This paper models the line-of-sight (LOS) channel between two continuous circular antennas (CCAs) as a bounded linear normal operator whose kernel is defined by a deployment parameter: the product of the antenna radii divided by the product of the wavelength and transmission distance. Eigendecomposition reveals that orbital angular momentum (OAM) serves as the eigenmodes, with eigenvalues given by Bessel functions of the first kind, evaluated at the deployment parameter. By linking discrete circular arrays to CCAs through spatial sampling, we derive analytical expressions for the singular values of the LOS multiple-input multiple-output (MIMO) channel. The analysis considers two configurations: one where receive antennas form a single uniform circular array (UCA) with a rotational angular offset, and one with multiple sub-UCAs having different angular offsets, in both cases with the number of receive antennas being an integer multiple of the transmit antennas. For each setup, discrete Fourier transform (DFT)-based transceiver structures are proposed to achieve channel capacity. Numerical evaluations reveal: (i) The number of effective spatial degrees of freedom generally increases with the deployment parameter, but not monotonically (for fixed angular offsets); (ii) Channel capacity does not necessarily increase with the deployment parameter when the number of antennas is fixed; (iii) Angular offset significantly impacts performance when the number of antennas is small relative to the parameter; (iv) With a large number of antennas, the singular values of both configurations approach the CCA singular values, and the impact of angular offsets diminishes; (v) The non-uniform configuration studied in this paper yield small or no gains compared to the uniform configuration when angular offsets are optimized.

In this paper, we present a comprehensive foundation for the theory and practice of pilot-based carrier phase synchronization of OFDM symbols in the presence of phase noise. The system covers phase noise added in both the transmitter and receiver together with a frequency-selective channel. A novel, low-complexity, phase noise estimation method is presented, and we show that it is close to optimal over a wide dynamic range of phase noise. Additionally, a method for approximating the phase noise over the OFDM symbol using principal component analysis is proposed, where the number of parameters to estimate can be significantly reduced with minimal impact on performance.

We establish a solid foundation for the theory and practice of pilot-based carrier phase synchronization in line-of-sight (LOS) MIMO systems affected by phase noise. LOS MIMO is a multi-antenna technology used in fixed wireless backhaul systems. As part of this, a realistic and simple oscillator phase-locked loop model is employed. To maximize the rate, a novel pilot-based MMSE estimator is formulated to jointly estimate the received symbols and the unknown phase noise at both the transmitter and receiver. Additionally, we demonstrate that effective power allocation, considering phase noise, is crucial for maximizing the rate in phase noise-limited systems.

We analyze the uplink performance of a distributed massive multiple-input multiple-output (MIMO) architecture in which the remotely located access points (APs) are connected to a central processing unit via a fiber-optical fronthaul carrying a dithered and 1-bit quantized version of the received radio-frequency (RF) signal. The innovative feature of the proposed architecture is that no down-conversion is performed at the APs. This eliminates the need to equip the APs with local oscillators, which may be difficult to synchronize. Under the assumption that a constraint is imposed on the amount of data that can be exchanged across the fiber-optical fronthaul, we investigate the tradeoff between spatial oversampling, defined in terms of the total number of APs, and temporal oversampling, defined in terms of the oversampling factor selected at the central processing unit, to facilitate the recovery of the transmitted signal from 1-bit samples of the RF received signal. Using the so-called error-vector magnitude (EVM) as performance metric, we shed light on the optimal design of the dither signal, and quantify, for a given number of APs, the minimum fronthaul rate required for our proposed distributed massive MIMO architecture to outperform a standard co-located massive MIMO architecture in terms of EVM.

The Shannon capacity for the line-of-sight (LOS) multiple-input multiple-output (MIMO) channel between two perfectly aligned uniform circular arrays (UCAs) is derived from first principles in a tutorial fashion. It is well known that harmonically related complex exponentials (also known in the literature as orbital angular momentum (OAM) modes) are eigenmodes for the spatially continuous channel. We show that the corresponding eigenvalues can be expressed as Bessel functions of the first kind. We also show that the spatially discrete channel between two UCAs with the same finite number of Hertzian dipole antennas on both sides has eigenmodes that are spatially sampled continuous OAM modes, and discrete eigenvalues that are aliased versions of the continuous eigenvalues. Through numerical solution of Maxwell's equations, we verify that the discrete eigenvalues for UCAs with realistic dipole antennas are the same as with the Hertzian dipoles for the studied geometries (1 km hop distance, UCA radius 1 and 2 m, carrier frequency 70 GHz) as long as antenna spacing is not very dense.

