We consider a rate-splitting multiple access (RSMA) assisted dual-functional integrated sensing and communications (ISAC) system, where the ISAC base station (BS) has the dual capability to simultaneously communicate with downlink users and to probe detection signals to a target. For this system, we focus on the problem of energy efficiency (EE) maximization and propose a new algorithmic framework that aims to optimize the beamforming matrices of RSMA such as to maximize the EE. Our framework is applicable to the optimization of both common and private streams’ beamforming matrices, and it accounts for a variety of constraints which includes power consumption constraint, communication rate constraints and a sensing quality constraint which is expressed with the aid of Cramér-Rao bound (CRB). Finally, the performance of our framework is compared to that of SDMA and NOMA based ISAC, and the superiority of RSMA-ISAC to SDMA-ISAC and NOMA-ISAC is revealed.

This work investigates the performance of intelligent reflective surfaces (IRSs) assisted uplink nonorthogonal multiple access (NOMA) in energy-constrained networks. Specifically, we formulate and solve two optimization problems; the first aims at minimizing the sum of users’ transmit power, while the second targets maximizing the system-level energy efficiency (EE). The two problems are solved by jointly optimizing the users’ transmit powers and the beamforming coefficients at the IRS, subject to the users’ individual uplink rate and transmit power constraints. A novel and low-complexity algorithm is developed to optimize the IRS beamforming coefficients by optimizing the objective function over the complex circle manifold (CCM). To efficiently optimize the IRS phase shifts over the manifold, the optimization problem is reformulated into a feasibility expansion problem which is reduced to a max-min signal-to-interference-plus-noise ratio (SINR). Then, with the aid of a smoothing technique, the exact penalty method is applied to transform the problem from constrained to unconstrained. The proposed solution is compared against three semi-definite programming (SDP)-based benchmarks which are semi-definite relaxation (SDR), SDP-difference of convex (SDP-DC) and sequential rank-one constraint relaxation (SROCR). The results show that the manifold algorithm provides better performance than the SDP-based benchmarks, and at a much lower computational complexity for both the transmit power minimization and EE maximization problems. The results also reveal that IRS-NOMA is only superior to orthogonal multiple access (OMA) when the users’ target achievable rate requirements are relatively high.

This paper proposes a framework for designing robust precoders for a multi-input single-output (MISO) system that performs integrated sensing and communication (ISAC) across multiple cells and users. We use Cramer-Rao-Bound (CRB) to measure the sensing performance and derive its expressions for two multi-cell scenarios, namely coordinated beamforming (CBF) and coordinated multi-point (CoMP). In the CBF scheme, a BS shares channel state information (CSI) and estimates target parameters using monostatic sensing. In contrast, a BS in the CoMP scheme shares the CSI and data, allowing bistatic sensing through inter-cell reflection. We consider both block-level (BL) and symbol-level (SL) precoding schemes for both the multi-cell scenarios that are robust to channel state estimation errors. The formulated optimization problems to minimize the CRB in estimating the parameters of a target and maximize the minimum communication signal-to-interference-plus-noise-ratio (SINR) while satisfying a given total transmit power budget are non-convex. We tackle the non-convexity using a combination of semidefinite relaxation (SDR) and alternating optimization (AO) techniques. Simulations suggest that neglecting the inter-cell reflection and communication links degrades the performance of an ISAC system. The CoMP scenario employing SL precoding performs the best, whereas the BL precoding applied in the CBF scenario produces relatively high estimation error for a given minimum SINR value.

The polarization domain provides an extra degree of freedom (DoF) for improving the performance of multiple-input multiple-output (MIMO) systems. This paper takes advantage of this additional DoF to alleviate practical issues of successive interference cancellation (SIC) in rate-splitting multiple access (RSMA) schemes. Specifically, we propose three dual-polarized downlink transmission approaches for a massive MIMO-RSMA network under the effects of polarization interference and residual errors of imperfect SIC. The first approach implements polarization multiplexing for transmitting the users’ data messages, which removes the need to execute SIC in the reception. The second approach transmits replicas of users’ messages in the two polarizations, which enables users to exploit diversity through the polarization domain. The third approach, in its turn, employs the original SIC-based RSMA technique per polarization, and this allows the BS to transmit two independent superimposed data streams simultaneously. An in-depth theoretical analysis is carried out, in which we derive tight closed-form approximations for the outage probabilities of the three proposed approaches. Accurate approximations for the ergodic sum-rates of the two first schemes are also derived. Simulation results validate the theoretical analysis and confirm the effectiveness of the proposed schemes. For instance, under low to moderate cross-polar interference, the results show that, even under high levels of residual SIC error, our dual-polarized MIMO-RSMA strategies outperform the conventional single-polarized MIMO-RSMA counterpart. It is also shown that the performance of all RSMA schemes is impressively higher than that of single and dual-polarized massive MIMO systems employing non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) techniques.

Aiming at overcoming practical issues of successive interference cancellation (SIC), this paper proposes a dual-polarized rate-splitting multiple access (RSMA) technique for a downlink massive multiple-input multiple-output (MIMO) net-work. By modeling the effects of polarization interference, an in-depth theoretical analysis is carried out, in which we derive tight closed-form approximations for the outage probabilities and ergodic sum-rates. Simulation results validate the accuracy of the theoretical analysis and confirm the effectiveness of the proposed approach. For instance, under low to moderate cross-polar interference, our results show that the proposed dual-polarized MIMO-RSMA strategy outperforms the single-polarized MIMO-RSMA counterpart for all considered levels of residual SIC error.

In this work, we study the trade-off between the reliability and the investment cost of an unmanned aerial system (UAS) consisting of a set of unmanned aerial vehicles (UAVs) carrying radio access nodes, called portable access points (PAPs)), deployed to serve a set of ground nodes (GNs). Using the proposed algorithm, a given geographical region is equivalently represented as a set of circular regions, where each circle represents the coverage region of a PAP. Then, the steady-state availability of the UAS is analytically derived by modelling it as a continuous-time birth-death Markov decision process (MDP). Numerical evaluations show that the investment cost to guarantee a given steady-state availability to a set of GNs can be reduced by considering the traffic demand and distribution of GNs.

This work proposes a framework to design a cost-efficient unmanned aerial vehicle (UAV)-based energy-neutral (EN) system deployed to harvest data from a set of internet-of-things (IoT) nodes. The energy-neutrality refers to the zero-sum balance between energy harvested, stored, and consumed during operation, which is a game-changer when a connection to the electricity grid is not available/feasible. This involves employing an off-grid charging station (CS) comprising of photovoltaic (PV) panels and batteries that provide enough energy to recharge the UAV-based aerial access points (AAPs). The investment cost is determined by the number of AAPs, PV panels, and ground battery units. Its minimization cannot be achieved using conventional optimization tools due to the non-tractable form of the CS load. Therefore, a novel wave-based method is proposed to represent the load profile as a proportional function of the required number of AAPs, so as to directly relate the CS design to the trajectory optimization. Compared to baseline scenarios, the proposed trajectory design can halve the time and energy consumption; the investment cost varies with the time and season of service; the off-grid CS is particularly advantageous in rural areas, while in urban areas its cost is comparable to that of a grid-connected alternative.

Radio-frequency wireless energy transfer (RF-WET) is emerging as a potential green enabler for massive Internet of Things (IoT). Herein, we analyze channel state information (CSI)free multiantenna strategies for powering wirelessly a large set of single-antenna IoT devices. The CSI-free schemes are AASS (AA-IS), where all antennas transmit the same (independent) signal(s), and SA, where just one antenna transmits at a time such that all antennas are utilized during the coherence block. We characterize the distribution of the provided energy under correlated Rician fading for each scheme and find out that while AA-IS and SA cannot take advantage of the multiple antennas to improve the average provided energy, its dispersion can be significantly reduced. Meanwhile, AA-SS provides the greatest average energy, but also the greatest energy dispersion, and the gains depend critically on the mean phase shifts between the antenna elements. We find that consecutive antennas must be π-phase shifted for optimum average energy performance under AA-SS. Our numerical results evidence that correlation is beneficial under AA-SS, while a greater line of sight (LOS) and/or the number of antennas is not always beneficial under such a scheme. Meanwhile, both AA-IS and SA schemes benefit from small correlation, large LOS, and/or a large number of antennas. Finally, AA-SS (SA and AA-IS) is (are) preferable when devices are (are not) clustered in specific spatial directions.

