In this paper, we derive the data-aided error vector magnitude (EVM) in an interference limited system when both the desired channel and interferers experience independent and nonidentically distributed κ-μ shadowed fading. Then, it is analytically shown that the EVM is equal to the square root of number of interferers when the desired channel and interferers do not experience fading. Furthermore, the EVM is derived in the presence of interference and noise, when the desired channel experiences κ-μ shadowed fading and the interferers experience independent and identical Nakagami fading. Moreover, using the properties of the special functions, the derived EVM expressions are also simplified for various special cases.

Device-to-device (D2D) communication underlying cellular networks, allows direct transmission between two devices in each other's proximity that reuse the cellular resource blocks in an effort to increase the network capacity and spectrum efficiency. However, this imposes severe interference that degrades the system's performance. This problem may be circumvented by incorporating fractional frequency reuse (FFR) or soft frequency reuse (SFR) in OFDMA cellular networks. By carefully considering the downlink resource reuse of the D2D links, we propose beneficial frequency allocation schemes, when the macrocell has employed FFR or SFR as its frequency reuse technique. The performance of these schemes is quantified using both the analytical and simulation results for characterizing both the coverage probability and the capacity of D2D links under the proposed schemes that are benchmarked against the radical unity frequency reuse scheme. The impact of the D2D links on the coverage probability of macrocellular users (CUs) is also quantified, revealing that the CUs performance is only modestly affected under the proposed frequency allocation schemes. Finally, we provide insights concerning the power control design in order to strike a beneficial tradeoff between the energy consumption and the performance of D2D links.

We analytically characterize the data-aided error vector magnitude (EVM) performance of a single-input multiple-output (SIMO) communication system relying on maximal ratio combining (MRC) having either independent or correlated branches that are nonidentically distributed. In particular, exact closed form expressions are derived for the EVM in$\eta\text{-}\mu$fading and$\kappa W\mu$shadowed fading channels and these expressions arevalidatedby simulations. The derived expressions are expressed in terms of Lauricella’s function of the fourth kind$F_D^{(N)}(.)$, which can be easily computed. Furthermore, we have simplified the derived expressions for various special cases such as independent and identically distributed branches, Rayleigh fading, Nakagami-mfading, and$\kappa\text{-}\mu$fading. Additionally, a parametric study of the EVM performance of the wireless system is presented.

We study Compound TCP (C-TCP), the default TCP in the Windows operating system, with Random Exponential Marking (REM) and the widely used Drop-Tail queue policy. The performance metrics we consider are stability of the queue size, queuing delay, link utilization, and packet loss. We analyze the following models: 1) a nonlinear model for C-TCP with Drop-Tail and small buffers; 2) a stochastic variant of REM along with C-TCP; and 3) the original REM proposal as a continuous-time nonlinear model with delayed feedback. We derive conditions to ensure local stability and show that variations in system parameters can induce a Hopf bifurcation, which would lead to the emergence of limit cycles. With Drop-Tail and small buffers, the Compound parameters and the buffer size both play a key role in ensuring stability. In the stochastic variant of REM, larger thresholds for marking/dropping packets can destabilize the system. With the original REM proposal, using Poincaré normal forms and the center manifold analysis, we also characterize the type of the Hopf bifurcation. This enables us to analytically verify the stability of the bifurcating limit cycles. Packet-level simulations corroborate some of the analysis. Some design guidelines to ensure stability and low latency are outlined.

In this work, the authors derive the optimal signal‐to‐interference‐ratio (SIR) thresholds S t which maximise coverage probability for both fractional frequency reuse (FFR) and soft frequency reuse (SFR) networks with base station locations modelled using Poisson point process. It is analytically shown that for both FFR and SFR, the optimal SIR threshold is equal to the target SIR T , i.e, S t = T . The authors also show that at the optimal SIR threshold, FFR achieves a higher coverage than frequency reuse (1/Δ). Furthermore, for the cases when S t > T and S t < T , FFR achieves a higher coverage than reuse (1/Δ) and reuse 1, respectively. On the other hand, SFR coverage can be higher or lower than reuse (1/Δ) coverage, even when S t = T . However, when S t > T , SFR achieves a higher coverage than reuse 1, and when S t < T , the SFR coverage can be lower than reuse 1 coverage. The FFR and SFR coverages are also compared for a given Δ, and it is shown that FFR achieves a higher coverage than SFR at the optimal value of S t .