This paper considers the uplink of a single-cell multi-user massive multiple-input multiple-output (MIMO) system. Each receiver antenna of the base station is assumed to be equipped with a pair of analog-to-digital converters (ADCs) to quantize the real and imaginary part of the received signal. We propose a novel Bussgang-based weighted zero-forcing (B-WZF) receiver, which distinguishes the clipping and granular distortion. Numerical results demonstrate that for sufficiently high SNR and users that do not experience deep large-scale fading, the B-WZF brings significant performance gain over existing linear receivers in the literature, when the training sequence length is higher than the number of users.

This paper considers the uplink of a single-cell multiuser massive multiple-input multiple-output system. Each receiver antenna of the base station (BS) is assumed to be equipped with a pair of analog-to-digital converters to quantize the real and imaginary part of the received signal. We propose a novel clipping-aware receiver (CA-MMSE), which performs minimum mean square error (MMSE) reconstruction only on the clipped received samples, while the granular samples are left unchanged after the quantization. On this basis, we present an iterative algorithm to implement the CA-MMSE receiver and derive a sufficient condition for its geometrical convergence to a fixed point. We show that as long as the number of BS antennas or the quantization resolution is sufficiently high, then, the performance of the CA-MMSE is as good as the optimal MMSE receiver which reconstructs all quantized received symbols. Additionally, we propose a novel Bussgang-based weighted zero-forcing (B-WZF) receiver which distinguishes the clipping and granular distortion and it is shown that as long as the received training symbols per antenna are correlated, the CA-MMSE brings significant improvements compared to conventional receivers in the literature while for users that do not experience deep large-scale fading the simpler B-WZF is near to the CA-MMSE for sufficiently high signal-to-noise ratio and quantization resolution.

We consider the downlink of a massive multiuser (MU) multiple-input multiple-output (MIMO) system in which the base station (BS) is equipped with low-resolution digital-to-analog converters (DACs). In contrast to most existing results, we assume that the system operates over a frequency-selective wideband channel and uses orthogonal frequency division multiplexing (OFDM) to simplify equalization at the user equipments (UEs). Furthermore, we consider the practically relevant case of oversampling DACs. We theoretically analyze the uncoded bit error rate (BER) performance with linear precoders (e.g., zero forcing) and quadrature phase-shift keying using Bussgang's theorem. We also develop a lower bound on the information-theoretic sum-rate throughput achievable with Gaussian inputs, which can be evaluated in closed form for the case of 1-bit DACs. For the case of multi-bit DACs, we derive approximate, yet accurate, expressions for the distortion caused by low-precision DACs, which can be used to establish the lower bounds on the corresponding sum-rate throughput. Our results demonstrate that, for a massive MU-MIMO-OFDM system with a 128-antenna BS serving 16 UEs, only 3-4 DAC bits are required to achieve an uncoded BER of 10-4with a negligible performance loss compared to the infinite-resolution case at the cost of additional out-of-band emissions. Furthermore, our results highlight the importance of considering the inherent spatial and temporal correlations caused by low-precision DACs.

We consider a bi-directional point-to-point links and study the data transmission efficiency of frequency division duplex (FDD) and TDD (T: time) schemes with a bursty communication model. We use the recent results on the achievable rates of finite-length codes to analyze the end-to-end throughput and the data payload for TDD and FDD in the cases with codewords of finite length including the impact of guard time for TDD and guard bands for FDD. Also, in case of TDD we study the impact of adaptive resource allocation on the link throughput. As we demonstrate, TDD-based adaptive resource allocation based on the data traffic improves the performance over non-adaptive TDD and FDD schemes significantly. For instance, consider the data rates 0.1 and 1 bit/symbol and data request probabilities 0.2 and 0.6 in the two different directions, respectively, and Rayleigh fading conditions. Then, for a broad range of codewords lengths and moderate/high signal-to-noise ratios, the implementation of adaptive TDD improves the link throughput, compared to the nonadaptive duplexing by more than 50%.