A dual-polarized intelligent reflecting surface (IRS) can contribute to a better multiplexing of interfering wireless users. In this paper, we use this feature to improve the performance of dual-polarized massive multiple-input multiple-output (MIMO) with non-orthogonal multiple access (NOMA) under imperfect successive interference cancellation (SIC). By considering the downlink of a multi-cluster scenario, the IRSs assist the base station (BS) to multiplex subsets of users in the polarization domain. Our novel strategy alleviates the impact of imperfect SIC and enables users to exploit polarization diversity with near-zero inter-subset interference. To this end, the IRSs are optimized to mitigate transmissions originated at the BS from the interfering polarization. The formulated optimization is transformed into quadratically constrained quadratic sub-problems, which makes it possible to obtain the optimal solution via interior-points methods. We also derive analytically a closed-form expression for the users’ ergodic rates by considering large numbers of reflecting elements. This is followed by representative simulation examples and comprehensive discussions. The results show that when the IRSs are large enough, the proposed scheme always outperforms conventional massive MIMO-NOMA and MIMO-OMA systems even if SIC error propagation is present. It is also confirmed that dual-polarized IRSs can make cross-polar transmissions beneficial to the users, allowing them to improve their performance through diversity.

In this paper, we propose a novel successive sub-array activation (SSAA) diversity scheme for a massive multiple-input multiple-output (MIMO) system in combination with non-orthogonal multiple access (NOMA). A single-cell multi-cluster downlink scenario is considered, where the base station (BS) sends redundant symbols through multiple transmit sub-arrays to multi-antenna receivers. An in-depth analytical analysis is carried out, in which an exact closed-form expression for the outage probability is derived. Also, a high signal-to-noise ratio (SNR) outage approximation is obtained and the system diversity order is determined. Our results show that the proposed scheme outperforms conventional full array massive MIMO setups.

In this paper, we propose an energy-efficient optimal altitude for an aerial access point (AAP), which acts as a flying base station to serve a set of ground user equipment (UE). Since the ratio of total energy consumed by the aerial vehicle to the communication energy is very large, we include the aerial vehicle's energy consumption in the problem formulation. After considering the energy consumption model of the aerial vehicle, our objective is translated into a non-convex optimization problem of maximizing the global energy efficiency (GEE) of the aerial communication system, subject to altitude and minimum individual data rate constraints. At first, the non-convex fractional objective function is solved by using sequential convex programming (SCP) optimization technique. To compare the result of SCP with the global optimum of the problem, we reformulate the initial problem as a monotonic fractional optimization problem (MFP) and solve it using the polyblock outer approximation (PA) algorithm. Numerical results show that the candidate solution obtained from SCP is the same as the global optimum found using the monotonic fractional programming technique. Furthermore, the impact of the aerial vehicle's energy consumption on the optimal altitude determination is also studied.

The use of Massive MIMO and Millimeter-wave (mmWave) networks can be beneficial for a number of Fixed Wireless Access use cases, such as Smart City (SC) Services, providing connectivity for SC infrastructure, and Fixed Wireless Access using street-level distribution and access via so-called "street furniture" equipment. In this paper, we present the findings from a mmWave channel measurement campaign performed in different indoor and outdoor scenarios as part of our contribution to the mmWave Network Project Group of the Telecom Infra Project see (https://telecominfraproject.com/mmwave/). Indoor scenarios included workspace environments such as office rooms, corridors, etc. whereas, outdoor scenarios included urban and suburban environments. A set of two 802.11ad TerragraphTM Channel Sounder nodes (provided by Facebook under TIP) equipped with massive MIMO antenna arrays were used as the transmitter and the receiver for the characterization of the 60GHz mmWave channel. The measurement results include path loss, received power, input and output SNR and delay spread values for each specified beam combination. Urban, suburban and indoor environments were tested in both Line of Sight (LoS) and Non-Line of Sight (N-LoS) configurations.

In this paper, we propose a novel successive sub-array activation (SSAA) diversity scheme for a massive multiple-input multiple-output (MIMO) system in combination with non-orthogonal multiple access (NOMA). Considering a single-cell multi-cluster downlink scenario, where the base station (BS) sends redundant symbols through multiple transmit sub-arrays to multi-antenna receivers, a low-complexity two-stage beamformer, that is constructed based only on the long-term channel statistical information, is proposed. An in-depth analytical analysis is carried out, in which an exact closed-form expression for the outage probability is derived. A high signal-to-noise ratio (SNR) outage approximation is obtained and the system diversity order is determined. The ergodic sum-rate is also investigated, in which a closed-form solution is evaluated considering a particular case. Numerical and simulation results are provided to validate the analytical analysis and to demonstrate the performance superiority of the proposed SSAA scheme. For example, our results show that the proposed system operating with SSAA outperforms conventional full array massive MIMO setups.

This paper addresses multi-user multi-cluster massive multiple-input-multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode, and taking into consideration the impact of imperfect successive interference cancellation (SIC), an in-depth analytical analysis is carried out, in which closed-form expressions for the outage probability and ergodic rates are derived. Subsequently, the power allocation coefficients of users within each sub-group are optimized to maximize fairness. The considered power optimization is simplified to a convex problem, which makes it possible to obtain the optimal solution via Karush-Kuhn-Tucker (KKT) conditions. Based on the achieved solution, we propose an iterative algorithm to provide fairness also among different sub-groups. Simulation results alongside with insightful discussions are provided to investigate the impact of imperfect SIC and demonstrate the fairness superiority of the proposed dynamic power allocation policies. For example, our results show that if the residual error propagation levels are high, the employment of orthogonal multiple access (OMA) is always preferable than NOMA. It is also shown that the proposed power allocation outperforms conventional massive MIMO-NOMA setups operating with fixed power allocation strategies in terms of outage probability.

The combination of coordinated multi-point (CoMP) and underlay spectrum sharing promises substantial spectral efficiency (SE) gains for future cellular networks. However, this concept has been largely overlooked in the literature. Moreover, none of the few relevant studies consider the use of "standard" transmission strategies to facilitate the adoption of the aforementioned communication paradigm by 5G networks. The use of load-controlled antenna arrays (LC-AA) and symbol-level (SL) precoding can further enhance the performance of CoMP cellular networks, as it has been shown in the literature. Nevertheless, the corresponding research works do not consider a spectrum sharing setup. In this paper, we fill this gap in the literature by deriving the optimal power allocation strategy (in the sum-SE sense) and the corresponding algorithm that implements this solution for scenarios where various linear or SL precoding schemes are applied. Numerical simulations indicate the feasibility of the proposed approach for LC-AA-equipped CoMP networks and shed light on the effect of various parameters on system performance.

As network deployments become denser, interference arises as a dominant performance degradation factor. To confront with this trend, Long Term Evolution (LTE) incorporated features aiming at enabling cooperation among different base stations, a technique termed as Coordinated Multi Point (CoMP). Recent field trial results and theoretical studies of the performance of CoMP schemes revealed, however, that their gains are not as high as initially expected, despite their large coordination overhead. In this paper, we review recent advanced Coordinated Beamforming (CB) schemes, a special family of CoMP that reduces the coordination overhead through a joint choice of transmit and receive linear filters. We focus on assessing their resilience to uncoordinated interference and Channel State Information (CSI) imperfections, which both severely limit the performance gains of all CoMP schemes. We present a simple yet encompassing system model that aims at incorporating different parameters of interest in the relative interference power and CSI errors, and then utilize it for the performance evaluation of the state-of-the-art in CB schemes. It is shown that blindly applying CB in all system scenarios can indeed be counter-productive.

Compact parasitic arrays in the form of electronically steerable parasitic antenna radiators (ESPARs) have emerged as a new antenna structure that achieves multiple-input-multiple-output (MIMO) transmission with a single RF chain. In this paper, we study the application of precoding on practical ESPARs, where the antennas are equipped with load impedances of quantized values. We analytically study the impact of the quantization on the system performance, where it is shown that while ideal ESPARs with ideal loads can achieve a similar performance to conventional MIMO, the performance of ESPARs will be degraded when only loads with quantized values are available. We further extend the performance analysis to imperfect channel state information. In order to alleviate the performance loss, we propose to approximate the ideal current vector by optimization, where a closed-form solution is further obtained. This enables the use of ESPARs in practice with quantized loads. Simulation results validate our analysis and show that a significant performance gain can be achieved with the proposed scheme over ESPARs with quantized loads. Finally, the tradeoff between performance and power consumption is shown to be favorable for the proposed ESPAR approaches compared with conventional MIMO, as evidenced by our energy efficiency results.

Electronically steerable parasitic array radiator (ESPAR) technology enables the implementation of antenna arrays of a number of elements with a single radio frequency (RF) source. Two approaches to achieve stable transmission using an ESPAR antenna (EA) are to increase the self-resistance of an EA or to transmit signals closely approximating the actual signals that keep the EA stable. Both approaches did not take into account the impact of limited power on an EA transmission, which is a practical constraint on power amplifier design. We propose a new transmission scheme to enable an EA to provide stable multiple antenna functionality taking into account the instantaneous total power requirement. This problem is formulated as a non-convex optimization problem and it is solved analytically by coordinate transformation and geometric analysis. The optimal approximate signals are obtained using root finding and interior-point algorithms. Moreover, it is shown through simulations that our proposed scheme achieves similar symbol error rate performance to that of the standard multiple antenna transmitter with multiple RF chains under power limited single-user and multi-user transmission scenarios. Furthermore, it is shown that increasing the self-resistance of an EA to achieve stability is highly power inefficient.

