Utilizing low-resolution analog-to-digital converters (ADCs) in uplink massive multiple-input multiple-output (MIMO) systems is a practical solution to decrease power consumption. The performance gap between the low and high-resolution systems is small at low signal-to-noise ratio (SNR) regimes. However, at high SNR and with high modulation orders, the achievable rate saturates after a finite SNR value due to the stochastic resonance (SR) phenomenon. This paper proposes a novel pseudo-random quantization (PRQ) scheme by modifying the quantization thresholds that can help compensate for the effects of SR and makes communication with high-order modulation schemes such as 1024-QAM in one-bit quantized uplink massive MIMO systems possible. Moreover, modified linear detectors for non-zero threshold quantization are derived, and a two-stage uplink detector for single-carrier (SC) multi-user systems is proposed. The first stage is an iterative method called Boxed Newton Detector (BND) that utilizes Newton’s Method to maximize the log-likelihood with box constraints. The second stage, Nearest Codeword Detector (NCD), exploits the first stage solution and creates a small set of most likely candidates based on sign constraints to increase performance. The proposed two-stage method with PRQ outperforms the state-of-the-art detectors from the literature with comparable complexity while supporting high-order modulation schemes.

It is known that data rates in standard cellular networks are limited due to inter-cell interference. An effective solution to this problem is to use the multi-cell cooperation idea. In Cloud Radio Access Network (C-RAN), which is a candidate solution in 5G and future communication networks, cooperation is applied by means of central processors (CPs) connected to simple remote radio heads with finite capacity fronthaul links. In this study, we consider a downlink C-RAN with a wireless fronthaul and aim to minimize total power spent by jointly designing beamformers for fronthaul and access links. We consider the case where perfect channel state information is not available in the CP. We first derive a novel theoretical performance bound for the problem defined. Then we propose four algorithms with different complexities to show the tightness of the bound. The first two algorithms apply successive convex optimizations with semi-definite relaxation ideas where the other two are adapted from well-known beamforming design methods. The detailed simulations under realistic channel conditions show that as the complexity of the algorithm increases, the corresponding performance becomes closer to the bound.

Employing low resolution analog-to-digital converters in massive multiple-input multiple-output (MIMO) has many advantages in terms of total power consumption, cost and feasibility. However, such advantages come together with significant challenges in channel estimation and data detection due to the severe quantization noise present. In this study, we first derive linear minimum mean-square-error channel estimator for cyclic-prefix (CP) free single carrier MIMO (SC-MIMO) under frequency-selective channel. Then, we propose a novel iterative receiver for quantized CP-free uplink wideband SC-MIMO for uncorrelated or correlated Rayleigh and Rician fading channels. This detector utilizes an efficient message passing algorithm based on Bussgang decomposition, reduced state sequence estimation and Ungerboeck factorization. Therefore, it achieves remarkable complexity reduction and exhibits significant performance advantages compared to the existing quantized SC-MIMO receivers from the literature.

Massive multiple-input multiple-output (MIMO) systems have attracted much attention lately due to the many advantages they provide over single-antenna systems. Owing to the many antennas, low-cost implementation and low power consumption per antenna are desired. To that end, massive MIMO structures with low-resolution analog-to-digital converters (ADC) have been investigated in many studies. However, the effect of a strong interferer in the adjacent band on quantized massive MIMO systems have not been examined yet. In this study, we analyze the performance of uplink massive MIMO with low-resolution ADCs under frequency selective fading with orthogonal frequency division multiplexing (OFDM) in the perfect and imperfect receiver channel state information cases. We derive analytical expressions for the bit error rate and ergodic capacity. We show that the interfering band can be suppressed by increasing the number of antennas or the oversampling rate when a zero-forcing receiver is employed.

Massive multiple-input multiple-output (MIMO) systems have attracted much attention lately due to the many advantages they provide over single- antenna systems. Owing to the many antennas, low- cost implementation and low power consumption per antenna are desired. To that end, massive MIMO structures with one-bit analog-to-digital converters (ADC) have been investigated in many studies. However, the effect of a strong interferer in the adjacent band on one-bit quantized massive MIMO systems have not been examined yet. In this study, we analyze the performance of uplink massive MIMO with one-bit ADCs under frequency selective fading with orthogonal frequency division multiplexing (OFDM) in the perfect and imperfect receiver channel state information cases. We derive analytical expressions for the bit error rate and ergodic rate. We show that the interfering band can be suppressed by increasing the number of antennas or the oversampling rate when a zero-forcing receiver is employed.