Massive multiuser (MU) multiple-input multiple- output (MIMO) is foreseen to be a key technology in future wireless communication systems. In this paper, we analyze the downlink performance of an orthogonal frequency division multiplexing (OFDM)-based massive MU-MIMO system in which the base station (BS) is equipped with 1-bit digital-to-analog converters (DACs). Using Bussgang's theorem, we characterize the performance achievable with linear precoders (such as maximal-ratio transmission and zero forcing) in terms of bit error rate (BER). Our analysis accounts for the possibility of oversampling the time-domain transmit signal before the DACs. We further develop a lower bound on the information-theoretic sum-rate throughput achievable with Gaussian inputs. Our results suggest that the performance achievable with 1-bit DACs in a massive MU-MIMO- OFDM downlink are satisfactory provided that the number of BS antennas is sufficiently large.

Hybrid beamforming (HBF) is a potential solution to reduce the baseband hardware cost in massive multiple-input multiple-output (MIMO) systems that has drawn considerable attention recently. In this paper, we consider the uplink of a multiuser massive MIMO system in the presence of blockers. Such blockers, which arise from, for example, users served by other non-cooperative base stations (BSs), can limit the system performance if not handled properly. We propose a HBF scheme that can remove the impact of blockers, while preserving signals from intended users. Specifically, in our two-step receive beamforming scheme, the analog beamformer (ABF) is designed based on channel covariance matrices to minimize the powers of blockers, while the digital beamformer (DBF) deals with inter-user interference. We propose an iterative algorithm that efficiently gives a good sub-optimal solution to the NP-hard problem in the ABF design. Moreover, we consider a more complete BS architecture by incorporating automatic gain control (AGC) and analog-to-digital converter (ADC). As we show in the simulations, for a system with full-precision ADCs, our scheme approaches the sum rate of an ideal fully-digital system. Interestingly, for a system with low-resolution ADCs, our HBF scheme can even outperform a fully-digital system.

This paper studies the impact of in-phase and quadrature imbalance (IQI) on the downlink of a single-cell multiuser multiple-input multiple-output (MU-MIMO) system with large antenna arrays. Moreover, we consider a time-division duplex (TDD) system where we assume uplink/downlink channel reciprocity in the downlink precoding design. We study the impact of uplink/downlink channel mismatch on the downlink rate caused by different IQI at the base station (BS) and users equipment (UEs). A tractable analytical expression to predict the achievable downlink rates is derived for the regularized zero-forcing (RZF) and based on this expression, we prove that, as the number of BS antennas grow large, the achievable downlink rate of each UE is limited either by the RX IQI at the UEs or by the simultaneous presence of the transmit/receive IQI at the BS and TX IQI at the UEs, when there is uplink/downlink channel mismatch.

In this work we evaluate the potential of using access-integrated backhaul in a fixed wireless access (FWA) use case. FWA is considered as a potential use case for early 5G deployment. The system is deployed in the 28 GHz band to provide FWA to residential houses in a suburban scenario where the access points (APs) are deployed on utility poles. It is assumed that only a small fraction of the APs has dedicated backhaul transport (e.g. fiber) and the remainder of the APs are instead backhauled wirelessly by using access-integrated backhaul. The access-integrated backhaul shares the radio resources with the FWA and consumes a substantial part of the available resources especially when multi-hop backhaul is considered. The backhaul aggregation points quickly become the bottle necks since they consume a majority of the radio resources. However, when considering the amount of spectrum that is available at 28 GHz then serving at least 25 Mbps in aggregated constant DL/UL traffic to houses seems feasible. This is accomplished by having less than 20% of the APs connected with dedicated backhaul while the rest of the APs are using access-integrated backhaul.

