Effective spectrum sharing requires a nuanced understanding of how radio activity varies not only across frequency and geography but also with altitude, an increasingly important dimension for drone networks and non-terrestrial systems. This paper presents a comprehensive survey of existing spectrum measurement studies in the sub-6 GHz range, identifying major gaps in coverage, such as limited measurements involving altitude variation, a lack of longitudinal datasets, and the absence of publicly available geotagged aerial data. To address these limitations, we conduct a multi-year spectrum monitoring campaign using an aerial platform equipped with software-defined radios (SDRs), operating in both urban and rural areas of Raleigh, NC, USA. The aerial platform enables high-resolution measurements of spectrum activity from the ground up to 300 m. We analyze occupancy patterns across licensed and unlicensed bands, including Long Term Evolution (LTE), 5G (New Radio) (NR), and Industrial, Scientific, and Medical (ISM) bands, and document year-over-year changes that reflect evolving commercial deployments and regulatory trends. We further perform an altitude-dependent analysis of spectrum occupancy and received power across the 89 MHz–6 GHz range, highlighting how three-dimensional measurement perspectives reveal usage patterns that are not observable from ground-level sensing alone. Our results demonstrate that altitude is a critical dimension for spectrum characterization and should be considered in future spectrum policy, sensing strategies, and system design. This study provides both a literature-based and measurement-based foundation for altitude-aware spectrum analytics, supported by a publicly available geotagged dataset to enable reproducible research for emerging aerial networks and non-terrestrial communication systems.

The rapid evolution of 5G and beyond has advanced space-air-terrestrial networks, with unmanned aerial vehicles (UAVs) offering enhanced coverage, flexible configurations, and cost efficiency. However, deploying UAV-based systems presents challenges including varying propagation conditions and hardware limitations. While simulators and theoretical models have been developed, real-world experimentation is critically important to validate the research. Digital twins, virtual replicas of physical systems, enable emulation that bridge theory and practice. This paper presents our experimental results from AERPAW’s digital twin, showcasing its ability to simulate UAV communication scenarios and providing insights into system performance and reliability.

The ever-growing demand for wireless connectivity, coupled with limited spectrum resources, has resulted in spectrum congestion and interference. This research investigates the probability of occupancy in common sub-6 GHz cellular network bands based on measurements conducted in urban and rural environments. Specifically, we analyze the spectrum occupancy of various long-term evolution (LTE), 5thgeneration (5G) and Citizens Broadband Radio Service (CBRS) bands used in the United States, considering both uplink and downlink transmissions at altitudes up to 180 meters. Additionally, we explore the influence of altitude on the probability of spectrum occupancy in these bands. Our findings reveal that the probability of occupancy is generally higher in the downlink compared to the uplink. Moreover, we observe that line-of-sight (LoS) signals play a critical role in higher altitudes. These results provide insights spectrum utilization in various cellular bands across different altitudes, with implications on interference and spectrum coexistence between terrestrial networks and unmanned aerial systems (UASs) in the future.

The emerging 5G and future 6G technologies are envisioned to provide higher bandwidths and coverage using millimeter wave (mmWave) and sub-Terahertz (THz) frequency bands. The growing demand for higher data rates using these bands can be addressed by overcoming high path loss, especially for non-line-of-sight (NLOS) scenarios. In this work, we investigate the use of passive transparent reflectors to improve signal coverage in an NLOS indoor scenario. Measurements are conducted to characterize the maximum reflectivity property of the transparent reflector using channel sounder equipment from NI. Flat and curved reflectors, each with a size of 16 inches by 16 inches, are used to study coverage improvements with different reflector shapes and orientations. The measurement results using passive metallic reflectors are also compared with the ray-tracing-based simulations, to further corroborate our inferences. The analysis reveals that the transparent reflector outperforms the metal reflector and increases the radio propagation coverage in all three frequencies of interest: 28 GHz, 39 GHz, and 120 GHz. Using transparent reflectors, there is an increase in peak received power that is greater than 5 dB for certain scenarios compared to metallic reflectors when used in flat mode, and greater than 3 dB when used in curved (convex) mode.