Nonlinearities in various stages of a transmitter may hinder and restrict the transmission rate. As observed in many studies, outermost constellation points are usually more adversely affected by these impairments. To observe these effects, we utilize two power amplifier models that have different effects on transmitted signals. The Rapp model considers only amplitude deformation and the resultant in-phase and quadrature errors can be assumed to be independent on the receiver side. Unlike the Rapp model, the Saleh model exerts both amplitude and phase deformations and the phase deformation introduces correlation between the in-phase and quadrature errors according to our observations. In addition to the correlation, the variances of in-phase and quadrature errors may not be equal to each other. In this paper, we propose receivers that consider error variances of each quadrature amplitude modulation (QAM) symbol. We compare the performances of the receivers with those of other receivers that take average error variances into account for decoding. Furthermore, we propose a practical receiver that directly works on digitized observations based on a look-up table that keeps log-likelihood ratios of the quantized regions in order to reduce computational complexity.

High data rate demands of new generations of communication systems necessitate the use of higher and higher order QAM schemes. However, the nonlinearities in various stages of the transmitter may hinder the performance of higher order QAM and limit the transmission rate enhancements. As observed in many studies in the literature, outermost constellation points are usually more adversely affected by nonlinearities and larger regions of uncertainty form around them. We focus on nonuniform error vector magnitude (EVM) values of QAM symbols in this paper and present achievable rates. Furthermore, we propose a simplified receiver that considers the unequal EVM distribution by splitting the constellation into multiple regions and compare the performance of the receiver to that of a conventional receiver taking into account average EVM.

When the requirements of internet of things (IoT) and machine-type communication (MTC) are considered, the 5G technology needs to support high spectral efficiency and massive connectivity of users/devices, and the demand for low latency, short packet duration, low power, high mobility and diverse service types. In this paper, first a new multiple access technique belonging to the class of non-orthogonal multiple access (NOMA) based on multi-code signaling (MCS) is proposed for the uplink data transmission mode in severe multi-path fading channels in order to handle the key challenges of 5G technology. This new technique combines the index modulation in code domain with channel division multiple access (ChDMA) on which a novel receiver architecture is structured at significantly reduced complexity. Second, an efficient message passing algorithm (MPA), which realizes iterative maximum a posteriori probability (MAP) detection with linear complexity in the number of interfering users, is proposed. The novel feature of the proposed MPA stems from the use of Ungerboeck factorization, where the whitening filter is avoided before MAP detection. The joint task of equalization and multi-user detection (MUD) is fulfilled via the introduced Ungerboeck type sum-product algorithm (SPA) framework. This architecture for general NOMA transmission, operating on the resultant Ungerboeck type factor-graph (FG) with bidirectional feedback, achieves dramatic complexity reduction (compared to conventional FG based algorithms).

Use of 1-bit analog-to-digital converters in massive multiple-input multiple-output (MIMO) systems has been investigated widely due to the very low power consumption and implementation complexity they have. In this study, we present the benefits of temporal oversampling at the receiver side in 1-bit quantized uplink wideband massive MIMO systems. By expressing the oversampled system in a simple form, we derive the zero-forcing (ZF) detector. With ZF detector, oversampling provides up to 9 dB SNR gain in terms of symbol error rate compared to symbol rate sampling case. We also make the error rate analysis of such systems. Moreover, we show that the necessary number of antennas at the receiver side can be reduced significantly with temporal oversampling.

Owing to their low power consumption and cost, employing 1-bit analog-to-digital converters (ADC) in massive multiple-input multiple-output (MIMO) systems has attracted significant attention, which resulted in such systems to be examined widely in the recent literature. In our previous studies, benefits of temporal oversampling in 1-bit quantized uplink massive MIMO systems is investigated by employing a high complexity zero-forcing (ZF) detector. In this study, we propose a sequential linear receiver as an alternative to the existing ZF receiver for the temporal oversampling case in literature. The complexity of the proposed receiver for temporally oversampled uplink massive MIMO with 1-bit ADC increases linearly with block length while the complexity of the existing ZF receiver grows with the cube of block length. Furthermore, significant reduction for the delay in the estimation of the transmitted data symbols is achieved with the proposed receiver.