Expressions are derived for the coverage probability and average rate of both multi-user multiple input multiple output (MU-MIMO) and single input multiple output (SIMO) systems in the context of a fractional frequency reuse (FFR) scheme. In particular, given a reuse region of 1/3 (FR3) and a reuse region of 1 (FR1) as well as a signal-to-interference-plus-noise-ratio (SINR) threshold Sth, which decides the user assignment to either the FR1 or FR3 regions, we theoretically show that: 1) the optimal choice of Sthwhich maximizes the coverage probability is Sth= T, where T is the target SINR required for ensuring adequate coverage, and 2) the optimal choice of Sthwhich maximizes the average rate is given by Sth= T', where T' is a function of the path loss exponent, the number of antennas and of the fading parameters. The impact of frequency domain correlation amongst the OFDM sub-bands allocated to the FR1 and FR3 cell-regions is analysed and it is shown that the presence of correlation reduces both the coverage probability and the average throughput of the FFR network. Furthermore, the performance of our FFR-aided MU-MIMO and SIMO systems is compared. Our analysis shows that the (2 × 2) MU-MIMO system achieves 22.5% higher rate than the (1 × 3) SIMO system and for lower target SINRs, the coverage probability of a (2 × 2) MU-MIMO system is comparable to a (1 × 3) SIMO system. Hence the former one may be preferred over the latter. Our simulation results closely match the analytical results.

In cellular networks, all base stations (BSs) do not continuously transmit i.e., the BSs transmit only when their queues are non-empty. This implies that the system resources are only partially loaded, and the dynamics of such a network differs significantly from that of a fully-loaded system. The coverage probability in a fully- and partially-loaded cellular network is analysed. We consider a regular spatial arrangement of base stations, and obtain the coverage probability in the presence of interference. More specifically, expressions for coverage probability are obtained for square and hexagonal lattices with full and partial loading. The coverage probability is obtained using properties of lattice sums which were first used in physics to analyse potentials in crystal structures.

In orthogonal frequency division multiple access‐based systems where channel frequency response (CFR) estimation has to be carried out using only the user‐specific (localised) pilots within a small time frequency block, the accuracy of the estimates suffer because of the limited number of pilots and imperfect knowledge of the channel statistics. A biased estimator is proposed for the estimation of CFR over the time frequency block. Hypothesis tests are designed to ascertain the time and frequency selectivity of the CFR within the region of interest, and the outcome of these tests are used to determine a vector shrinkage target for the biased estimator. Simulation results indicate that the performance of the proposed estimator is comparable to that of the optimal minimum mean square error estimator, even though it does not have any knowledge of the channel statistics.

Different-complexity Multi-Cell Processing (MCP) schemes employing Distributed Signal-to-Interference-Leakage-plus-Noise-Ratio (SILNR) precoding techniques are proposed, which require reduced back-haul data exchange in comparison to the conventional MCP structure. Our results demonstrate that the proposed structures are capable of increasing the achievable cell-edge throughput and offering different geographic rate profile distributions as well as meeting different delay requirements.