Due to the scarcity of spectrum resources, the emergence of new technologies and ever-increasing number of wireless devices operating in the radio frequency spectrum lead to data congestion and interference. In this work, we study the effect of altitude on sub-6 GHz spectrum measurement results obtained at a Helikite flying over two distinct scenarios; i.e., urban and rural environments. Specifically, we aim at investigating the spectrum occupancy of various long-term evolution (LTE), 5thgeneration (5G) and citizens broadband radio service (CBRS) bands utilized in the United States for both uplink and downlink at altitudes up to 180 meters. Our results reveal that generally the mean value of the measured power increases as the altitude increases where the line-of-sight links with nearby base stations is more available. SigMF-compliant spectrum measurement datasets used in this paper covering all the bands between 100 MHz to 6 GHz are also provided.

Subsurface microwave imaging is the image reconstruction of objects buried below the surface of a medium, such as soil. Modeling the interactions between the background medium and objects, as well as artifacts due to the limited view of objects, are the major concerns in the image reconstruction process. In this work, we have presented an efficient subsurface microwave imaging technique for the reconstruction of targets in a two-layered medium with an arbitrary rough interface. The use of a computationally expensive two-layered background Green’s function in the classical integral equation model is avoided by exploiting the boundary data model where only a simple homogeneous Green’s function is required. The contrast source imaging technique is reformulated in terms of boundary data and total variation (TV) regularization is included in the cost function multiplicatively to handle limited view and noisy data in a robust way. Numerical simulations demonstrated that the proposed method dramatically reduces the computational time while keeping the same accuracy in comparison to the classical approach.

Radio dynamic zones (RDZs) are geographically bounded areas where novel advanced wireless technologies can be developed, tested, and improved, without the concern of interfering to other incumbent radio technologies nearby the RDZ. In order to operate an RDZ, use of a real-time spectrum monitoring system carries critical importance. Such a monitoring system should detect out-of-zone (OoZ) signal leakage outside of the RDZ, and if the interference to nearby receivers is intolerable, the monitoring system should be capable of mitigating such interference. This can e.g. be achieved by stopping operations inside the RDZ or switching to other bands for RDZ operation. In this paper, we introduce a spectrum monitoring concept for OoZ signal leakage detection at RDZs, where sensor nodes (SNs) are installed at the boundary of an RDZ and monitor the power leakage from multiple transmitters within the RDZ. We propose a prediction algorithm that estimates the received interference at OoZ geographical locations outside of the RDZ, using the measurements obtained at sparsely located SNs at the RDZ boundary. Using computer simulations, we evaluate the performance of the proposed algorithm and study its sensitivity to SN deployment density.

In the upcoming 5G communication, the millimeter-wave (mmWave) technology will play an important role due to its large bandwidth and high data rate. However, mmWave frequencies have higher free-space path loss (FSPL) in line-of-sight (LOS) propagation compared to the currently used sub-6 GHz frequencies. What is more, in non-line-of-sight (NLOS) propagation, the attenuation of mmWave is larger compared to the lower frequencies, which can seriously degrade the performance. It is therefore necessary to investigate mmWave propagation characteristics for different deployment scenarios of interest, to understand coverage and rate performance in such scenarios. In this paper, we focus on 28 GHz wideband mmWave signal propagation characteristics at Johnston Regional Airport (JNX), a local airport near Raleigh, NC. To collect data, we use an NI PXI-based channel sounder at 28 GHz for indoor, outdoor, and indoor-to-outdoor scenarios. Results on LOS propagation, reflection, penetration, signal coverage, and multipath components (MPCs) show a lower indoor FSPL, a richer scattering, and a better coverage compared to outdoor. We also observe high indoor-to-outdoor propagation losses.