Low-resolution analog-to-digital converters (ADCs) have attracted much attention lately for massive multiple-input multiple-output (MIMO) communication and systems with large bandwidth. Especially, 1-bit ADCs are suitable for such systems due to their low-power consumption and cost. In this paper, we illustrate the benefits of using faster than symbol rate (FTSR) sampling in an uplink massive MIMO system with 1-bit ADCs in terms of symbol error rate (SER). We show that the FTSR sampling provides about 5-dB signal-to-noise ratio (SNR) advantage in terms of SER and achievable rate with a linear zero-forcing-type receiver. We also develop analytical bounds on the SER and achievable rate performance of uplink massive MIMO structures with 1-bit quantization for the FTSR scenario for the whole SNR region. The proposed analytical bound holds not only for the FTSR case but also to yield more accurate results compared with some other analytical expressions in the literature. Our results establish a tradeoff between temporal oversampling and the number of receive antennas.

Low resolution analog-to-digital converters (ADC) attracted much attention lately for massive multiple-input multiple-output (MIMO) communication and systems with high bandwidth. Especially, 1-bit ADCs are suitable for such systems due to their low power consumption and cost. In this study, we illustrate the benefits of using faster than symbol rate (FTSR) sampling in an uplink massive MIMO system with 1-bit ADCs in terms of symbol error rate (SER). We show that FTSR sampling provides about 4 dB signal-to-noise ratio (SNR) advantage in terms of SER with a linear low complexity zero-forcing type receiver. We also obtain an analytical bound for the SER performance of uplink massive MIMO structures with 1-bit quantization for the FTSR sampling scenario for low, medium and high SNR regimes. The proposed analytical bound is also applicable to no FTSR sampling case and shown to yield more accurate results compared to some other analytical expressions in the literature. Our results establish a tradeoff between temporal oversampling and the number of receive antennas.

Faster than symbol rate (FTSR) sampling is necessary once practical non-adaptive analog front-end filter and excess bandwidth are employed in case of unequally spaced channel taps. Based on this a novel FTSR sampled mismatched minimum mean square error (MMSE) time domain equalization (TDE) is proposed in response to cyclic prefix (CP) based block transmissions. Our results show that the proposed MMSE TDE implementation nearly introduces 3dB signal-to-noise ratio (SNR) advantage with respect to conventional symbol rate (SR) sampled CP based MMSE single carrier frequency domain equalization (SC-FDE) for an error rate of 10^-3 and 16 quadrature amplitude modulation (QAM).

In this paper, we propose a low complexity graph-based linear minimum mean-square-error (LMMSE) equalizer in order to remove inter-symbol and inter-stream interference in a multiple input multiple output (MIMO) communication. The proposed state space representation inflicted on the graph provides linearly increasing computational complexity with block length. In addition, owing to the Gaussian assumption used in the presented cycle-free factor graph, the complexity of the suggested equalizer structure is not affected by the size of the signaling space. In addition, we introduce an efficient way of computing extrinsic bit log-likelihood ratio values for the LMMSE estimation compatible with higher order alphabets, which is shown to perform better than the other methods in the literature. Overall, we provide an efficient receiver structure reaching high data rates in frequency selective MIMO systems, whose performance is shown to be very close to a genie-aided matched filter bound through extensive simulations.

We propose a low complexity graph-based linear minimum mean square error (LMMSE) equalizer which considers both the intersymbol interference (ISI) and the effect of non-white noise inherent in Faster-than-Nyquist (FTN) signaling. In order to incorporate the statistics of noise signal into the factor graph over which the LMMSE algorithm is implemented, we suggest a method that models it as an autoregressive (AR) process. Furthermore, we develop a new mechanism for exchange of information between the proposed equalizer and the channel decoder through turbo iterations. Based on these improvements, we show that the proposed low complexity receiver structure performs close to the optimal decoder operating in ISI-free ideal scenario without FTN signaling through simulations.