Massive multiuser (MU) multiple-input multiple-output (MIMO) is foreseen to be one of the key technologies in fifth-generation wireless communication systems. In this paper, we investigate the problem of downlink precoding for a narrowband massive MU-MIMO system with low-resolution digital-to-analog converters (DACs) at the base station (BS). We analyze the performance of linear precoders, such as maximal-ratio transmission and zero-forcing, subject to coarse quantization. Using Bussgang's theorem, we derive a closed-form approximation on the rate achievable under such coarse quantization. Our results reveal that the performance attainable with infinite-resolution DACs can be approached using DACs having only 3-4 bits of resolution, depending on the number of BS antennas and the number of user equipments (UEs). For the case of 1-bit DACs, we also propose novel nonlinear precoding algorithms that significantly outperform linear precoders at the cost of an increased computational complexity. Specifically, we show that nonlinear precoding incurs only a 3 dB penalty compared with the infinite-resolution case for an uncoded bit-error rate of 10-3, in a system with 128 BS antennas that uses 1-bit DACs and serves 16 single-antenna UEs. In contrast, the penalty for linear precoders is about 8dB.

In this paper, we study the impact of in-phase and quadrature imbalance (IQI) on single-cell multiuser multiple-input multiple-output systems with large antenna arrays. Moreover, we consider a time-division duplex system, where we assume uplink/downlink channel reciprocity in the downlink precoding design. First, we investigate the effect of transceiver IQI on the uplink channel estimation by deriving the linear minimum-mean-square-error estimator for the IQ-impaired model and prove that only the receiver IQI at the base station (BS) limits the estimation accuracy. Then, we study the impact of uplink/downlink channel mismatch on the downlink rate caused by different IQI at the BS and user equipments (UEs). We prove that the achievable downlink rate of each UE is limited either by the receiver IQI at the UEs or jointly by the transmit and receive IQI at the BS, when there is mismatch between the uplink and downlink channels.

We investigate the uplink throughput achievable by a multiple-user (MU) massive multiple-input multiple-output (MIMO) system, in which the base station is equipped with a large number of low-resolution analog-to-digital converters (ADCs). Our focus is on the case where neither the transmitter nor the receiver have any a priori channel state information. This implies that the fading realizations have to be learned through pilot transmission followed by channel estimation at the receiver, based on coarsely quantized observations. We propose a novel channel estimator, based on Bussgang's decomposition, and a novel approximation to the rate achievable with finite-resolution ADCs, both for the case of finite-cardinality constellations and of Gaussian inputs, that is accurate for a broad range of system parameters. Through numerical results, we illustrate that, for the 1-bit quantized case, pilot-based channel estimation together with maximal-ratio combing, or zero-forcing detection enables reliable multi-user communication with high-order constellations, in spite of the severe nonlinearity introduced by the ADCs. Furthermore, we show that the rate achievable in the infinite-resolution (no quantization) case can be approached using ADCs with only a few bits of resolution. We finally investigate the robustness of low-ADC-resolution MU-MIMO uplink against receive power imbalances between the different users, caused for example by imperfect power control.

This study focuses on the coexistence between 5G networks and Fixed Services (FS), where fixed links (FL) is one application. 5G is expected to require spectrum in high frequency ranges and fixed services is a highly probable candidate to share spectrum with. Most of the spectrum is co-primary allocated to both mobile and fixed. This study gives assessment on the inference to/from the fixed link, and identifies areas for further study. The results indicate that the interference that 5G radiates to the fixed link is higher than the requirement in the co- channel case. However a low traffic load at 5G together with beamforming is the best scenario with a 30\% probability of interference. One possibility to reduce the probability of interference to 6\% is to increase antenna directivity of the fixed link's. This can be a valid solution to be applied for operators owning both fixed and 5G networks. The interference from fixed link to 5G downlink is below the allowed limit and it is found that at 5G downlink the main contributor to the aggregated interference is the intra network interference. The interference scenario can be improved by utilizing coordination protocols with beam- steering, and advanced antennas. Operators can also consider to deploy in a coordinated manner, or even using other deployments type like micro or indoor.

