. Finally, the scheme performance is evaluated for different configurations.

A potentiality of the location problem in wireless networks that has not been explored enough is the mobility of the user equipment (UE). This paper deals with UMTS mobile location tracking using Kalman filtering based on TDOA (time difference of arrival) measurements. The performance of the proposed approach is compared with the CRB (Cramer Rao bound) for the static location estimator.

This paper deals with the problem of estimating the position of a user equipment operating in a wireless communication network. We present a new positioning method based on the angles of arrival (AOA) measured in several radio links between that user equipment and different base stations. The proposed AOA-based method leads us to a non-iterative closed-form solution of the positioning problem, and an statistical analysis of that solution is also included. The comparison between this method and the classical AOA-based positioning technique is discussed in terms of computational load, convergence of the solution and also in terms of the bias and variance of the position estimate.

In a wireless communication network, the position estimation of a given user equipment is usually obtained by the combination of angle and delay measurements of one or more radio links between that user equipment and one or several base stations. This paper focuses on the performance of an approximate maximum likelihood position estimator in the presence of non-zero cross-correlations between measurements. This issue becomes specially relevant in hybrid positioning techniques because angles and delays of the same radio link are combined and, in consequence, the usual assumption of uncorrelation between measurements does not hold.

A new time variant wideband propagation channel model is presented for user location applications in third generation mobile environments. The model considers evolutionary angle of arrival (AOA) and evolutionary time of arrival (TOA), based on the real instantaneous relative user equipment and base station position. The channel model proposed is used also in a link level simulator (LLS) to estimate realistic delay and angle of arrival coherence time, that is, the time in which position and time delay and angle of arrival for the received signal remain almost constant. In order to increase the time integration period and consequently reduce the error in geographical positioning, the maximum coherence time has to be known in the time delay and angle estimating process. The new wideband propagation channel model will provide the delay and angle estimating process with realistic coherence time and Doppler spread. The model also provides spatial correlation matrices for different diversity base station (BS) antenna schemes and compares them with experimental results.

The well-known structure of an array combiner along with a maximum likelihood sequence estimator (MLSE) receiver is the basis for the derivation of a space-time processor presenting good properties in terms of co-channel and intersymbol interference rejection. The use of spatial diversity at the receiver front-end together with a scalar MLSE implies a joint design of the spatial combiner and the impulse response for the sequence detector. This is faced using the MMSE criterion under the constraint that the desired user signal power is not cancelled, yielding an impulse response for the sequence detector that is matched to the channel and combiner response. The procedure maximizes the signal-to-noise ratio at the input of the detector and exhibits excellent performance in realistic multipath channels.

This work concentrates on the problem of watermarking embedding and optimum detection in color images through the use of spread spectrum techniques both in space (Direct Sequence Spread Spectrum or DSSS) and frequency (Frequency Hopping). It is applied to RGB and opponent color component representations Perceptive information is considered in both color systems. Some tests are performed in order to ensure imperceptibility and to assess detection quality of the optimum color detectors.

The use of spatial diversity at the receiver front-end together with a sequence detector implies a joint design problem of the spatial combiner and the sequence detector impulse response. This joint design is usually faced under the constraint that the impulse response of the sequence detector is matched to the channel plus combiner response. This procedure maximizes the signal to noise ratio at the input of the detector but does not guarantee that the so-called effective signal to noise ratio is maximized. This work presents a procedure that, starting from the matched criteria, faces directly the maximization of the effective signal to noise ratio, yet preserving all the features of the spatial processor in terms of co-channel and high order intersymbol interference rejection.

This work concentrates on the problem of watermarking of still images using the luminance component, through the use of spread spectrum techniques, both in space (direct sequence spread spectrum or DSSS) and frequency (frequency hopping or FH), following the guidelines of Delaigle et al. (1998). The system described is able to embed watermarks and recover them with zero probability of error. The problem is faced from a statistical detection point of view through the analysis of the density function of the image to be marked. A Cauchy model is found to be very accurate and some tests are performed in order to assess improved detection quality. The resulting system turns out to be easy to encrypt and very robust to filtering and JPEG compression.