In this paper, the performance of a cloud radio access network (CRAN) is analysed, which consists of multiple randomly distributed remote radio heads (RRHs) and a macro base station (MBS). Different from previous works on CRAN where Poisson Point Process (PPP) is used to model spatial distribution of RRHs, a more realistic Matern Hard-core point process (MHCPP) model is adopted in this work. To compare system performance of CRAN when different transmission strategies are used, two RRH selection schemes are adopted including 1) the best RRH selection (BRS) and 2) all RRHs participation (ARP). Considering downlink transmission, the outage probability and system throughput of CRAN are analytically characterized. The presented results demonstrate that compared to PPP model, the presence of hard-core distance will increase outage probability. Furthermore, the BRS scheme is more energy-efficient than the ARP scheme. Moreover, it is shown that the hard-core distance has a more significant impact on systems with higher intensity of PPP distributed candidate points and in large hard-core distance regime increasing the intensity of candidate points can only provide a small improvement in outage performance.

This paper proposes a new system architecture for Licensed Shared Access (LSA) wireless networks, as well as novel band management techniques for fair and ranking-based spectrum allocation. The proposed architecture builds upon recently standardized and regulatory-accepted LSA systems and stems from the work done in the EU-funded project ADEL. Two new resource allocation algorithms are introduced and their behaviour is validated via system-level simulations.

In this paper, we analyze the performance of a cloud radio access network (CRAN), consisting of multiple randomly distributed remote radio heads (RRHs) and a macro base station (MBS), each equipped with multiple antennas. To model the spatial distribution of RRHs and analyze its performance, we use stochastic geometry tools. In contrast to previous works on CRAN that consider Poisson Point Process (PPP) model for the spatial distribution of RRHs, we consider a more realistic Matérn hard-core point process (MHCPP) model that imposes a certain minimal distance (referred to as hard-core distance) between the two RRHs so that the RRHs are not too close to each other. To compare system performance of CRAN when different transmission strategies are used, three RRH selection schemes are adopted including 1) the best RRH selection (BRS); 2) all RRHs participation (ARP); and 3) nearest RRH selection (NRS). Considering downlink transmission, the ergodic capacity, outage probability, and system throughput of CRAN are analytically characterized for different RRH selection schemes. The presented results demonstrate that compared to PPP model, the increase in hard-core distance will result in a higher outage probability and cause a negative impact on ergodic capacity. Furthermore, when the same total transmit power is consumed, BRS scheme provides the best outage performance while ARP scheme is the best RRH selection scheme when the same transmit SNR at each RRH is assumed. Moreover, it is shown that the hard-core distance has a more significant impact on systems with higher intensity of PPP distributed candidate points and in large hard-core distance regime increasing the intensity of candidate points can only provide a small improvement in outage performance. We extend our work to multiuser case with zero-forcing (ZF) precoding where it is proven that the results in multiuser case reduce to the derived results in this work by substituting K=1 for single-user.

Electronically steerable parasitic array radiator (ESPAR) antenna has been proposed to obtain multiple antenna functionality with only a single radio frequency (RF) chain. However, for some signals, the input resistance of the ESPAR antenna (EA) becomes negative. A negative input resistance would lead to oscillatory/unstable behavior of an EA to transmit signals. In this work, we address this issue of an EA by obtaining approximate signals for transmission, which are close to the ideal signals in the mean-squared-error (MSE) sense, and satisfy the requirement that the input resistance is positive. Specifically, we formulate and solve an optimization problem to minimize the MSE between the ideal and the approximate signals taking into account the constraint on the input resistance. Closed-form expressions to calculate the approximate signal vector from ideal signal vector are also obtained, resulting in simplified processing at the transmitter. We denote the EA utilizing the novel closed-form expressions as EA with preprocessing (EA-P) and the EA without any preprocessing as the standard EA (EA-S). The performance of EA-P is compared with the performance of EA-S and the standard multiple antenna system, with multiple RF chains, under various communication scenarios. Our simulations show that the performance of EA-S significantly degrades compared with the standard multiple antenna system and an error floor is obtained. However, using the proposed EA-P scheme, the error floor is avoided and nearly the same performance as that of the standard multiple antenna system is achieved.

We present a method for smart auscultation by proposing a novel blind recovery of the original cardiac and respiratory sounds from a single observation mixture, in the framework of nonnegative matrix factorization (NMF). The method learns the basis spectra of the mixing sources in unsupervised or semisupervised fashion depending upon the applications. A modified NMF technique is proposed, which enforces the spectral structure of the target sources in mixture factorization, resulting in good separation of target sources, even in the presence of nonstationary noise. Moreover, data is processed in small batches which 1) enables dynamic bases spectra update technique to mitigate the spectral variations of the mixing sources, and 2) reduces computational complexity. The analytical work is verified through simulations using synthetic as well as actual clinical data collected from different subjects in different clinical sittings. The proposed smart auscultation method demonstrates excellent results even in noisy clinical environments.

The detection of heart rate variability (HRV) via cardiac auscultation examination can be a useful and inexpensive tool which, however, is challenging in the presence of pathological signals and murmurs. The aim of this research is to analyze acoustic cardiac signals for HRV and murmur detection. A novel method based on hierarchical decomposition of the single channel mixture using various nonnegative matrix factorization techniques is proposed, which provides unsupervised clustering of the underlying component signals. HRV is determined over the recovered normal cardiac acoustic signals. This novel decomposition technique is compared against the state-of-the-art techniques, experiments are performed using real-world clinical data, which show the potential significance of the proposed technique.

Transmitter (TX) cooperation at various levels has been shown to increase the sum throughput of multiuser multiple-input multiple-output (MIMO) systems. In this paper we consider a k-user MIMO system where TXs have only global channel state knowledge. It has been theoretically shown that interference alignment (IA) achieves the K/2 degrees of freedom of this K-user MIMO interference channel. However, results on IA and all proposed transceiver techniques for this channel up to date, assume conventional antenna arrays at the transceivers with multiple radio-frequency (RF) chains, each connected to a different antenna element. To reduce the consequent hardware burden and power dissipation imposed by such arrays, we propose in this paper the utilization of compact single-RF electronically steerable parasitic (passive) array radiators (ESPARs) at the cooperating TXs. A signal model capable of capturing the characteristics of the considered antenna arrays is first described and then a general precoding design methodology for the tunable parasitic loads at the TXs' ESPARs is introduced. Specific precoding techniques and an indicative ESPAR design are presented for a 3-user 2×2 MIMO system with one ESPAR TX, and the obtained performance evaluation results show that the gains of TX cooperation are still feasible.

Auscultation is an effective noninvasive medical procedure for examining the cardiorespiratory system. However, the cardiac and respiratory acoustic sounds interfere in time as well as in spectral contents, which hampers the diagnostibility of the classical stethoscope. We propose a method for smart auscultation by blindly recovering the original cardiac and respiratory sounds from a single observation mixture. We decompose the spectrogram of the mixture into independent, non-redundant components, by employing non-negative matrix factorization (NMF). To group the decomposed components into original sources, a new unsupervised technique is proposed. Time-frequency masking is used to recover the original sources. This smart auscultation method is successfully applied to actual data collected from different subjects in different clinical settings. Our method demonstrates excellent results even in noisy clinical environments.

It is already well-known that interference alignment (IA) achieves the sum capacity of the K-user interference channel at the high interference regime. On the other hand, it is intuitively clear that when the interference levels are very low, a sum-rate scaling of K (as opposed to K/2 for IA) should be accessed at high signal-to-noise ratio values by simple (“myopic”) singlelink multiple-input multiple-output (MIMO) techniques such as waterfilling. Recent results have indicated that in certain low-to-moderate interference cases, treating interference as noise may in fact be preferable. In this paper, we present a distributed iterative algorithm for K-user MIMO interference networks which attempts to adjust itself to the interference regime at hand, in the above sense, as well as to the channel conditions. The proposed algorithm combines the system-wide mean squared error minimization with the waterfilling solution to adjust to the interference levels and channel conditions and maximize accordingly each user's transmission rate. Sum-rate computer simulations for the proposed algorithm over Ricean fading channels show that, in the interference-limited regime, the proposed algorithm reconfigures itself in order to achieve the IA scaling whereas, in the low-to-moderate interference regime, it leads itself towards interference-myopic MIMO transmissions.