In this paper, we consider the uplink of a single-cell multi-user single-input multiple-output (MU-SIMO) system with in-phase and quadrature-phase imbalance (IQI). In particular, we investigate the effect of receive (RX) IQI on the performance of MU-SIMO systems with large antenna arrays employing maximum-ratio combining receivers. In order to study how IQI affects channel estimation, we derive a new channel estimator for the IQI-impaired model and show that the higher the value of signal-to-noise ratio, the higher the impact of IQI on the spectral efficiency (SE). Moreover, a novel pilot-based joint estimator of the augmented multiple-input multiple-output (MIMO) channel matrix and IQI coefficients is described, and then, a low-complexity IQI compensation scheme is proposed, which is based on the IQI coefficients' estimation and it is independent of the channel gain. The performance of the proposed compensation scheme is analytically evaluated by deriving a tractable approximation of the ergodic SE assuming transmission over Rayleigh fading channels with large-scale fading. Furthermore, we investigate how many mobile stations should be scheduled in massive MIMO systems with IQI and show that the highest SE loss occurs at the optimal operating point. Finally, by deriving asymptotic power scaling laws and proving that the SE loss due to IQI is asymptotically independent of the number of BS antennas, we show that massive MIMO is resilient to the effect of RX IQI.

In this paper, we consider the uplink of a single-cell massive multiple-input multiple-output (MIMO) system with inphase and quadrature-phase imbalance (IQI). This scenario is of particular importance in massive MIMO systems, where the deployment of lower-cost, lower-quality components is desirable to make massive MIMO a viable technology. Particularly, we investigate the effect of IQI on the performance of massive MIMO employing maximum-ratio combining (MRC) receivers. In order to study how IQI affects channel estimation, we derive a new channel estimator for the IQI-impaired model and show that IQI can substantially downgrade the performance of MRC receivers. Moreover, a low-complexity IQI compensation scheme, suitable for massive MIMO, is proposed which is based on the IQI coefficients' estimation and it is independent of the channel gain. The performance of the proposed compensation scheme is analytically evaluated by deriving a tractable approximation of the ergodic achievable rate and providing the asymptotic power scaling laws assuming transmission over Rayleigh fading channels with log-normal large-scale fading. Finally, we show that massive MIMO effectively suppresses the residual IQI effects, as long as, the compensation scheme is applied.

Radio-frequency (RF) impairments, which intimately exist in wireless communication systems, can severely limit the performance of multiple-input-multiple-output (MIMO) systems. Although we can resort to compensation schemes to mitigate some of these impairments, a certain amount of residual impairments always persists. In this paper, we consider a training-based point-to-point MIMO system with residual transmit RF impairments (RTRI) using spatial multiplexing transmission. Specifically, we derive a new linear channel estimator for the proposed model, and show that RTRI create an estimation error floor in the high signal-to-noise ratio (SNR) regime. Moreover, we derive closed-form expressions for the signal-to-noise-plus-interference ratio (SINR) distributions, along with analytical expressions for the ergodic achievable rates of zero-forcing, maximum ratio combining, and minimum mean-squared error receivers, respectively. In addition, we optimize the ergodic achievable rates with respect to the training sequence length and demonstrate that finite dimensional systems with RTRI generally require more training at high SNRs than those with ideal hardware. Finally, we extend our analysis to large-scale MIMO configurations, and derive deterministic equivalents of the ergodic achievable rates. It is shown that, by deploying large receive antenna arrays, the extra training requirements due to RTRI can be eliminated. In fact, with a sufficiently large number of receive antennas, systems with RTRI may even need less training than systems with ideal hardware.

Radio-frequency (RF) impairments in the transceiver hardware of communication systems (e.g., phase noise (PN), high power amplifier (HPA) nonlinearities, or in-phase/quadrature-phase (I/Q) imbalance) can severely degrade the performance of traditional multiple-input multiple-output (MIMO) systems. Although calibration algorithms can partially compensate these impairments, the remaining distortion still has substantial impact. Despite this, most prior works have not analyzed this type of distortion. In this paper, we investigate the impact of residual transceiver hardware impairments on the MIMO system performance. In particular, we consider a transceiver impairment model, which has been experimentally validated, and derive analytical ergodic capacity expressions for both exact and high signal-to-noise ratios (SNRs). We demonstrate that the capacity saturates in the high-SNR regime, thereby creating a finite capacity ceiling. We also present a linear approximation for the ergodic capacity in the low-SNR regime, and show that impairments have only a second-order impact on the capacity. Furthermore, we analyze the effect of transceiver impairments on large-scale MIMO systems; interestingly, we prove that if one increases the number of antennas at one side only, the capacity behaves similar to the finite-dimensional case. On the contrary, if the number of antennas on both sides increases with a fixed ratio, the capacity ceiling vanishes; thus, impairments cause only a bounded offset in the capacity compared to the ideal transceiver hardware case.