Development of a comprehensive channel propagation model for high-fidelity design and deployment of wireless communication networks necessitates an exhaustive measurement campaign in a variety of operating environments and with different configuration settings. As the campaign is time-consuming and expensive, the effort is typically shared by multiple organizations, inevitably with their own channel-sounder architectures and processing methods. Without proper benchmarking, it cannot be discerned whether observed differences in the measurements are actually due to the varying environments or to discrepancies between the channel sounders themselves. The simplest approach for benchmarking is to transport participant channel sounders to a common environment, collect data, and compare results. Because this is rarely feasible, this paper proposes an alternative methodology - which is both practical and reliable - based on a mathematical system model to represent the channel sounder. The model parameters correspond to the hardware features specific to each system, characterized through precision, in situ calibration to ensure accurate representation; to ensure fair comparison, the model is applied to a ground-truth channel response that is identical for all systems. Five worldwide organizations participated in the cross-validation of their systems through the proposed methodology. Channel sounder descriptions, calibration procedures, and processing methods are provided for each organization as well as results and comparisons for 20 ground-truth channel responses.

Millimeter wave (mmWave) communications can provide high speed data rate for 5G wireless networks, taking advantage of the large bandwidth available at mmWave frequencies. It is also well known that mmWave links may suffer from outages due to non-line-of-sight (NLOS) propagation problems. In this paper, we study the characteristics of IEEE~802.11ad based mmWave systems at 60~GHz, and investigate the effect of passive reflectors for improving coverage. The experiments are performed using Tensorcom single chip TC60G-USB3-EVB and TC60G70100UP picocell platforms in different indoor and outdoor environments, both supporting beamforming based on IEEE~802.11ad specifications. Our results show that the passive metallic reflectors may signifciantly improve the mmWave signal coverage in regions where the line-of-sight (LOS) connectivity between the transmitter and the receiver is limited.

Communication at mmWave bands carries critical importance for 5G wireless networks. In this paper, we study the characterization of mmWave air-to-ground (AG) channels for unmanned aerial vehicle (UAV) communications. In particular, we use ray tracing simulations using Remcom Wireless InSite software to study the behavior of AG mmWave bands at two different frequencies: 28 GHz and 60 GHz. Received signal strength (RSS) and root mean square delay spread (RMS-DS) of multipath components (MPCs) are analyzed for different UAV heights considering four different environments: urban, suburban, rural, and over sea. It is observed that the RSS mostly follows the two ray propagation model along the UAV flight path for higher altitudes. This two ray propagation model is affected by the presence of high rise scatterers in urban scenario. Moreover, we present details of a universal serial radio peripheral (USRP) based channel sounder that can be used for AG channel measurements for mmWave (60 GHz) UAV communications.

We present a novel microwave imaging technique for sparse domain imaging applications. In the proposed method, inverse scattering algorithm modified gradient method (MGM) is combined with a fast iterative shrinkage-thresholding algorithm to improve the resolution and robustness of the MGM by enforcing the sparsity in the imaging domain. The numerical experiments show that the proposed method achieves higher resolution and robustness compared with that of classical MGM. For nonsparse domain reconstruction, the wavelet transformation is adopted to convert nonsparse spatial domain into a sparse wavelet coefficient domain. The feasibility of the proposed method in the wavelet domain is demonstrated through the numerical experiments.

Cooperative wireless communication has attracted intense interest as an alternative way to multiple-antenna systems to obtain spatial diversity. In this paper, we investigate the performance of a vehicle-to-vehicle cooperative scheme where another vehicle in the vicinity of the source vehicle acts as a relay. The underlying source-to-relay, relay-to-destination, and source-to-destination links are modeled as cascaded Nakagami-m fading which provides a realistic description of an intervehicular channel. Unlike the most studies on cooperative intervehicular communications in the literature which are based on analog relaying, we employ digital relaying approach and investigate the performance of the techniques developed for mitigating error propagation in decode and forward based wireless relay systems such as maximum likelihood, cooperative maximal ratio combining, link adaptive relaying, virtual noise based detection and soft information relaying. Simulation results show that detection schemes with these techniques outperform the noncooperative system that involves direct transmission between the source and destination terminals and overcome the diversity gain reduction due to error propagation.