This paper considers a K-user multiple-input multiple-output (MIMO) interference channel in which uncoordinated interference appears. Due to the uncoordinated interference, perfect interference alignment (IA) may be not attained, which indicates the interference subspaces can not be completely aligned. The rank constrained rank minimization (RCRM) framework has been recently developed to minimize the rank of the subspace spanned by interference signals with full rank constraint on the direct signal space. To solve this non-convex and intractable problem, we introduce a log-sum function as an approximation surrogate and develop a joint Frobenius norm and reweighted nuclear norm approach which jointly enhances the sum rate at low-to-moderate signal-to-noise ratio (SNR) and the achievable multiplexing gain per user in the high SNR regime. The optimum solutions are iteratively achieved with the convergence guaranteed. Simulation results are presented to validate the effectiveness of the proposed reweighted nuclear norm algorithm and its further development.

Spectrum sensing for cognitive radio is studied, using an electronically steerable parasitic antenna receptor (ESPAR), which relies on a single RF front end, and therefore meets the demanding low cost, power and size requirements of modern wireless terminals. We develop a strategy whereby the angular domain is divided into sectors, that are accessed via beamforming on a time division basis, to detect signals from primary users. We study the performance of detection metrics based on energy received per beam, and also eigenvalue-based detection statistics through considering the covariance matrix across the various directional beams. The ESPAR is able to achieve over 6dBi SNR improvement due to its beamforming capability. Further, once primary users' signals have been detected, directional transmit opportunities which do not interfere with active PUs become available, and we develop an adaptive beamforming algorithm to capitalise on these to efficiently utilise the spatial domain, which numerically optimises the beampattern and antenna efficiency using a convex formulation. The resulting beampatterns give between -20dB and -30dB nulls in the primary user direction.

Managing uncoordinated interference becomes a substantial problem for heterogeneous networks, since the unplanned interferences from the femtos cannot be coordinately aligned with that from the macro/pico base stations (BSs). Due to the uncoordinated interference, perfect interference alignment (IA) may be not attained. In order to achieve linear capacity scaling by IA, we follow the rank-constrained rank minimization (RCRM) framework which minimizes the rank of the interference subspace with full rank constraint on the direct signal space. Considering that the sum of log function can obtain low-rank solutions to linear matrix inequality (LMI) problems for positive semidefinite matrices, we introduce sum of log function as an approximation surrogate of the rank function. To minimize the concave function, we implement a Majorization-Minimization (MM) algorithm and develop a reweighted nuclear norm minimization algorithm with a weight matrix introduced. Moreover, considering the practical available signal-to-noise ratio (SNR), a mixed approach is developed to further improve the achievable sum rate in low-to-moderate SNR region. Simulation results show that the proposed algorithm considerably improves the sum rate performance and achieves the highest multiplexing gain than the recently developed IA approaches for various interference channels.

Space-time coded cooperative transmission has been proposed as a means to prolong the battery lifetime of conventional single-antenna energy-constrained wireless sensor nodes. However, newly proposed smart-antenna sensor prototypes enable the existence of more than one antenna within a single-radio transceiver architecture. Exploiting such capability, this paper proposes simple non-cooperative space-time techniques for single-RF switched-antenna systems that reduce significantly both the transmission and the circuit energy consumption. The energy savings of the suggested schemes are shown not only against conventional SISO systems, but also against cooperative diversity schemes in Rayleigh and log-normal shadowed Rayleigh fading channels with distance-based path loss.

Interference Alignment (IA) is the process of designing signals in such a way that they cast overlapping shadows at their unintended receivers, while remaining distinguishable at the intended ones. Our goal in this paper is to come up with an algorithm for IA that runs at the transmitters only (and is transparent to the receivers), that doesn't require channel reciprocity, and thus alleviates the need to alternate between the forward and reverse network as is the case with the Distributed IA algorithm presented, thereby saving significant overhead in certain environments where the channel changes frequently. Most importantly, our effort is focused on ensuring that this one-sided approach does not degrade the performance of the system w.r.t. Distributed IA. As a first step, we mathematically express the interference in each receiver's desired signal as a function of the transmitters' beamforming vectors. We then propose a simple steepest descent (SD) algorithm and use it to minimize the interference in each receiver's desired signal space. We mathematically establish equivalences between our approach and the Distributed IA algorithm and show that our algorithm also converges to an alignment solution (when the solution is feasible).

In this paper, we study the eigenvalue-based spectrum sensing techniques for multiple-antenna cognitive radio networks. First, we study the extreme eigenvalue distributions of a complex Wishart matrix and then, in contrast to the asymptotic analysis reported in the literature, we derive the exact distribution of the test statistics of (i) maximum eigenvalue detector (MED) (ii) maximum-minimum eigenvalue (MME) detector and (iii) energy with minimum eigenvalue (EME) detector for finite number of samples (n) and finite number of antennas (m). These distributions are represented by complex hypergeometric functions of matrix argument, which can be expressed in terms of complex zonal polynomials. We also describe the method to compute these complex hypergeometric functions. Based on these exact distribution of the test statistics we find the exact decision thresholds as a function of the desired probability of false-alarms for MED, MME and EME. Simulation results show superior performance compared to the decision thresholds obtained from asymptotic (i.e, n,m → ∞) distributions.

A novel orthogonal space time block code (OSTBC) that is capable of extracting a diversity order of two via a single RF frontend is proposed in this paper. The scheme is implemented using a practical antenna system of two transmit antennas connected to a common ground. An orthogonal block of two real (non-complex) signals is transmitted over a duration of two symbol periods by exciting one antenna every symbol period while exciting the other parasitically by the field of the active one. A switched-antenna system similar to the one reported in [10] can be used for simultaneously driving and switching the antenna elements. Besides the orthogonality of the signals, the array far-field is a linear mixture of two eigenpatterns onto which the BPSK signals are mapped, hence independent fading among the signals is almost always guaranteed.

The downlink performance of systems exploiting multiuser diversity has been shown to improve by using multiple antenna receivers and diversity combining techniques. However, the cost and power restrictions of the user mobile terminals prohibit the use of multiple antennas whereas the size limitations can result in correlated and coupled receive antenna elements downgrading the effectiveness of the applied schemes. In this paper, we propose a simple beam selection combining (SC) technique using a miniaturized single radio receive antenna system assisted by low cost parasitic antennas. The system is optimized for both antenna efficiency and diversity thus made capable of forming four practically uncorrelated beam-patterns. The computer simulations show that the proposed beam SC technique outperforms classical antenna SC as well as a previously reported beam combining approach in terms of the average throughput especially for small user populations.

Multiple input-multiple output (MIMO) systems have drawn remarkable interest in recent years, since they are known to boost the spectral efficiency of wireless communication systems compared to single antenna architectures. However, the implementation cost and circuit complexity of such systems conflicts the guaranteed high performance gain. Recent research efforts focus on the investigation of cheaper and low complexity transceivers, introducing a novel beamspace MIMO (BS-MIMO) architecture. BS-MIMO systems have shown equivalent performance with the corresponding conventional systems, while they have been also evaluated in closed loop environments. In this paper we extend the closed loop BS MIMO approach presenting advanced limited feedback techniques which outperform predecessor feedback schemes.

The goal of this paper is to establish the rate region of a wireless multi-hop, one-sender, two-receiver transmission chain. We examine and evaluate the advantages of utilizing directional antennas in this context. In particular, we consider a two-dimensional communication network with a single source node S, two destination nodes D1, D2, and 2 times (N - 1) intermediate nodes placed equidistantly between them. Multi-hop transmission is an extension of single-hop transmission that can take advantage of the reduced attenuation between closely spaced relay nodes, as well as the opportunity of spatial reuse. In two-dimensional multi-hop half-duplex transmission, each node utilizes capacity-achieving point-to-point codes to forward the most recently decoded message to its nearest neighbor in the direction of D1or D2. The transmission is performed over two parallel chains and it is a mixture of two techniques, "broadcast" communication (one transmitter to two relay nodes) and interference channel. First we describe our network and the assumptions made in the scope of this study. We further evaluate the end-to-end rate region of this topology under our transmission constraints and describe the effects that take place after replacing omni-directional antennas with perfectly directional ones. Our results indicate a 5-fold end-to-end sum rate improvement over a 10-hop network with the use of 30 degrees directional beams, as compared to omni-directional transmission.

A universal scheme for encoding multiple symbol streams using a single driven element (and consequently a single radio frequency (RF) frontend) surrounded by parasitic elements (PE) loaded with variable reactive loads, is proposed in this paper. The proposed scheme is based on creating a MIMO system by expanding the far-field of a compact parasitic array into an orthogonal set of angular functions (basis). Independent information streams are encoded by means of angular variations of the far-field in the wavevector domain, rather than spatial variations as usually happens in conventional MIMO systems. The array can spatially multiplex the input streams by creating all the desired linear combinations (for a given modulation scheme) of the basis functions. The desired combinations are obtained by projecting the ratio of the symbols to be spatially multiplexed on the ratio of the basis functions' weights (complex coefficients), which is a function of the currents induced on the PE within the antenna domain, and controlled by the independent reactive loadings.