Pilot assisted channel tracking (PACT) has been very popular for channel estimation in OFDM systems. However, as the mobility in the system increases and one has to maintain a high accuracy in channel estimation, the pilot overhead typically has to be increased. Emerging cellular OFDM standards are expected to use about 6 - 12% pilot overhead per stream, and any possible reduction in pilot overhead would be useful. Decision directed channel tracking (DDCT) can help reduce pilot overhead, but is known to suffer from error propagation at high fade rates. In emerging broadband wireless systems promising peak bit rates of 50 Mbps or more, saving on pilot overhead by using DDCT schemes would be highly attractive provided: (a) Such a DDCT approach does not suffer from error propagation and has an error rate performance comparable to (or better than) PACT schemes even at high fade rates; (b) The computational complexity of such a DDCT approach is not significantly more than that of the MMSE based PACT scheme. In this work, we propose a low complexity DDCT method which exploits the structure of the regression matrix in conjunction with robust statistics to mitigate the effect of error propagation. It has a much lower computational complexity and a better error rate performance than the decision directed EM-Kalman and other existing robust statistics based DDCT schemes. The proposed method also outperforms a 12.5% pilot overhead based PACT scheme with only a modest increase in computational complexity.

In the emerging broadband wireless networks such as IEEE 802.16m and LTE-A networks which employ universal frequency reuse-1, the cell coverage is predominantly limited by the co-channel interference. Bit level data repetition, and conventional multi-antenna maximal-ratio-combining (MRC) techniques are typically used to improve the signal-to-interference-plus- noise ratio (SINR) at the receiver. Simple data repetition does not guarantee efficient interference suppression and it reduces spectrum efficiency. In this paper, we propose a symbol level data repetition technique called conjugate data repetition (CDR), which transmits the modulation alphabet of the desired signal and its complex-conjugate in distinct sub carriers. The CDR operation is performed across all base stations in a synchronous manner. We show that minimum mean-square error (MMSE) filtering of the complex-valued signal and its conjugated copy, provides a high interference cancellation (IC) gain. For repetition factor greater than 2, we propose a combination of conjugate repetition and random phase rotation of the repeated symbols. Simulation results show that CDR with a repetition factor 2 or 3 can provide a significant advantage in coverage/reliability for cell edge users.

We propose a novel subspace-based 2-D damped harmonic retrieval algorithm that uses a single snapshot of data. The data is packed into a measurement tensor and spatial smoothing is applied to it to get a spatially smoothed tensor. We observe a structure inherent in the spatially smoothed tensor. This structure can be fully exploited by constructing multiple higher-order tensors from the spatially smoothed tensor and by running parameter estimation algorithm multiple times, one for each dimension. In this paper we propose to construct a single higher-order tensor and perform a single higher-order singular value decomposition (HOSVD) for estimating the normalized frequencies along the two dimensions. The proposed algorithm performs significantly better than Tensor-ESPRIT applied to the spatially smoothed tensor, and matrix-based approaches. Moreover, it is insensitive to changes in the number of samples per subarray. Our work can be extended to R-D damped harmonic retrieval problems.

Spatial smoothing is a widely used preprocessing scheme for direction-of-arrival (DOA) estimation of more than one source from a single snapshot, although the effective array aperture gets reduced by this process. In this paper we propose a preprocessing scheme applicable for DOA estimation algorithms that exploit the shift invariance property of the array steering matrix and call it spatial smoothing with improved aperture (SSIA). SSIA, when applied to a noise corrupted data vector, improves the effective array aperture significantly as opposed to conventional spatial smoothing. Simulations confirm the significant performance gain provided by SSIA in conjunction with Unitary ESPRIT.

Performance of spatial multiplexing multiple-input multiple-output (MIMO) wireless systems can be improved with channel state information (CSI) at both ends of the link. This paper proposes a new linear diagonal MIMO transceiver, referred to as co-ordinate interleaved spatial multiplexing (CISM). With CSI at transmitter and receiver, CISM diagonalizes the MIMO channel and interleaves the co-ordinates of the input symbols (from rotated QAM constellations) transmitted over different eigenmodes. The analytical and simulation results show that with co-ordinate interleaving across two eigenmodes, the diversity gain of the data stream transmitted over the weaker eigenmode becomes equal to that of the data transmitted on the stronger eigenmode, resulting in a significant improvement in the overall diversity. The diversity-multiplexing tradeoff (DMT) is analyzed for CISM and is shown that it achieves higher diversity gain at all positive multiplexing gains compared to existing diagonal transceivers. Over rank n MIMO channels, with input symbols from rotated n-dimensional constellations, the DMT of CISM is a straight line connecting the endpoints (0,NtNr) and (min{Nt,Nr}, 0), where Nt, and Nrare the number of transmit and receive antennas, respectively.