In this paper, two different antenna selection models based on signal-to-noise ratio (SNR) have been proposed in order to reduce the end-to-end bit error rate (BER) of decode and forward (DF) relaying cooperative system where source and destination terminals contain single antenna while relay terminal has multiple antennas. Specifically, by using instantaneous and average SNR of source-to-destination, source-to-relay and relay-to-destination links, optimal decision rules are derived theoretically for antenna selection at the relay terminal. Later, BER expressions of considered system have been derived for two antenna selection models over Rayleigh fading channels. Theoretical and simulation results show the validity of proposed mathematical analysis and point out the confirmation of theoretical results.

Maximum likelihood (ML) detection, link adaptive relaying (LAR) and selection relaying (SR) are among the most popular techniques developed for mitigating error propagation in regenerative decode and forward based cooperative wireless networks. In this paper, three different transmission schemes referred to as hybrid LAR and ML (LAR-ML), hybrid SR and ML (SR-ML) and hybrid SR, LAR and ML (SR-LAR-ML) are introduced to combat the error propagation which are obtained by combining the classical ML, LAR and SR approaches. The performance of the proposed structures are determined by computer simulations and providing a general framework for average BER analysis in case of noncoherent binary frequency shift keying which does not require channel state information at either the users or the destination. It has been shown that all of the proposed techniques supply full diversity gain and prevent performance degradation due to error propagation.

This letter introduces a computationally efficient inversion algorithm based on the contrast source inversion method for two-layered media applications. The proposed algorithm employs Cauchy data to derive an integral representation of the electromagnetic field inside the homogeneous neighborhood of the target. This representation yields a Lippmann-Schwinger-type integral equation that does not involve the background Green's function. Therefore, it provides a significant improvement in computational efficiency. Numerical experiments are provided to demonstrate the performance of the method.

Link adaptive relaying (LAR) is one of the most popular techniques developed for mitigating error propagation in decode and forward (DF) based cooperative wireless networks which employs soft power scaling approaches at the relay nodes. On the other side, frequency shift keying (FSK) is a prominent technique for eliminating the need for channel estimation by training sequences which increases complexity of the system and causes reduction in the transmission rate in proportional to the number of users involved in the network. In this paper, performance of an LAR scheme with noncoherent binary FSK (BFSK) signaling is investigated by deriving exact closed form bit error rate expressions in Rayleigh fading channels.

The direct-conversion architecture used for Orthogonal Frequency Division Multiplexing (OFDM) systems suffers from intercarrier interference (ICI) between image subcarriers in each OFDM symbol due to I/Q imbalance between the inphase (I) and quadrature (Q) branches at the transmit and receive sides. One of the widely-used metrics to evaluate the performance degradation due to I/Q imbalance is the signal to interference plus noise ratio (SINR). The instantaneous subcarrier SINR can be represented as a ratio conditioned on a particular channel realization and the exact SINR is evaluated by averaging over the channel realizations. In the literature, it is common to approximate the SINR by taking the average of the numerator and denominator separately although the two are not independent. In this paper, we calculate the exact SINR under the assumption that each pair of interfering subcarriers experiences uncorrelated channel realizations. We show that the SINR grows as the logarithm of the input SNR when the receiver has I/Q imbalance. On the other hand, under transmit-only I/Q imbalance, there is an SINR ceiling for large input SNR. Therefore, transmitter side I/Q imbalance is more harmful, in terms of average SINR, than receiver-only I/Q imbalance. We also show that, the approximate SINR expression, commonly used in the literature, is not accurate for large input SNR values, except for the case of transmit-only I/Q imbalance.