The use of spatial diversity at the receiver front-end together with a sequence detector implies a joint design problem of the spatial combiner and the sequence detector impulse response. This joint design is usually faced under the constraint that the impulse response of the sequence detector is matched to the channel and combiner response. This procedure maximizes the signal to noise ratio at the input of the detector but, as it is well known, this does not guarantee a minimum probability of error, which is more related to the so-called effective signal to noise ratio. This work presents a procedure that, starting from a simple structure for the space-time receiver aims directly at the maximization of the effective signal to noise ratio, yet preserving all the features of the spatial processor in terms of co-channel and high order intersymbol interference rejection.

In this paper, the occupancy of the HMM states is modeled by means of a Markov chain.A linear estimator is introduced to compute the probabilities of the Markov chain.The distribution functions OF) represents accurately the observed data.Representing the DF as a Markov chain allows the use of standard HMM recognizers.The increase of complexity is negligible in training and strongly limited during recognition.Experiments performed on acousticphonetic decoding shows how the phone recognition rate increases from 60.6 to 61.1.Furthermore, on a task of database inquires, where phones are used as subword units, the correct word rate increases from 88.2 to 88.4.

Multiuser detection in code division multiple access systems usually requires either knowledge of the transmitted signature sequences and channel state information or use of a known training sequence for adaptation. We develop a scheme that can be employed for the joint adaptive blind multiuser identification and detection in asynchronous CDMA systems. This scheme relies on a multiuser Viterbi algorithm that incorporates an adaptive estimation of the overall channel impulse responses, given by the convolution of the signature sequences of the users and corresponding physical channels impulse responses. Once the overall channel responses are estimated, the blind multiuser detection algorithm performs like the maximum-likelihood sequence estimator. Results are provided to illustrate the convergence of the blind multiuser approach, near-far resistance and sensitivity to the algorithm initialization.

The problem of recognition in noisy environments is addressed. Often, a recognition system is used in a noisy environment and there is no possibility of training it with noisy samples. Classical speech analysis techniques are based on second-order statistics and their performance dramatically decreases when noise is present in the signal under analysis. New methods based on higher order statistics (HOS) are applied in a recognition system and compared against the autocorrelation method. Cumulant-based methods show better performance than autocorrelation-based methods for low SNR.

The paper applies the theory of hidden Markov models (HMM) in digital communications to obtain a complete characterization of the channel, convolutional code, and transmitted constellation in a blind environment, i.e., without the help of a training sequence. The HMM formulation leads to a joint maximum likelihood estimation of both the channel and the transmitted sequence. The Baum-Welch (BW) identification algorithm is able to estimate all the parameters of the model, including the constellation and the probability of each symbol. Minor modifications to the algorithm allow one to consider restrictions or known parameters to improve the estimation of the rest of parameters with methods of lower complexity. An LMS-type adaptive version of the BW algorithm is also developed and tested. The simulation results show the fast convergence of the proposed optimal approaches. They also demonstrate that the performance of the decoder is comparable to that obtained in a known environment.>

Many linear methods have been proposed in the literature to blindly estimate the ARMA parameters of a time series using HOS. Nevertheless, they are mainly off-line and not much has been done in the adaptive case. The method proposed in this contribution is the adaptive version of the w-slice method. The recursion is based on the inversion lemma when attempting the solution of an undetermined matrix equation. The system impulse response can be recovered regardless of the ARMA or MA character of the system. The number of operations depends on the square of the system order and it is considerably reduced with respect to previous approaches. Application to channel deconvolution is shown.>

A general linear approach to identifying the parameters of a moving average (MA) model from the statistics of the output is developed. It is shown that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. This result is then used to obtain a new well-conditioned linear method to estimate the MA parameters of a nonGaussian process. The proposed approach does not require a previous estimation of the filter order. Simulation results show improvement in performance with respect to existing methods.>

The problem of estimating the autoregressive (AR) parameters of a causal AR moving average (ARMA) (p,q) process using higher-order statistic is addressed. It is shown that there is always a linear combination of p+1 slices that gives a full-rank Toeplitz matrix. This derivation proves that consistent estimates can always be obtained with this set of p+1, 1-D slices. These results lead to the development of a new adaptive lattice algorithm with improved performance. Some results are presented comparing this scheme with previous algorithms based on a single slice. Estimation of the MA parameters of the obtained AR-compensated sequence completes the identification of the system. As this method is based on cumulants, the estimation will be unbiased, even in the presence of colored Gaussian noise.>