Channel estimation for Alamouti space frequency coded (ASFC) 2 times 2 and 2 times 1 MIMO OFDM systems, employing decision directed channel tracking (DDCT) for high fade rates and long frame durations is studied here. Errors in the regression matrix (i.e. equalisation errors) have a Gaussian distribution, but due to error propagation problem of DDCT at high fade rates and long symbol durations, large deviations from the Gaussian model is observed. Hence the problem of channel estimation can be formulated as an outlier contaminated Gaussian linear regression problem. Most of the classical estimators like Least squares (LS) and Expectation Maximisation (EM) algorithm perform poorly in presence of outliers. Moreover, for a MIMO system the source of outliers are the erroneous decisions of any of the multiple input channels. Here, we propose to use the EM algorithm to partition multiple input channel into independent estimations for each transmit-receive antenna pair and provide an iterative framework for solving the multiple regression problem. EM algorithm is made robust using the Huber's M principle (for the E and the M steps) and it is shown analytically that mean square error (MSE) performance improves as compared to existing schemes which assume Gaussian noise. The simulated symbol error rate (SER) and MSE performances demonstrate the significant gains of the proposed robust EM algorithm over existing DDCT techniques at high normalised fade rates for the given system.

Vertical layering with successive interference cancellation (SIC) at the receiver (e.g. V-BLAST) is a popular spatial multiplexing scheme that achieves high data rates over multi-antenna wireless channels. However, SIC suffers from low diversity gains and recently, with limited feedback, a diversity optimal SIC receiver has been proposed based on greedy QR decomposition (GQR-SIC). But the low diversity gain of the first decoded layer degrades the overall diversity gain. In this paper, we present a new diagonally layered spatial multiplexing scheme that employs GQR-SIC receiver but achieves significantly higher diversity gains. In the proposed scheme, the diversity gain of a weak layer is improved through interleaving the co-ordinates of the symbols transmitted over the weak layer and a strong layer. In this work, we focus on spatial multiplexing with only two layers and analyze the diversity multiplexing tradeoff to show that the proposed scheme achieves maximum diversity gain. When compared with other diagonally layered schemes, the proposed scheme has low decoding complexity.

We look at the performance of turbo coded OFDM systems in the presence of narrowband interference (NBI) and co-channel interference (CCI). In systems employing standards such as the IEEE 802.16d/e, CCI behaves like NBI with the number of affected subcarriers ranging from 10% to 30%. Hence we treat symbol detection in such systems as detection in contaminated Gaussian (CG) noise and propose a robust log- likelihood ratio (LLR) computation for it. The proposed LLR computation method exploits the fact that NBI/CCI has a CG probability density function (pdf) but does not assume knowledge of the NBI power, NBI pdf and the fraction of subcarriers affected by NBI. Simulation results indicate that the proposed method performs very close to the optimal method which would have complete knowledge of the CG pdf parameters.

A robust cost function for log likelihood ratio (LLR) computation is proposed for turbo coded OFDM systems in the presence of narrowband interference (NBI) and co-channel interference (CCI). In systems employing standards such as the IEEE 802.16d/e, CCI behaves like NBI with the number of affected subcarriers ranging from 10% to 30%. The combined effect of NBI and thermal Gaussian noise leads to a contaminated Gaussian (CG) noise probability density function (pdf). Simulation results indicate that the proposed method performs very close to the optimal method where the optimal method computes the LLR using the CG pdf. While the optimal method requires knowledge of the NBI power, the fraction of subcarriers contaminated by NBI and the NBI pdf, the proposed method does not require knowledge of these parameters.