Beamforming capabilities of electronically steerable passive array radiator (ESPAR) antennas have attracted considerable attention in recent literature. In this paper we consider a different beamforming approach, presenting an efficient optimization algorithm which enables such antennas to create specific transmit radiation patterns in real time, rather than patterns aiming at signal to interference ratio maximization. Moreover, we investigate the proposed algorithm over a novel multiple input - multiple output architecture, showing that even cost and size sensitive mobile handsets may efficiently operate in closed loop communication environments.

A framework for implementing spatial multiplexing using an electronically steerable parasitic array radiator (ESPAR) antenna is presented. While traditional multi-element arrays (MEA) show great potential for meeting the increasing demand for higher data rates, they come at the expense of computationally demanding signal processing, larger size, and higher consumption of DC power, making traditional MEA impractical at userspsila hand-held devices. In this work, we introduce a novel methodology for using ESPAR antennas as a compact, cheap and less power-hungry MEA, for spatially multiplexing BPSK symbols, while still providing comparable spectral efficiency and performance as traditional MEA. The main idea is to exploit the strong mutual coupling among the ESPAR antenna elements at the transmitter side to create a linear combination of orthogonal patterns (beams), onto which the symbols are directly mapped, instead of the traditional approach of sending the symbols toward different locations within the antenna domain. On the other side, the receiver (base-station (BS) or access point (AP)) is equipped with a traditional uniform linear array (ULA), and decodes the received signal using the Vertical Bell labs layered space time (VBLAST) algorithm.

Recently, a novel beamspace multiple input multiple output (BS-MIMO) transmission technique has appeared, which increases the spectral efficiency of open-loop communication systems while using compact antenna structures with a single radio-frequency (RF) front-end at the transmitter. In this paper, we extend the aforementioned architecture proposing an efficient limited feedback technique for capacity optimization, considering electronically steerable parasitic array radiator (ESPAR) antennas at the transmitter. The performance of the resulting closed-loop BS-MIMO is evaluated against equivalent traditional MIMO systems that require a much larger number of active antenna elements to operate. The results are very promising, paving the way for integrating the proposed system in cost and size sensitive wireless handheld devices such as mobile terminals and mobile personal digital assistants.

In this paper we introduce a new perspective to the implementation of wireless MIMO transmission systems with increased bandwidth efficiency. Unlike traditional spatial multiplexing techniques in MIMO systems, where additional information can be sent through the wireless channel by feeding uncorrelated antenna elements with diverse bitstreams, we use the idea of mapping diverse bitstreams onto orthogonal bases defined in the beamspace domain of the transmitting array far-field region. Using this approach we show that we can increase the capacity of wireless communication systems using compact parasitic antenna architectures and a single RF front end at the transmitter, thus paving the way for integrating MIMO systems in cost and size sensitive wireless devices such as mobile terminals and mobile personal digital assistants.

Wireless systems exploiting multi-user diversity require accurate channel state information. In this paper we examine channel prediction as a method to improve the performance of these systems. We model the outdoor channel by the Rician model, which combines diffuse spectra with a single specular component. Prediction accuracy is determined for the Rician model given various ratios (K factors) of specular to diffuse power. Simulation results show that accurate channel prediction further than one wavelength can be achieved at 30 dB SNR when the channel K factor is greater than ten. The predictor was evaluated on measured channels, and the Rician model was found to be appropriate as prediction intervals of the measured data are similar to those of synthetic data with same K factor. Using measurements some results regarding channel stationarity and optimal filter order are presented. We show for a proportionally fair scheduled downlink packet system that the predictor reduces fade margin at fixed packet outage leading to an improvement in throughput.

In this paper the use of electronically steerable passive array radiator (ESPAR) antennas is introduced for achieving increased spectral efficiency characteristics in multiple-input, multiple-output (MIMO) systems using a single active element, and compact antennas. The proposed ESPAR antenna is capable of mapping phase-shift-keying (PSK) modulated symbols to be transmitted onto orthogonal basis functions on the wavevector domain of the multi-element antenna (MEA), instead of the traditional approach of sending different symbol streams in different locations on the antenna domain. In this way, different symbols are transmitted simultaneously towards different angles of departure at the transmitter side. We show that the proposed system, called beamspace-MIMO (BS-MIMO) can achieve performance characteristics comparable to traditional MIMO systems while using a single radio-frequency (RF) front-end and ESPAR antenna arrays of total length equal to λ/8, for popular PSK modulation schemes such as binary-PSK (BPSK), quaternary-PSK (QPSK), as well as for their offset-PSK and differential-PSK variations.

We construct a class of linear space-time block codes for any number of transmit antennas that have controllable ML decoding complexity with a maximum rate of 1 symbol per channel use. The decoding complexity for M transmit antennas can be varied from ML decoding of 2lceillog2Mrceil-1symbols together to single symbol ML decoding. For ML decoding of 2lceillog2Mrceil-n(n = 1,2,hellip) symbols together, a diversity of min(M, 2lceillog2Mrceil-n+1) can be achieved. Numerical results show that the performance of the constructed code when 2lceillog2Mrceil-1symbols are decoded together is quite close to the performance of ideal rate-1 orthogonal codes (that are non-existent for more than 2 transmit antennas).

Most classes of quasi-orthogonal space-time codes proposed in the literature require the use of rotated constellations for the interfering symbols to ensure full diversity. Since there is no analytical result available to get the exact probability of error in terms of the rotation angle, the optimization of the rotation angle has been done with respect to the Euclidean distance or the diversity product criteria. This paper provides analytical expressions for the optimal rotation angles for the Euclidean distance criteria for any M-PSK (phase shift keying) constellation.

Channel prediction is an appealing approach to mitigate channel mismatch in wireless downlink packet systems. Channel mismatch arises due to the delay in the feedback loop. Both synthetic and measured channels were used to assess the accuracy of channel prediction for various ratios of specular to diffuse power. The power spectrum was estimated rather than assumed known. It has been found that high ratios (K factors) greater than ten are necessary for prediction greater than one wavelength. K factors of measured channels gave prediction accuracy similar to that of the synthetic channel given by the same K factor.

In high speed downlink packet access systems (HS-DPA), opportunistic beamforming has been proposed as a viable technique for improving the system capacity by taking advantage of the multiuser diversity due to the time varying fluctuations of the mobile users channels. In opportunistic beamforming with proportional fair scheduling, mobile users who have the largest rates when compared with their averaged throughputs, are scheduled over preferred spatial beams, thereby yielding improved throughput-delay tradeoffs. In this paper, we consider cellular architectures where base stations coordinate to service users. These base stations are assumed equipped with smart antenna systems which generate pilot beams according to a predefined algorithm, collect only an SINR report from the users, and provide opportunistic scheduling. We propose schemes where the base stations coordinate to generate beams that reduce the inter-cell interference to the users considered for service. Through computer simulations we show that the proposed base station coordination technique provides significant performance gains in downlink packet access cellular systems. Furthermore this is achieved with the use of only modest feedback (SINR) from the users i.e. without the need for excessive channel state information feedback.

We examine the effect of measurement delays on the throughput of certain downlink data packet systems operating over Rayleigh fading channels. In these systems the base station (BS) schedules a single user at a time and transmits at a rate which is based on measurements of the BS's received power performed by the user. The same subject was also discussed in a recent paper, titled "Asymptotically fair transmission scheduling over fading channels" by Berggren and Jantti (2004). They studied the effects of measurement delays on the operation of the scheduler. As a consequence of the delay, it is possible that by the time the BS actually transmits data, the propagation channels might have changed, such that the scheduler's choice no longer conforms to the desired scheduling policy, resulting in loss of system throughput and multi-user gain. Berggren and Jantti assume that perfect link adaptation is nevertheless always assured, i.e., that the BS transmits at a rate that matches precisely the current state of the selected user's channel. However, measurement delays lead also to mismatch between the data rate the BS transmits to the chosen user, and the current state of the propagation channel to that user. We believe that this mismatch must also be taken into account. In this letter we propose to use a backoff factor and analyze its mitigating effect on losses introduced by measurements delay in a Rayleigh fading environment. We then show the resulting gain in system throughput for optimal choices of the backoff factor

We address the problem of pilot and data channel mismatch in a steered space time spreading (SSTS) system by means of advanced signal processing at the mobile receiver. The main idea is to apply the SSTS antenna array architecture and transmission algorithm and involve both the pilot and traffic signals in channel estimation at the receiver. Two semi-blind algorithms are compared with the conventional pilot-based receiver in a cdma2000-1xRC3 environment by means of simulations with variable speed and spatial angular spread, taking into account the main imperfections, such as estimation error for the correlation coefficient at the reverse link, calibration error, different pilot powers for diversity antennas, etc. It is demonstrated that the semi-blind algorithms outperform the conventional receiver in the low- and medium-speed areas.