Radio-frequency (RF) impairments, that exist intimately in wireless communications systems, can severely degrade the performance of traditional multiple-input multiple-output (MIMO) systems. Although compensation schemes can cancel out part of these RF impairments, there still remains a certain amount of impairments. These residual impairments have fundamental impact on the MIMO system performance. However, most of the previous works have neglected this factor. In this paper, a training-based MIMO system with residual transmit RF impairments (RTRI) is considered. In particular, we derive a new channel estimator for the proposed model, and find that RTRI can create an irreducible estimation error floor. Moreover, we show that, in the presence of RTRI, the optimal training sequence length can be larger than the number of transmit antennas, especially in the low and high signal-to-noise ratio (SNR) regimes. An increase in the proposed approximated achievable rate is also observed by adopting the optimal training sequence length. When the training and data symbol powers are required to be equal, we demonstrate that, at high SNRs, systems with RTRI demand more training, whereas at low SNRs, such demands are nearly the same for all practical levels of RTRI.

We consider downlink transmission in a cellular network consisting of multi-antenna base stations (BSs), single-antenna mobile users, directional antennas each with a vertically adjustable beam, and control signaling delays in feedback and backhaul links. We propose a novel transmission technique in which intercell interference management is performed via coordinating the beamforming jointly in the horizontal and vertical planes of the wireless channel, denoted as coordinated 3D beamforming. In the horizontal plane, we focus on intercell interference cancelation (ICIC) and investigate its performance when the provided channel state information (CSI) is impaired due to delay/mobility. It is demonstrated that the superiority of ICIC over conventional intracell maximum ratio transmission is highly dependent on the CSI accuracy. In the vertical plane, we consider intercell interference control via coordinatively adapting the elevation angle of the BS antenna pattern, denoted as tilt, to the locations of the scheduled users. It is shown that with perfect CSI interference management should be performed in the horizontal plane using ICIC, while at high delay/mobility it should be done in the vertical plane via coordinated tilt adaptation. For intermediate values of delay/mobility, joint interference management in both planes is required.

In this paper we present a study on the applicability and performance of microwave backhauling of small-cells in a heterogeneous network. Microwave backhaul in non-line-of-sight (NLOS) between a hub and a client provides a cost efficient and flexible small-cell deployment. In contrast to conventional NLOS communications using sub-6 GHz frequencies we propose the use of super-6 GHz frequencies which offers high antenna gain with reasonably sized antennas and wide bandwidths in licensed spectrum. We study both Point-to-Point (PtP) and Point-to-Multi-Point (PtMP) system concepts. The PtP system is characterized by pencil beam antennas with unshared radio resources for each link. The PtMP system is characterized by a single wide-beam antenna system at the hub with radio resources that are shared between multiple clients.

In this paper we investigate the feasibility of using microwave frequencies for fixed non-line-of-sight wireless backhauling connecting small-cell radio base stations with an aggregation node in an outdoor urban environment, i.e. a typical heterogeneous network scenario. We study system level simulations for a point-to-point system where the wave propagation is based on diffraction over rooftops. We further investigate the effects of carrier frequency, interference, antenna height, rain, and tolerance to antenna alignment errors. It is found that the higher frequencies offer not only larger bandwidths but also higher antenna gains which would ideally work to their advantage. However, these advantages may be lost when taking antenna alignment errors and rain into account. Different frequencies simply have their different trade-offs.