Spatial multiplexing over multiple-input multiple-output (MIMO) channels significantly improves the data rates over wireless channels. With channel knowledge at both ends of the link, many spatial multiplexing schemes have been proposed in literature, showing improved performance with respect to some performance measure. Co-ordinate interleaved spatial multiplexing (CISM) (Srinivas et al., 2006) is one such scheme that has been shown to achieve improved error rate performance. In this paper, we analyze CISM from diversity-multiplexing gain tradeoff (DMT) perspective. We focus on CISM over MIMO channels having only two degrees of freedom and show that the DMT of CISM is a straight line connecting the two extreme points (0, 2 m) and (2, 0) where m = max{Nt, Nr}. This result shows that CISM outperforms many other schemes that require same amount of feedback.

M estimators have been widely used for parameter estimation in the presence of outliers or impulsive noise. A number of papers use the iteratively reweighted least squares (IRLS) algorithm for M estimation. The IRLS method tries to iteratively converge to the non-linear M estimate using a weighted least squares algorithm. While the performance of the IRLS algorithm has been demonstrated through simulation, to our knowledge, the MSE of the IRLS based M estimation approach has not been theoretically derived in signal processing literature. In this paper, we derive the theoretical MSE of three M estimators, namely, the Huber's M (HM) estimator, the extreme value theory (EVT) based estimator and the Hampel's 3-part (HP) estimator when they are implemented using the IRLS algorithm. This theoretical MSE is a function of the M estimator cost function, the noise distribution, and the iteration number of the IRLS algorithm. Based on the theoretical analysis in this paper, we show that for both Cauchy and Gaussian impulsive noise, the MSE of the IRLS based M estimator converges to the MSE of the desired M estimator within 3 to 5 iterations.

Decision directed channel tracking (DDCT) at high fade rates in OFDM based systems is addressed in this paper. Existing DDCT algorithms like the expectation-maximization (EM) algorithm (Al-Naffouri et al., 2002) suffer from error propagation and exhibit poor performance when applied to large frames at high fade rates. We propose a robust EM algorithm which mitigates the effect of error propagation and is able to track the channel in the decision directed mode even over frame durations experiencing 2-3 fade cycles. This EM algorithm uses the Huber's cost function in the maximization step instead of the non-robust least squares or Kalman cost function. Further, the noise variance is estimated using the robust median absolute deviation estimator instead of the standard maximum likelihood estimator. The proposed robust EM based DDCT scheme has a better error rate and MSE performance when compared to Kalman filter based pilot assisted channel tracking scheme with a 6.25% pilot overhead, even at a normalized Doppler of 0.04.

A method for the mitigation of the effect of narrowband interference (NBI) on the turbo decoder in OFDM systems is proposed. The presence of NBI leads to a contaminated Gaussian (CG) noise probability density function (pdf) which induces an outlier effect in the data detection problem. The outlier effect leads to significant degradation in the performance of turbo coded OFDM systems which use Gaussian noise pdf based log likelihood ratios (LLRs), with the degradation increasing as a function of the power of NBI and the number of subcarriers affected by NBI. We propose to use outlier detection theory to detect subcarriers affected by NBI, and then downweigh the corresponding LLRs before passing them to the turbo decoder. Extreme value theory (EVT) is used to define the weight function in this weighted-LLR (W-LLR) method. The method is easy to implement, is of modest computational complexity, and shows a significant improvement in the simulated error rate performance when compared with the simple unweighted turbo decoder in the presence of NBI. Furthermore, frequency selectivity and diversity mapping in OFDM systems such as IEEE 802.16 d/e WMAN standard causes the co-channel interference (CCI) to look like NBI within the FEC block. Therefore, the W-LLR method can also be applied for CCI mitigation in these systems. Since reuse-one cellular systems have a CCI limited performance, the proposed method provides a significant improvement over the normal turbo decoder.