In this paper, we start by investigating the impact of joint transmit-receive I/Q imbalance on the performance of direct-conversion beamforming OFDM transceivers. We derive a new analytical expression for the average subcarrier SINR of the I/Q imbalance-ignorant beamformer in terms of the I/Q imbalance level at both the transmit and receive sides, the size of the beamforming array, and the input SNR level. This expression motivates the need for I/Q imbalance compensation and provides valuable design insights when examining several special and limiting cases. Next, we derive the throughput-maximizing multiple beamforming transmit/receive coefficients under a general system model with an asymmetric frequency-dependent (FD) joint transmit-receive I/Q imbalance. In addition, we propose a low-complexity pilot-aided scheme for the estimation of the channel and I/Q imbalance parameters. Our simulation results demonstrate that the proposed generalized multiple beamforming scheme is highly effective in mitigating I/Q imbalance effects at practical complexity levels.

In this paper, we investigate the effects of asymmetric frequency-dependent joint transmit-receive I/Q imbalance on the performance of beamforming MIMO-OFDM systems. We derive the throughput-maximizing transmit/receive beamforming coefficients taking into account I/Q imbalance effects. In addition, we propose a low-complexity pilot-aided scheme for the estimation of the channel and I/Q imbalance parameters. Our simulation results demonstrate the effectiveness of the proposed generalized beamforming scheme in mitigating I/Q imbalance effects.

In this paper, we derive an analytical expression for the subcarrier average SINR of a beamforming OFDM system in the presence of joint transmit-receive I/Q imbalance. The derived expression quantifies the impact of the I/Q imbalance level at both the transmit and receive sides, the size of the beamforming array, and the input SNR level on performance. Several special and limiting cases are investigated providing new design insights.

Bi-directional relaying (BDR) in which two users wish to exchange independent information in presence of a relay is one of the fundamental wireless network coding applications that attracted intense interests recently. In this paper, maximum likelihood (ML), cooperative maximal ratio combining (CMRC) and soft information relaying (SIR) schemes proposed to combat error propagation in wireless relay systems are applied to the BDR scenario with demodulate-and-forward protocol, which decreases system complexity and cost by removing the decoding process at the relay terminal. Simulation results for Rayleigh fading channels show that detection schemes using ML and CMRC techniques outperform the noncooperative system that involves direct transmissions between user terminals and overcome the diversity gain reduction due to error propagation for different levels of channel state information (CSI). In case of SIR based communication scenario, the diversity gain is contingent on the availability of a coefficient depending on instantaneous CSI.

Abstract The research challenges to enhance the throughput of communication networks revealed the concept of network coding which is based on the idea of coding at packet level. The bi‐directional relay channel in which two user terminals exchange independent information with the help of a relay terminal is among the prominent applications of network coding in wireless cooperative communications. In this paper, maximum likelihood (ML) performance analysis of digital relaying based bi‐directional communication is presented. The three stage communication scenario is considered where the first and second stages are allotted to the transmissions of the users and after demodulation the relay broadcasts the network encoded packet obtained by a bit‐wise XOR operation to the users in the third stage. The average bit error rate of this scheme with ML detection is derived for Rayleigh fading channels under noncoherent BFSK and coherent BPSK signaling. Simulation results are also presented to validate the theoretical analysis. Analytical and simulation results show that digital relaying based three stage bi‐directional communication scheme with ML detection not only outperforms the noncooperative system that involves direct transmissions between user terminals but also prevents the diversity level reduction due to error propagation. Copyright © 2010 John Wiley & Sons, Ltd.

Super-orthogonal space–time trellis (SOSTT) codes provide a significant coding gain with respect to the conventional space–time trellis (STT) codes without increasing the decoding complexity at the receiver. Transmit antenna selection (TAS) is an important technique to solve the implementation complexity problems of multiple-antenna systems that arise from employing a separate RF chain for each antenna. This study treats a scheme combining SOSTT coding with TAS in order to exploit performance improvements provided by SOSTT codes while realising the promises made by the TAS technique. In the proposed scheme, transmit antennas that maximise the signal-to-noise ratio at the receiver are chosen and activated out of all available transmit antennas for transmission of the baseline SOSTT code, whereas all other transmit antennas are silent. The error performance of the proposed structure is investigated by deriving moment generating function (MGF)-based upper bound expressions on the pairwise error probability in quasi-static flat Rayleigh fading channels for both perfect and imperfect antenna subset selection. The performance analysis demonstrates that the proposed scheme provides full diversity order as if all transmit antennas were used when antennas are perfectly selected. Moreover, it is shown that this structure provides better error performance almost at the same decoding complexity compared to the previous STT coding structures with TAS in the literature.