We address the problem of downlink throughput improvement for IEEE 802.11a/g systems by using a modified access point (AP) equipped with multiple antennas. The main restriction is that the standard terminals should not be modified in any way. An alternating time-offset space division multiple access (SDMA) solution is considered for a conference room scenario. A simulation is based on channel models approved by the IEEE 802.11 Standard Group and takes into account the main features of the IEEE 802.11a/g standard. It is demonstrated that a near doubling of downlink capacity can be achieved in a conference room environment.

It is shown that single symbol maximum-likelihood (ML) decoding for chosen rate 6/8 linear complex space-time codes for up to eight transmit antennas is possible in the presence of a phase feedback. The performance of the code is the same as that of an ideal code, for which the sufficient statistic of the channel is its Frobenius norm. For rate 1 codes for up to eight antennas, a two-phase feedback enables a symbol to see the interference from only one symbol instead of three, thereby reducing the complexity of ML decoding. Quantization of the feedback is also considered.

Asymptotic Analysis of MIMO Wireless Systems With Spatial Correlation at the Receiver With a unified approach, this paper investigates the asymptotic performance, or equivalently, the large-system properties, of various point-to-point systems with antenna-array-based multiple-input multiple-output (MIMO) channels having spatial correlations. Using the replica method originally developed for statistical physics, we provide analytical solutions to the input–output mutual information of MIMO systems at the transmit side, with arbitrary inputs, and at the receive side, with either the optimum space–time joint decoding, or various suboptimum spatial equalizers followed by a bank of temporal decoders. Important physical meanings revealed though the analytical solutions to those more practical combinations, such as how the input–output mutual information is affected by the channel spatial correlations, are highlighted along our derivation. Moreover, we provide a novel waterfilling algorithm to determine the data-rate-maximizing transmit signal covariance matrix when only the channel long-term spatial correlations are available at the transmitter.

Abstract Coexistence of different access technologies, hierarchical cellular deployment, a wide variety of data services, requirements for transparent operation across different technologies, adaptivity to varying network conditions and mobility and quality of service (QoS) constraints introduce a number of challenges in the design of future generation systems and the specification of new air interfaces, such as efficiency and flexibility in the utilization of spectrum, dynamic resource allocation and exploitation of the multiuser diversity and reconfigurable interference management and inter‐cell coordination. In this paper, three critical issues for the design of next generation systems are addressed: (i) duplexing, (ii) scheduling and resource allocation and (iii) interference and inter‐cell coordination. A number of research directions are presented, which constitute promising potential candidates for next generation systems specification. Copyright © 2005 John Wiley & Sons, Ltd.

In single-user MIMO communication, the first-order throughput scaling is determined by the smaller of the number of transmit and receive antennas. This typically renders terminals the constraining bottleneck. In a multiuser downlink, this bottleneck can be bypassed by having the base station communicate with multiple terminals simultaneously, whereby the receive antennas at those terminals are effectively pooled in term of throughput scaling. This, however, requires that the base has instantaneous channel information. Without such information, the structure and statistics of the channel can be exploited to form multiple simultaneous beams towards the various users, but these beams are in general mutually interfering. Focusing on UMTS HSDPA (high-speed downlink packet access), the paper proposes the use of multiuser detection to discriminate the signals conveyed over interfering beams. This approach is formulated and experimentally evaluated on an HSDPA MIMO testbed that involves a commercial base station, multi-antenna terminals, and custom ASICs.

We use the replica method originally developed in statistical physics to investigate the asymptotic sum-rate of a Gaussian antenna-array-based multiple-input multiple-output (MIMO) multiple-access wireless channel having spatial correlations at both the transmitters and the receiver. The asymptotic solution is not only rigorously valid for systems with large array sizes, but it also produces highly accurate ergodic results for systems with only a few antenna elements at each transmitter and receiver. Furthermore, with the asymptotic solution, we provide an efficient iterative water-filling algorithm to determine the optimum transmit signal covariance matrices when only the slow-varying channel spatial covariance information is available.

A blind source separation problem for short burst systems is addressed by means of a constant modulus technique under orthogonal constraints. It is shown that a conventional Gram-Schmidt orthogonalization procedure normally exploited in similar applications may cause a non-uniform misadjustment distribution among the receiver outputs leading to an overall performance degradation. We propose a modified algorithm, based on random reordering of the weight vectors before the orthogonalization stage, and demonstrate its efficiency by means of simulations in a short burst MIMO environment.

Opportunistic scheduling (OS) has been proposed as a technique to improve the downlink throughput of high speed packet systems. OS attempts to use the time varying propagation channels between the base station (BS) and the mobile stations (MSs) when they reach their peak rate capability and defer using channels when in bad state. It exploits the fact that the propagation channels between the BS and the MSs fade independently and the tolerance of many data services to delay and delay jitter. However, when the fading is slow in comparison with an acceptable packet delay, or weak, OS is not very useful. In such cases, opportunistic beamforming (OBF), a recently proposed scheme, may offer additional gains. OBF is a "natural" enhancement to OS. The enhancement amounts to replacing the BS antenna with multiple antennas and implementing an algorithm that generates a different radiation pattern every timeslot. In this paper we propose to tie the sequence of radiation patterns to the waiting times of the served MSs. We show through simulations that the scheme we propose leads to both, reduced probability of excessive packet delay and improved throughput. This can be achieved by additional processing of the feedback received from the MSs, with no additional signaling on the air interface.

We use the replica method originally developed in statistical physics to investigate the asymptotic sum-rate of a Gaussian antenna-array-based multiple-input multiple-output (MIMO) multiple-access wireless channel having spatial correlations at both the transmitters and the receiver. The asymptotic solution is not only rigorously valid for systems with large array sizes, hut it also produces highly accurate ergodic results for systems with only a few antenna elements at each transmitter and receiver. This otters the asymptotic solution important practical values in analyzing and designing a MIMO multiple access system that makes best use of the wireless channel structure. Furthermore, with the asymptotic solution, we provide an efficient iterative water-filling algorithm to determine the optimum transmit signal covariance matrices when only the slow-varying channel spatial covariance information is available.

In a unified approach, this paper investigates the asymptotic performance, or equivalently the large-system properties, of various point-to-point systems with antenna-array-based multiple-input multiple-output (MIMO) channels having spatial correlations at both the transmitter and the receiver. Using the replica method originally developed for statistical physics, we provide closed-form solutions to the input-output mutual information of MIMO systems: 1) at the transmit side, with either Gaussian inputs or various nonGaussian arbitrary inputs, and 2) at the receive side, with either the optimum space-time joint-decoding, or various suboptimum spatial equalizers followed by a bank of temporal decoders. Among all these combinations, in Part I, we focus on the performance analysis of the MIMO systems with the optimum space-time joint-decoding, i.e., the information-theoretic optimum decoding. Based on the framework developed in this paper, some known performance results are recovered and some new performance results are discovered. Furthermore, we provide a novel water-filling algorithm to determine the data-rate-maximizing transmit signal covariance matrix when only the channel long-term spatial correlations are available at the transmitter. In Part II, we focus on the performance analysis of the MIMO systems with various suboptimum spatial equalizers, each followed by a bank of temporal decoders.

For pt.I, see ibid., p.3504-8 (2004). In Part I of this paper, we analyzed the asymptotic mutual information of the joint-decoding MIMO systems. Here in Part II, we focus on the performance analysis of the MIMO systems with various separate decoding schemes, i.e., with various suboptimum spatial equalizers followed by a bank of temporal decoders. Among the suboptimum spatial equalizers, under the proposed framework, we cover both 1) linear spatial equalizers such as linear MMSE spatial equalizer, linear zero-forcing spatial equalizer, and matched-filter equalizer, and 2) nonlinear spatial equalizers such as individually optimal spatial equalizer and marginal optimal spatial equalizer. Closed-form solutions are derived for all the possible combinations of 1) various transmit-side arbitrary input distributions and 2) the receive-side decoding schemes listed above. Important physical meanings revealed though the closed-form solutions to those more practical combinations, as how the input-output mutual information is affected by the transmit-side and the receive-side channel spatial correlations, are highlighted along our derivation.