We propose an improved channel estimator for reuse-1 orthogonal frequency division multiplexing (OFDM) cellular systems. The proposed channel estimation technique exploits delay subspace structure in reducing the interference on channel estimation. The proposed pilot-based channel estimation technique initially estimates the multipath delay locations of both the desired and interference channels. In estimating multipath delays, we assume that the time-of-flight difference between the desired and interfering signals ensures that the multipath delay locations of the corresponding channels are distinct. This information is used to suppress interference in the multipath-delay domain, and define a channel interpolator with a lower normalized mean squared error (NMSE) when compared to the conventional modified least-squares technique (mLS). We also derive the analytical expression for the bit-error-rate of a zero- forcing (ZF) receiver based on the proposed channel estimator. In particular, we show that for uncoded OFDM, the match between the estimated BER and analytical BER is very good and the proposed estimator can outperform mLS by more than a order of magnitude in BER if the interference on the data subcarriers is significantly lower than the interference seen on the pilot subcarriers. Simulation results are also presented with turbo-coded OFDM which further demonstrates the efficacy of the proposed algorithm.

Orthogonal frequency division multiplexing (OFDM) systems are highly sensitive to frequency synchronization errors which cause inter-carrier interference, leading to degradation in the system performance. In this paper, a pragmatic timing and frequency synchronization scheme for reuse-1 OFDMA systems that is compatible with IEEE 802.16d/e wireless MAN standard is proposed. The algorithm uses cyclic prefix correlation technique to both estimate and track OFDMA frame boundary and fractional frequency offset. Once the preamble is captured, the integral part of the frequency offset and cell-specific preamble code can be estimated. This novel scheme is computationally efficient and robust to co-channel interference and multipath fading. Simulation results show that the proposed algorithm gives excellent performance even at very low signal to interference noise ratios.

Decision feedback equalizers (DFEs) are designed to deal with AWGN noise, and hence, generally perform very poorly in the presence of impulsive noise. Extreme value theory (EVT) is used to modify the DFE structure to handle impulsive noise. The received measurements are modified using EVT based weights before passing it to the equalizer. A modified maximal ratio combining (MRC) scheme which also uses EVT is developed to further improve the error-rate performance in the presence of impulsive interference. The proposed method performs much better than the conventional DFE-MRC technique which uses the simple MRC in conjunction with the DFE at low signal-to-interference (SIR) ratios.

Co-channel interference (CCI) on pilot subcarriers can severely degrade the channel estimation accuracy in reuse-1 cellular OFDM systems. Currently most OFDM channel estimation schemes use a Kalman filter, which implicitly assumes that the CCI is Gaussian. However, when only one or two strong CCI signals are present, the Gaussianity assumption of the disturbance sequence is usually not valid. We propose Hinfinbased channel estimation for such CCI limited OFDM systems. Simulated performance results of normalized mean squared error as well as singular value plots indicate that the Hinfinbased algorithm yields a significantly superior performance when compared to the Kalman filter.

Channel estimation in the presence of multitone narrowband interference (MNBI) in OFDM systems is addressed in this paper. While pilot based OFDM channel estimation in the presence of only thermal noise at the receiver is a Gaussian regression problem, the presence of MNBI leads to an outlier contaminated Gaussian regression problem. Since Gaussian probability density function (pdf) based maximum likelihood (ML) estimators are highly sensitive to outliers, we define a M estimator based on the theory of robust regression for channel estimation in the presence of MNBI. The proposed iterative M estimator minimizes the Huber's cost function for p iterations and then minimizes a cost function defined by a redescending M estimator based on extreme value theory in the last few iterations. Simulation results indicate that the proposed estimator outperforms both the Gaussian pdf based ML estimator and a M estimator based only on Huber's cost function.

Spatial multiplexing (SM) over multiple-input multiple-output wireless channels provides significant capacity gains. In a SM scheme, the eigenmode having the least signal-to-noise ratio (SNR), degrades the overall error rate performance. In this paper, we propose co-ordinate interleaved spatial multiplexing that maximizes the minimum SNR over all eigenmodes. This linearly decodable SM scheme needs the knowledge of the right singular vectors of the channel at the transmitter, and the singular values and left singular vectors at the receiver. We derive the SNR expressions for the proposed scheme and compare its performance with other closed-loop schemes using computer simulations