A reciprocity gap linear sampling method (RG-LSM) coupled with an analytic continuation method is proposed to localize and retrieve the shape of objects buried under a rough surface from multistatic data at a fixed frequency. The obtained procedure makes feasible the application of the RG-LSM algorithm to imaging experiments where the data are collected in the upper domain. It does not require the computation of the Green's function of the background layered medium and also does not require any a priori knowledge on the number or the physical properties of the buried scatterers. The efficiency and robustness of the method are validated through various numerical experiments for single and multiconnected objects.

In recent years, digital beamforming has evolved into an excellent technology to improve wireless communications over fading channels. Especially in slow fading environments with a sufficient number of users in the system, opportunistic beamforming through multiuser diversity [1] has offered some advantages over true beamforming methods that rely on full channel feedback and/or robust channel estimation methods. Opportunistic beamforming achieves good throughput with only signal-to-noise ratio (SNR) feedback from the users. The quality of the SNR feedback such as the degree of SNR quantization is essential for opportunistic beamforming because the base station selects the best receiving user based on the SNR measurements sent by the users. In this paper, we develop an optimum SNR quantization method performed by the users and analyze its impact on the system throughput. While keeping the fairness among the users, we show that the opportunistic beamforming gain can still be realized with the help of the proposed quantization method. Theoretical analysis and computer simulation results show the feasibility and effectiveness of the method which provides insights for engineers to implement opportunistic beamforming in practice.

In recent years, diversity techniques have evolved into highly attractive technology for wireless communications in different forms. For instance, the channel fluctuations of the users in a network are exploited as multiuser diversity by scheduling the user with the best signal-to-noise ratio (SNR). When fading is slow, beamforming at a multiple antenna transmitter is used to induce artificial channel fluctuations to ensure multiuser diversity in the network. Such a beamforming scheme is called opportunistic beamforming since the transmitter uses random beamforming to artificially induce opportunism in the network [1]. Opportunism requires a large number of users in the system in order to reach the performance of the true beamforming that uses perfect channel state information (CSI). In this paper we investigate the benefit of having partial CSI at an opportunistic transmitter. In the investigation, we focus on the maximum normalized SNR scheduling where user's feedback consists of SNR relative to its channel gain. We show that opportunism can be beneficially used to increase the average throughput of the system. Simulations support the analytical average throughput results obtained as the amount of CSI and the number of users vary.

A new, simple, and fast method for the solution of electromagnetic scattering problems for perfectly conducting objects of arbitrary shape is presented. The method is based on an equivalent representation of the conducting object in terms of a circular one having a higher order impedance boundary condition on its surface. As a first result, a new universal relation between the higher order surface impedances and the shape of the object is obtained. Then, by taking advantage of this relationship, the scattering problem related to a conducting object is recast as the solution of a matrix equation whose coefficients are determined from the higher order impedances. Numerical simulations show that the method yields to accurate results, and that, it is computationally effective

Opportunistic beamforming has been shown to achieve true beamforming gains with unquantized signal-to-interference ratio (SNR) feedback when there are sufficient users in the system [1], [2]. In this paper we investigate the performance of opportunistic beamforming with an SNR quantization scheme that maximizes the expected system throughput. To show that the opportunistic beamforming can still be beneficially employed with quantized SNR feedback, we derive the SNR statistics and the system throughput to optimize the SNR quantization with respect to thresholds separating quantization levels. Numerical results are used to illustrate the impact of the optimum threshold levels and the number of thresholds.