The proportional fair (PF) scheduling algorithm has been proposed as a technique to improve the throughput of multiple packet-data users sharing a wireless downlink channel while preserving fairness. It exploits the fact that the propagation channels between the base station (BS) and the mobile stations (MS) fade independently giving rise to "multi-user diversity". The gain offered is significant when the allowed packet delay exceeds the de-correlation time of the fading channels and the number of users is high. We analytically investigate the "time allocation" property and the multi-user diversity gain of the PF algorithm under certain conditions in the context of the HSDPA standard. Since in practical systems a certain latency is unavoidable, we have studied the use of a "backoff' factor to reduce the probability that when the transmission takes place, the channel cannot support it.

Multiple-access interference is one of the major impediments in the reverse link of code-division multiple-access (CDMA) systems, due to the synergy of the users' spreading codes, transmission delays, and the channel characteristics. A space-time dynamic signature-assignment (DSA) algorithm was briefly described by the authors in a previous paper. In this paper, we further elaborate on the space-time DSA approach and its receiver structure for the reverse link of direct-sequence (DS)-CDMA systems using multiple antennas at the receiver. The space-time DSA dynamically assigns the users' spreading codes and transmission delays, i.e., to assign the user signatures, in order to minimize mutual crosscorrelations. In assigning the signatures, the DSA adopts a low-complexity iterative algorithm which utilizes channel information and aims to maximize the signal-to-interference-plus-noise ratio of the poorest performing user at the base station. Analytic results as well as further simulation results are provided to support our arguments.

The antenna array asynchronous interference cancellation problem is addressed by means of semi-blind algorithms with projections to the finite alphabet. It has been observed that the conventional least squares (LS) solution estimated over the training interval may not be suitable for initialization of iterative semi-blind schemes in the case of asynchronous interference. Unlike the synchronous case, a modified LS initialization based on the autocorrelation matrix estimated over the whole burst of data outperforms the conventional LS initialization for the high interference level. We propose a re-configurable receiver which exploits on-line selection of the initialization. Its efficiency is demonstrated in TDMA and OFDM environments.

In this paper, we discuss some of the most basic architectural superstructures for wireless links with multiple antennas: M at the transmit site and N at the receive site. Toward leveraging the gains of the last half century of coding theory, we emphasize those structures that can be composed using spatially one dimensional coders and decoders. These structures are investigated primarily under a probability of outage constraint. The random matrix channel is assumed to hold steady for such a large number of M-dimensional vector symbol transmission times, that an infinite time horizon Shannon analysis provides useful insights. The resulting extraordinary capacities are contrasted for architectures that differ in the way that they manage self-interference in the presence of additive receiver noise. A universally optimal architecture with a diagonal space-time layering is treated, as is an architecture with horizontal space-time layering and an architecture with a single outer code. Some capacity asymptotes for large numbers of antennas are also included. Some results for frequency selective channels are presented: It is only necessary to feedback M rates, one per transmit antenna, to attain capacity. Also, capacity of an (M,N) link is, in a certain sense, invariant with respect to signaling format.

In this letter, we show that the performance of recently proposed quasi-orthogonal space-time codes can be improved by phase-shifting the constellations of the symbols constituting the code. The optimal rotation of the symbols increases the minimum distance of the corresponding space-time codewords, leading to substantially improved performance.

The design of space-time codes that are capable of approaching the capacity of multiple-input-single-output (MISO) antenna systems is a challenging problem, yet one of high practical importance. While a remarkably simple scheme of Alamouti (1998) is capable of attaining the channel capacity in the case of two-transmitter and one-receiver antennas (2,1), no such schemes are known for the case of more than two transmitter antennas. We propose a family of space-time codes that are especially designed for the case of four-transmitter antennas and that are shown to allow the attainment of a significant fraction of the open-loop Shannon capacity of the (4,1) channel.

Orthogonal codes are a class of space-time block codes that achieve full diversity gain, though typically at a loss of code rate. Such codes have simple single-symbol decoders. The code rate can be made higher by constructing quasi-orthogonal codes (such as those proposed last year in [1], [2]) which trade a small loss of performance for full rate coding. In this paper, which builds on previous work in [1], we propose a novel rotation technique for improving the performance of quasi-orthogonal codes in terms of bit-error rate (BER). Numerical simulations show that significant improvements to previously reported results without rotation can be attained.

The antenna array asynchronous interference cancellation problem is addressed by means of semi-blind algorithms with projections to the finite alphabet. It is observed that the conventional least squares (LS) solution estimated over the training interval may not be suitable for initialization of the iterative semi-blind schemes in the case of asynchronous interference. The simulation results in an OFDM HIPERLAN/2 environment are presented, which demonstrate that, contradictory to the synchronous interference case, a modified LS initialization based on the autocorrelation matrix estimated over the whole burst of data outperforms the conventional LS initialization for high interference levels.

Orthogonal codes are a class of space-time block codes that achieve full diversity, though at a loss of code rate. Such codes have simple single-symbol decoders. The code rate can be made higher by constructing quasi-orthogonal codes, which trade a small loss of performance for full rate coding. Typically, quasi-orthogonal codes perform the best when joint maximum likelihood (ML) decoding is used within subsets of the space-time codewords that are mutually orthogonal. We show that for a particular class of quasi-orthogonal codes, the interference which the subset of the symbols to be jointly decoded sees from other symbols is such that the signal to interference ratio remains constant for all channel realizations. Using the same constellation for all symbols in the subset reduces the minimum distance for such codes and results in a loss of performance. As a remedy to this problem, we introduce a rotation-based method that aims at maximizing the minimum distance in the space-time constellation. Numerical simulations show that significant improvements to previously reported results without rotation can be attained.

Results in information theory have demonstrated the enormous potential of wireless communication systems with antenna arrays at both the transmitter and receiver. To exploit this potential, a number of layered space-time architectures have been proposed. These layered space-time systems transmit parallel data streams, simultaneously and on the same frequency, in a multiple-input multiple-output fashion. With rich multipath propagation, these different streams can be separated at the receiver because of their distinct spatial signatures. However, the analysis of these techniques presented thus far had mostly been strictly narrowband. In order to enable high-data-rate applications, it might be necessary to utilize signals whose bandwidth exceeds the coherence bandwidth of the channel, which brings in the issue of frequency selectivity. In this paper, we present a class of layered space-time receivers devised for frequency-selective channels. These new receivers, which offer various performance and complexity tradeoffs, are compared and evaluated in the context of a typical urban channel with excellent results.

We demonstrate an experimental evaluation of unsupervised (i.e., blind) channel deconvolution that is based on the multi-user kurtosis (MUK) maximization criterion. We focus on the narrowband case and compare the performance of the MUK algorithm against the conventional trained linear MMSE and the V-BLAST algorithm. These results constitute, to the best of our knowledge, the first over-the-air demonstration of blind techniques for multiple-transmitter/multiple-receiver systems.

We propose a novel transmit diversity scheme for the downlink of communication systems that employ four transmit antennas. The scheme can be seen as a simplified transmission architecture admitting an entire family of space-time codes. It can be also seen as an extension of previously proposed techniques (such as those presented in Alamouti (1998), Tarokh et al. (1998), and Hochwald et al. (2001)) to the case of four transmit antennas with complex input data symbols. Our technique has a number of appealing features, namely, it enables a significant portion of the open-loop channel capacity, it requires simple receiver processing (involving typically 2/spl times/2 matrix operations in conjunction with single-user or 2-user decoding) and it admits single-user encoding in an overlay fashion.

We present a transmit diversity technique for the downlink of (wideband) direct-sequence (DS) code division multiple access (CDMA) systems. The technique, called space-time spreading (STS), improves the downlink performance by using a small number of antenna elements at the base and one or more antennas at the handset, in conjunction with a novel spreading scheme that is inspired by space-time codes. It spreads each signal in a balanced way over the transmitter antenna elements to provide maximal path diversity at the receiver. In doing so, no extra spreading codes, transmit power or channel information are required at the transmitter and only minimal extra hardware complexity at both sides of the link. Both our analysis and simulation results show significant performance gains over conventional single-antenna systems and other open-loop transmit diversity techniques. Our approach is a practical way to increase the bit rate and/or improve the quality and range in the downlink of either mobile or fixed CDMA systems. A STS-based proposal for the case of two transmitter and single-receiver antennas has been accepted and will be included as an optional diversity mode in release A of the IS-2000 wideband CDMA standard.

We consider the problem of detecting synchronous code division multiple access (CDMA) signals in multipath channels that result in multiple access interference (MAI). It is well known that such challenging conditions may create severe near-far situations in which the standard techniques of combined power control and temporal single-user RAKE receivers provide poor performance. To address the shortcomings of the RAKE receiver, multiple antenna receivers combining space-time processing with multiuser detection have been proposed in the literature. Specifically, a space-time detector based on minimizing the mean-squared output between the data stream and the linear combiner output has shown great potential in achieving good near-far performance with much less complexity than the optimum space-time multiuser detector. Moreover, this space-time minimum mean-squared error (ST-MMSE) multiuser detector has the additional advantage of being well suited for adaptive implementation. We propose novel trained and blind adaptive algorithms based on stochastic gradient techniques, which are shown to approximate the ST-MMSE solution without requiring knowledge of the channel. We show that these linear space-time detectors can potentially provide significant capacity enhancements (up to one order of magnitude) over the conventional temporal single-user RAKE receiver.