Decision directed channel tracking (DDCT) at high fade rates in OFDM based systems is addressed in this paper. Channel estimation in DDCT can be formulated as a linear errors-in-variables regression problem. While most of the errors in the regression matrix (equalization errors) are Gaussian in nature, few of the detected symbols can have high error due to the frequency and time selective fading. These poor symbol decisions behave like outliers in the regression matrix and give rise to contaminated Gaussian noise distributions. Classical estimators like total least squares (TLS) and the expectation-maximization (EM) based estimators exhibit poor performance in the presence of such outliers. We propose the Huber's M (HM) estimator and an extreme value theory (EVT) based M estimator for the DDCT problem. The proposed HM and EVT-HM estimators are robust to outliers and have an efficiency greater than 95% in purely Gaussian noise. The error rate performance of the proposed HM and EVT-HM estimators are compared with that of the TLS estimator, and the EM based estimator proposed in [4].

Decision directed channel tracking (DDCT) in OFDM systems can suffer from error propagation at high fade rates, due to the combined effect of rapid variation of the channel, long frame length and frequency selectivity of the channel. Conventional estimators like the 2D-minimum mean square error (MMSE) channel estimator and the expectation maximization (EM) based Kalman channel estimator [3] show poor performance when they are applied to DDCT over large frame lengths, due to the error propagation induced by wrong symbol decisions. The poor symbols decisions usually act like leverage points in the regression matrix, and can be identified using the hat matrix as a leverage diagnostic. We use extreme value theory (EVT) on the hat matrix to define a channel estimator, which, in addition to exploiting time and frequency correlation of the channel, downweighs leverage points before utilizing them in the estimator structure. The proposed EVT-leverage weighted (LW) estimator reduces error propagation in the frame since it downweighs possible wrong decisions before using them in the channel estimator structure. The proposed EVT-LW estimator has a significantly better error rate performance when compared to both the 2D-MMSE estimator [2] and the EM based Kalman estimator [3].

In this work, we present an algorithm for parametric estimation of a wireless channel for OFDMA transmission, tailored to the pseudo-random "tile" allocation pattern prevalent in multi-user allocation schemes1. Such tile allocations are usually common in the uplink where a tile is usually a small number of adjacent data subcarriers with a few pilot subcarriers. The algorithm estimates the delay subspace of the parametric channel description, and shows robustness for high RMS delay-spread channels. The estimator error convergence performance improves with increase in the channel Doppler frequency. Although the proposed algorithm requires more intensive computation than straight-forward intra-tile linear interpolation, it offers a greatly enhanced Bit-Error-Rate (BER) performance. In mobile channel nel environments, the need for numerous re-transmissions is therefore decreased, making this algorithm suitable for low BER applications such as video and data.

Orthogonal space-time block codes (OSTBCs) yield full diversity gain even while requiring only a linear receiver. Such full-rate (rate-one) orthogonal designs are available for complex symbol constellations only for N=2 transmit antennas. In this paper, we propose a new family of full-rate space-time block codes (STBCs) using a single parameter feedback for communication over Rayleigh fading channels for N=3,4 transmit antennas and M receive antennas. The proposed rate-one codes achieve full diversity, and the performance is similar to maximum receiver ratio combining. The decoding complexity of these codes are only linear even while performing maximum-likelihood decoding. The partial channel information is a real phase parameter that is a function of all the channel gains, and has a simple closed-form expression for N=3,4. This feedback information enables us to derive (channel) orthogonal designs starting from quasi-orthogonal STBCs. The feedback complexity is significantly lower than conventional closed-loop transmit beamforming. We compare the proposed codes with the open-loop OSTBCs and also with the closed-loop equal gain transmission (EGT) scheme which uses equal power loading on all antennas. Simulated error-rate performances indicate that the proposed channel orthogonalized STBCs significantly outperform the open-loop orthogonal designs, for the same spectral efficiency. Moreover, even with significantly lower feedback and computational complexity, the proposed scheme outperforms the EGT technique for M>N

Linear dispersion codes (LDC) designed for multiple input multiple output (MIMO) wireless systems are examples of space-time codes which try to maximize the mutual information between the transmitter and receiver. However, such codes are typically designed for flat fading channels. It is possible to extend LDC designs for frequency selective fading channels using orthogonal frequency division multiplexing (OFDM). Additionally, the multipath diversity available as frequency diversity could be potentially exploited by properly designed space-frequency LDC codes for MIMO-OFDM systems. In this paper, the design criteria to obtain such space-frequency LDC along with the error-rate performance of such codes in frequency selective fading channels are provided.