We propose a reduced complexity, graph based linear minimum mean square error (LMMSE) filter in which the non-white statistics of a random noise process are taken into account. Our method corresponds to block LMMSE filtering, and has the advantage of complexity linearly increasing with the block length and the ease of incorporating the a priori information of the input signals whenever possible. The proposed method can be used with any random process with a known autocorrelation function by use of an approximation to an autoregressive (AR) process. We show through extensive simulations that our method performs identical with the optimal block LMMSE filtering for Gaussian input signals.

In this paper, we propose a generic receiver based on optimum maximum likelihood sequence estimation (MLSE) employing a generalized Ungerboeck metric with significantly reduced complexity for the general class of M-ary quasi orthogonal signaling (MOS) in severe multipath fading channels. First, by using the factor graph (FG) of the obtained generalized Ungerboeck metric for MOS and sum-product algorithm (SPA) framework, a highly efficient reduced state sequence estimation (RSSE) algorithm is proposed that operates on forward and backward directions and is directly applied to unwhitened channel matched filter (CMF) and code matched filter outputs at symbol rate. The proposed structure, generating the a posteriori probabilities (APP) by bidirectional RSSE recursions, are substantiated with symbol rate bidirectional decision feedback (BDF) based on surviving paths in order to eliminate the post- and pre-cursor inter-symbol interference (ISI) as well as multi code interference (MCI) due to the non-ideal properties of the signaling waveforms and multipath channel. It appears as the unification of Ungerboeck type reduced trellis equalization framework for MOS and achieves near-optimum performance especially for channels with large dispersion. Second, we identify a bias term through an error probability analysis which helps us improve the proposed receiver's performance. Furthermore, a tight approximation for the bit error rate (BER) of the proposed receiver is derived. These analyses lead to significant insight on the selection of system parameters and clearly demonstrate the high performance and efficiency of the proposed scheme by a proper choice of the signaling parameters.

This paper extends some approximation methods that are used to identify closed form Bit Error Rate (BER) expressions which are frequently utilized in investigation and comparison of performance for wireless communication systems in the literature. By using this group of approximation methods, some expectation integrals, whose exact analyses are intractable and whose Monte Carlo simulation computations have high complexity, can be computed. For these integrals, by using the sampling property of the integrand functions of one or more arguments, reliable BER expressions revealing the diversity and coding gains are derived. Although the methods we present are valid for a larger class of integration problems, in this work we illustrate the method by showing the step by step derivation of the BER expressions for a canonical cooperative communication scenario as well as a network coded system scenario. The derived expressions agree with the simulation results for a very wide range of signal-to-noise ratio (SNR) values.

We propose a simple yet effective wireless network coding and decoding technique for a multiple unicast network. It utilizes spatial diversity through cooperation between nodes which carry out distributed encoding operations dictated by generator matrices of linear block codes. In order to exemplify the technique, we make use of greedy codes over the binary field and show that the arbitrary diversity orders can be flexibly assigned to nodes. Furthermore, we present the optimal detection rule for the given model that accounts for intermediate node errors and suggest a low-complexity network decoder using the sum-product (SP) algorithm. The proposed SP detector exhibits near optimal performance. We also show asymptotic superiority of network coding over a method that utilizes the wireless channel in a repetitive manner without network coding (NC) and give related rate-diversity trade-off curves. Finally, we extend the given encoding method through selective encoding in order to obtain extra coding gains.

The paper proposes a general framework for both time-domain (TD) and frequency-domain (FD) iterative blockwise equalization in single carrier (SC) wideband multiple-input multiple-output (MIMO) channels. First, a novel turbo blockwise operating equalizer structure is proposed by jointly optimizing the feed-forward and feedback filters at each iteration based on the minimum mean squared error (MMSE) criterion. Optimization of the filter coefficients, utilized for feed-forward equalization and decision feedback, is performed in both time and frequency domains, and the equivalence between them is established by unifying the iterative block equalization with the feed-forward and feedback filters in various domains. The corresponding filters are obtained analytically in a closed form as a solution of the constrained Wiener-Hopf equation with the use of average reliability information. Second, asymptotic performance and diversity analysis of the proposed single carrier frequency domain equalizer (SC-FDE) is carried out that leads to insights on the structures of the filters in the high SNR regime. Furthermore, we elaborate on the rate and diversity tradeoff of the space-time coded SC-FDE based on the proposed equalizer structure and the space-frequency coded OFDM systems. Performance comparison between the proposed SC-FDE scheme and OFDM is made. The proposed SC-FDE scheme performs very close to the genie-aided performance bounds and better than OFDM based transmission.