In earlier work we presented a set of necessary and sufficient conditions for the blind separation of a number of independent identically distributed (i.i.d.) source signals that share the same distribution and are mutually independent. We present an algorithm for implementing the multi-user Kurtosis (MUK) constrained optimization criterion suggested by these conditions. The algorithm is derived directly from the MUK cost function via a stochastic-gradient update at each iteration, followed by a Gram-Schmidt orthogonalization to project onto the criterion's constraint. A convergence analysis of the derived algorithm reveals that it is globally convergent (in the absence of noise) to a desired setting that recovers all the input sources, up to an arbitrary phase rotation each.

Multiple antennas and space-time processing are known to provide large link-level capacity gains. In this paper we investigate the system-level impact of using antenna arrays with up to four elements at both transmitter and receiver in a downlink CDMA system. We consider the following uses for multiple transmit antennas: transmit diversity, BLAST transmission (using the same spreading code to radiate independent data from different antennas), and directive beam steering. Link spectral efficiencies can be calculated as a function of the required signal-to-interference ratio (SIR) assuming capacity-approaching channel coding. System-level simulations provide the probability distribution of received SIR in a multi-cell CDMA system, with and without directive beam steering. The link- and system-level results are then combined to yield the number of equal-rate users that can be supported at some outage level. We show that 10 fold increases in user capacity can be achieved when up to four antenna elements are used on each side of the link (assuming a per-user rate of 1.25 Mbps and a 5-MHz bandwidth).

We consider the problem of linear polyphase blind equalization (BE), i.e. we are interested in equalizing the output of a single-input-multiple-output (SIMO) channel, without observing its input. A previous result by Liu and Dong (see IEEE Trans. on Circuits and Systems, vol.44, no.5, 1997) showed that if the sub-channel polynomials are co-prime in the z-domain, then the equalizer output whiteness is necessary and sufficient for the equalization of a white input. Based on this observation, we propose a simple decorrelation criterion for second-order based BE. Due to its second-order nature, this criterion is insensitive to the distance of the input from Gaussianity, hence it achieves BE even for Gaussian or non-Gaussian inputs. Moreover, unlike other second-order techniques, our approach bypasses channel estimation and computes directly the equalizer. By doing so, it avoids the problem of ill-conditioning due to channel order mismatch which is crucial to other techniques. Combined to its good convergence properties, these characteristics make the proposed technique an attractive option for robust polyphase BE, as evidenced by both our analysis and computer simulation results.

To guarantee low correlations among user signatures in the reverse-link at the base station, we propose an adaptive algorithm to jointly update the user signatures. Making use of the wireless channel information, we iteratively reassign the spreading signature of the users with the minimum SINR (signal to interference-plus-noise ratio). As shown by simulation results, the proposed algorithm is likely to provide signatures which are orthogonal among users if the number of users is small, then multi-user detection is no longer required. When the number of users is large, the proposed algorithm still tries to maintain equal distances among user signatures, and thus improves the condition of the channel matrix and brings about an increase of capacity by up to 3-4 times, as compared to the same receivers with random codes.

We consider the problem of separating adaptively p synchronous user signals that are received by an m-element antenna array without the use of training sequences. We establish a set of necessary and sufficient conditions for perfect recovery of all the transmitted signals. Based on these conditions we propose optimization criteria that lead to adaptive algorithms for efficient blind source separation of non-Gaussian signals. Convergence analysis shows important global convergence properties of the proposed techniques. Combined with their low complexity, these features make the proposed algorithms good candidates for adaptive source separation.

We derive and evaluate the performance of two minimum mean-squared error (MMSE) multiuser multi-antenna detectors for multipath channels. We consider the case of synchronous BPSK data signals for which the two detectors differ in the order of the "real" operation (r) and the linear transformation (T) for mitigating multi-access interference. In the adaptive implementations of these detectors, the Tr detector does not require prior channel estimates whereas the rT does. We show that as the noise floor vanishes, these MMSE detectors are equivalent to respective rT and Tr decorrelating (zero-forcing) detectors. If the channel parameters are known exactly, we show that the performance of the rT decorrelating detector uniformly outperforms the Tr decorrelator. Semi-analytic results demonstrate the capacity gains achieved using these multiantenna detectors.

We consider the problem of global convergence of Godard (1980) equalizers in the special case of binary (2-PAM) input signals, when the channel impulse response is complex. We present a class of global minima of all Godard equalizers for this case, which do not correspond to settings free of intersymbol-interference (ISI). The equalizer output corresponding to these global minima appears as a four-point constellation in the complex plane, however it is easily shown that the decomposition in its real and imaginary part provides two ISI-free versions of the transmitted signal. In the case of multi-user constant modulus algorithms, the situation is somewhat more complicated: the real and imaginary parts of each equalizer output after convergence, may correspond to different user signals. These results can be extended to other types of real input signals.

Recently, a number of classes of multipath channels which are not blindly identifiable from fractionally spaced samples and second-order cyclic spectra have been presented. In this paper, we consider the blind identification problem of these channels using multiple antennas and show that they will not in general give rise to any common roots among the sub-channels formed from the antennas, and hence, they can be identified from second-order statistics.

The consider the problem of recovering p synchronous communication signals that are transmitted through a multiple-input/multiple-output (MIMO) linear channel and are, therefore, received in the presence of both interuser (IUI) and intersymbol interference (ISI). A multichannel linear equalization approach is taken, and we propose to adjust the equalizer coefficients with a blind adaptive algorithm (without the use of training data). This multiuser constant modulus algorithm (MU-CMA) is derived from the minimization of a cost function that penalizes deviations of the equalized signals from the constant modulus property as well as cross-correlations between them. The proposed scheme appears to be an appealing technique for multiuser blind equalization that combines good convergence properties with low computational complexity.

Recently, Ding (see IEEE Signal Processing Lett., vol.3, p.150-2, May 1996) has pointed out several classes of multipath channels that are not blindly identifiable from fractionally spaced samples and second-order cyclic spectra. In this letter, we consider the blind identification problem using multiple antennas and show that the multipath channels will not give rise to any common roots among the subchannels formed from the antennas and, hence, they can be identified from second-order statistics. In our development, we will point out the role of band-limitedness of the channels in characterizing different classes.

Slock and Papadias (1994) showed that in the case of multiple antennas and/or oversampling, FIR ZF equalizers exist for FIR channels and can be obtained from the noise-free linear prediction (LP) problem. The LP problem also leads to a minimal parameterization of the noise subspace, which was used to solve the deterministic maximum likelihood (DML) channel estimation problem. The present authors provide further contributions along two lines. One is a number of blind equalization techniques of the adaptive filtering type. They also present some robustifying modifications of the DML problem.

We present a new class of adaptive filtering algorithms for blind equalization of constant modulus signals. The algorithms are first derived in a classical system identification context by minimizing at each iteration a deterministic criterion and then their counterpart for blind equalization is derived by modifying this criterion taking into account the constant-modulus property of the transmitted signal. The algorithms impose more constraints than the classical constant modulus algorithm (CMA) and as a result achieve faster convergence. An asymptotic analysis has provided useful parameter bounds that guarantee the algorithms' stability. A priori knowledge of these bounds helps the algorithms escape from undesirable local minima of their cost function thus giving them a potential advantage over the classical CMA. An efficient computational organization for the derived algorithms is also proposed and their behaviour has been tested by means of computer simulations.>

Equalization for digital communications constitutes a very particular blind deconvolution problem in that the received signal is cyclostationary. Oversampling (OS) (w.r.t. the symbol rate) of the cyclostationary received signal leads to a stationary vector-valued signal (polyphase representation (PR)). OS also leads to a fractionally-spaced channel model and equalizer. In the PR, channel and equalizer can be considered as an analysis and synthesis filter bank. Zero-forcing (ZF) equalization corresponds to a perfect-reconstruction filter bank. We show that in the OS case FIR ZF equalizers exist for a FIR channel. In the PR, the noise-free multichannel power spectral density matrix has rank one and the channel can be found as the (minimum-phase) spectral factor. The multichannel linear prediction of the noiseless received signal becomes singular eventually, reminiscent of the single-channel prediction of a sum of sinusoids. As a result, a ZF equalizer can be determined from the received signal second-order statistics by linear prediction in the noise-free case, and by using a Pisarenko-style modification when there is additive noise. In the given data case, Music (subspace) or ML techniques can be applied. We also present some Cramer-Rao bounds and compare them to the case of channel identification using a training sequence.>