Closed-loop, rate-one, channel orthogonalized space-time block codes (CO-STBCs) for three and four transmit antennas using a single (real) phase feedback term have been proposed . These codes achieve full diversity and result in maximum likelihood (ML) decoding with only linear processing at the receiver similar to OSTBCs. In this paper, we propose a closed-loop STBC for five and six transmit antennas with rate 3/4, where the one parameter feedback angle can be evaluated in closed form. These codes achieve full diversity and are delay optimal. Simulation results comparing the error-rate performance of the CO-STBC with open-loop OSTBC as well as some quasiorthogonal space-time block codes are also provided. While the 1- to 5-dB gain accrued by the closed-loop scheme (over the open-loop methods) is not surprising, the novel contribution of this work is in the approach taken to derive the feedback parameter as a single phase term, which is purely a function of the channel gains.

In this letter, we investigate the effect of hopping pilots on the parametric channel estimation in orthogonal frequency-division multiplexing (OFDM) systems. Channel estimation algorithms based on parametric channel modeling require the multipath delays to be estimated at the receiver. The use of a fixed pilot pattern leads to longer training overhead in multipath delay estimation for slow fading channels. However, if hopping pilot patterns are available, then we show that the normalized mean-squared error (NMSE) convergence rate of the channel estimates can be significantly improved. We also show that hopping pilot patterns in OFDM systems effectively allow the eigenvectors of the delay subspace (of the autocorrelation matrix) to be estimated faster. Simulation results are provided to show the faster convergence rate of the NMSE for the hopping pilot pattern over the fixed pilot pattern.

We describe an algorithm for sparse channel estimation applicable to orthogonal frequency division multiplexing systems. The proposed algorithm uses a least squares (LS) technique for channel estimation and a generalized Akaike information criterion to estimate the channel length and tap positions. This effectively reduces the signal space of the LS estimator, and hence improves the estimation performance as demonstrated using computer simulations. For example, the proposed modified LS with sparse channel-estimation algorithm has a 5-dB lower mean square error in channel estimation when compared to the conventional approach , which translates to approximately 0.5 dB improvement in signal-to-noise ratio at the receiver.

Spatial correlation is introduced when antennas are not well separated, which typically leads to performance degradation in space diversity systems for flat fading wireless channels. However, in a frequency-selective environment with orthogonal frequency division multiplexing (OFDM), multipath diversity can help in overcoming this performance degradation. This is due to transformation of a highly spatially correlated channel impulse response to less spatially correlated channel frequency response inherently by an OFDM system in the presence of multipath diversity . In this letter, we numerically evaluate the minimum antenna separation required for a target spatial correlation in the frequency domain in situations with low multipath diversity. Performance results for two highly spatially correlated receive antennas with such spacing are provided for low multipath diversity channels and it is found to be within 1 dB (at BER=10/sup -3/) of spatially uncorrelated reception for QPSK modulation.

Tarokh et al. (1998) introduced the concept of space-time trellis coding as a means to combat fading by introducing redundancy, both in space and time. If the wireless channels are static or fade very slowly, the channel state information can be sent back to the transmitter using a low bit rate feedback path. In such a situation, it may be possible to mitigate the effects of signal cancellation due to simultaneous transmission, by using some sort of pre-processing technique at the transmitter (which incorporates the channel knowledge). However, we assume that no such feedback channel exists. Therefore, we address the issue of feedforward only pre-processing schemes at the transmitter. For fading channels, the error-rate performance depends on the effective code length, which is the length of the shortest error event path. The performance also depends on the minimum product distance which is computed from the maximum likelihood path and the other error paths with non-zero distance from it.