We study the downlink of a multicell MIMO system where clusters of multi-antenna base stations jointly serve multiple single-antenna users, commonly referred to as a network MIMO system. Most of the previous studies on network MIMO have only considered the azimuth pattern of the antenna, while ignoring the elevation pattern. In this paper, we consider both the azimuth and the elevation patterns and investigate the impact of the elevation angle tuning parameter, denoted as the antenna tilt, on the performance of such systems. Using system simulations, it is shown that the promised performance gains of network MIMO systems over conventional non-coordinated systems, crucially depend on the choice of the right tilt setting including the tilt type, i.e., mechanical or electrical, and the tilt angle. In particular, for tilt angles smaller than the optimum, network MIMO with intra-site coordination performs almost as well as the conventional system; while for tilt angles larger than the optimum, the performance of network MIMO with intra-site is similar to that of network MIMO with inter-site coordination.

In this paper, we present a channel estimation scheme for Amplify-and-Forward (AF) relaying systems, using measurements at the destination only. A Least-Squares (LS) based channel estimation algorithm is developed, that provides the destination with full knowledge of all channel responses involved in the transmission. To investigate the algorithm performance, the Cramer-Rao lower bound (CRB) is analytically computed and compared with the asymptotic covariance of the proposed estimator. Since the existing estimator does not reach the CRB, we also propose and analyze an improved algorithm by taking into account the noise characteristics via weighted LS (WLS). The improved algorithm is asymptotically efficient, since it attains the CRB as the SNR tends to infinity.

In this paper the downlink of a multi-user MIMO (MUMIMO) system with multi-mode transmission is considered. We propose a low-complexity algorithm for selecting users and the corresponding number of data streams to each user, denoted as user transmission mode (UTM). The selection is only based on the average received signal-to-noise ratio (SNR) from the base station (BS) for each user. This reduces the overall amount of feedback for scheduling, as opposed to techniques that assume perfect instantaneous channel state information (CSI) from all users. Analytical average throughput approximations are derived for each user at different UTMs. Simulation results demonstrate that the proposed algorithm provides performance close to dirty paper coding (DPC) with considerably reduced feedback.

In this paper we present results from a outdoor-to-indoor MIMO measurement campaign where we study the effect of repeaters on singular values, spatial richness, capacity, and delay spread distributions. We present results from different repeater scenarios such as, e.g. different outdoor/indoor repeater deployments with single/dual polarized antennas. The measurements show that repeaters significantly enhance the received SNR while they increase the delay spread and decrease the spatial richness of the MIMO channel. However, the main conclusion is that a significant increase in channel capacity is attained when deploying repeaters mostly thanks to their ability to provide spatial multiplexing over the high-quality eigenmodes they may provide. The number of such eigenmodes is limited by the number of repeaters, deployment, and their antennas.

Two line-of-sight (LoS) multiple-input multiple-output (MIMO) systems for point-to-point microwave radio links are simulated and analyzed. Both 2 × 2 spatially-separated, single-polarized and 4 × 4 spatially-separated, dual-polarized systems are considered in the presence of a frequency selective and time varying channel. Time dependence is introduced by moving the antennas during the simulation and thereby introducing the need for an adaptive space-time-equalizer (STE). Our results indicate that a time-varying frequency selective LoS MIMO channel puts higher requirements on the STE and introduces a higher SNR penalty compared to a single-input single-output (SISO) system.

In this work the modeling and capacity of a dual polarized (DP) MIMO channel is addressed. The modeling includes channel parameters such as receive and transmit correlation, channel cross-polarization discrimination (XPD), and antenna parameters such as polarization state, polarization parallelity and coupling. The capacity of the DP MIMO channel is evaluated and compared to the capacity of a single polarized (SP) MIMO system. The SP MIMO system with spatially separated antenna sensors has the advantage that it also offers array gain and will therefore during idealized conditions outperform the DP MIMO system. However, in this work it is found that this advantage often is reduced and sometimes even lost when channel and antenna imperfections such as, e.g., correlation, channel XPD, and polarization mismatch are introduced. The main conclusion is that DP antennas might not always yield the best MIMO performance, but instead offer compact antenna solutions for mobile devices and robust performance that is more insensitive to the aforementioned imperfections.