In wireless networks, average system through-put can be improved by scheduling transmissions according to instantaneous signal-to-noise ratio (SNR) values of the users assuming that channel fading is fast enough to maintain multiuser diversity. If the fading is slow, opportunistic multiple antenna approaches can introduce artificial fading in the system. These schemes require significant amount of SNR feedback. A novel channel estimation method for opportunistic beamforming is proposed based only on SNR feedback. More importantly, the effectiveness of the proposed channel estimation algorithm is verified using our multiple antenna testbed. The experimental results show that the channel estimation based beamforming can attain true beamforming gains.

In a wireless network the channel fluctuations of the users can be exploited by means of multiuser diversity where the user transmissions are scheduled when they experience a high instantaneous SNR. When fading is slow, beamforming at a multiple antenna transmitter can be used to induce artificial temporal fading to ensure multiuser diversity in the network. Such a beamforming scheme is called opportunistic beamforming [1] since the transmitter sends random beamforming vectors to artificially induce opportunism in the network. Opportunistic beamforming requires a large number of users in the system in order to achieve the performance of the true beamforming that uses perfect channel state information (CSI). In this paper we investigate the benefit of having partial CSI at the transmitter. We show that opportunism is still exploited to increase the average throughput of the system. Numerical results show that with partial CSI at the transmitter performance close to that of true beamforming can be obtained with even fewer number of users in the system.

The analytical performance of the blind estimation of finite-impulse response (FIR) channels without eigendecomposition in CDMA systems is examined. The channel problem arises when CDMA signals are subject to frequency selective fading. Blind channel estimation is desired when training data is unavailable. Blind channel estimation techniques in the literature often rely on subspace decomposition of received signals. Blind channel estimation can also be coupled with a multiuser receiver design in the context of a minimum output energy (MOE) criterion. While subspace decomposition is avoided, the inverse of the data covariance matrix of the received signals is needed (Xu, Z. et al., Proc. IEEE Asilomar Conf. Signals, Syst. Comput., p.689-93, 2002). Previously (Ozdemir, O. and Torlak, M., Proc. IEEE Int. Conf. on Commun., vol.5, p.2621-5, 2004), we proposed a blind channel estimation method using simple covariance matrix transformations. We now use analytical and simulation results to show that the channel estimates converge to the eigendecomposition based channel estimates at medium to high signal-to-noise ratio (SNR).

We address the problem of blind estimation of finite-impulse response (FIR) channels without eigendecomposition in CDMA systems. The blind channel estimation problem arises in the presence of frequency selective fading, when the training data is unavailable. The blind channel estimation techniques in the literature often rely on the eigendecomposition of the received signals. The blind channel estimation can also be coupled with the multiuser receiver design in the context of minimum output energy (MOE) criterion. While MOE receiver avoids eigendecomposition, the inverse of data covariance matrix of received signals is needed [Z. Xu et al., Nov. 2002]. In this paper we propose a blind channel estimation method that avoids eigendecomposition. At the same time, the proposed method directly uses the data covariance matrix without requiring its inversion. Analytical and simulation results are provided to show that the channel estimates converge to the eigendecomposition based channel estimates at the medium to high signal-to-noise ratio (SNR).

CDMA systems need simultaneous multiple access interference suppression and adaptive interference suppression filters that may span three symbols. Thus, a large number of filter coefficients need to be estimated. By the use of reduced rank filtering, it is possible to lower the number of required filter coefficients with a small decrease in performance. M. Honig (see Proc. IEEE Asilomar Conf. Signals, Syst. Comput., p.1106-10, 1998) made a successful attempt to develop a reduced rank algorithm for non-dispersive CDMA signals based on the multistage Wiener (MSW) filter of J. Goldstein et al. (see IEEE Trans. on Information Theory, vol.44, no.7, p.2943-59, 1998). Motivated by MSW, we propose reduced rank advanced RAKE receivers for dispersive CDMA signals. The proposed receivers are blindly implemented in a lower dimensional space, relative to the full-rank receivers, without the aid of training sequences and channel information. By exploiting the structure of the user signature waveform, the proposed receivers exhibit performance close to that of the reduced rank minimum mean square error (MMSE) receiver implemented with the desired user's known channel information.