This paper investigates simple means of analyzing the error rate performance of a general q-ary Galois Field network coded detect-and-forward cooperative relay network with known relay error statistics at the destination. Equivalent relay channels are used in obtaining an approximate error rate of the relay network, from which the diversity order is found. Error rate analyses using equivalent relay channel models are shown to be closely matched with simulation results. Using the equivalent relay channels, low complexity receivers are developed whose performances are close to that of the optimal maximum likelihood receiver.

We propose a simple yet effective wireless network coding (NC) and decoding technique. It utilizes spatial diversity through cooperation between nodes which carry out distributed encoding operations dictated by generator matrices of linear block codes. For this purpose, we make use of greedy codes over the binary field and show that desired diversity orders can be flexibly assigned to nodes in a multiple unicast network, contrary to the previous findings in the literature. Furthermore, we present the optimal detection rule for the given model that accounts for intermediate node errors and suggest a network decoder using the sum-product algorithm. The proposed sum-product detector exhibits near optimal performance.

This paper presents a comparison between two transmit diversity schemes, namely space-time coding and time-switched transmit diversity (TSTD) over block-fading and time-varying multi-input single-output (MISO) channels with various channel parameters. The schemes are concatenated with outer channel codes in order to achieve spatio-temporal diversity. The analytical results are derived for the error performances of the systems and simulation results as well as outage probabilities are provided. It is demonstrated using the analytical and simulation results that TSTD may have a comparable error performance with the space-time coding techniques and it even outperforms the space-time codes in some scenarios. Our results indicate that TSTD can be suggested as an alternative to space-time codes in some time-varying channels especially due to its implementation simplicity.

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.

In wireless communications, knowledge of the channel coefficients is required for coherent demodulation. In this work, a blind channel estimation method based on the Lloyd-Max algorithm is proposed for single-tap fading channels. The algorithm estimates the constellation points for the received signal using the Lloyd-Max algorithm. The algorithm is investigated for frequency hopping systems with small hop durations and operating under partial-band jamming for both detecting the jammer and estimating the channel. The performance of the Lloyd-Max channel estimation algorithm is compared to the performance of pilot-based channel estimation algorithms and non-coherent demodulation and decoding. A special concatenated channel code is constructed to work with the proposed blind channel estimation due to the phase ambiguity in estimates.

A bidirectional LMS algorithm is considered for estimation of fast frequency-selective time-varying channels with a promise of near optimal tracking performance and robustness to parameter imperfections under various scenarios at a practical level of complexity. The performance of the algorithm is verified by the theoretical steady-state MSE analysis and experimental bit error rate (BER) results.

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.

In this paper, we propose a general framework for both time domain (TD) and frequency domain (FD) block iterative equalization schemes for wideband multiple-input multiple-output (MIMO) channels. The equalization systems are designed by jointly optimizing the forward and backward filters based on minimum mean square error (MMSE) criterion. The equivalence of block iterative TD and FD equalization with decision feedback is established by analytically showing that the same mean square error (MSE) is achieved by the two systems. Asymptotic performance of the studied block iterative FD equalization scheme is analyzed, and the rate-diversity tradeoffs of space time / frequency coded MIMO SC-FDE and MIMO OFDM are compared.

Cooperative relaying is a promising technique for improving the performance of weak communication links in wireless networks by exploiting spatial diversity induced by relay transmissions. This paper considers cooperative relaying schemes for a narrow- band frequency hopping system. A novel hybrid relaying scheme called opportunistic hybrid relaying, which is specifically designed for this system, is presented. Unlike most relaying schemes in the literature, opportunistic hybrid relaying uses bandwidth efficiently by allowing the relays to transmit in non-orthogonal channels without any considerable coordination overhead among the relays. A joint channel estimation and data detection scheme is considered to be used at the destination to combine relay signals. It is shown that this scheme compares favorably to similar relaying schemes in the literature in terms of average success rate.

In this study, the authors discuss the implementation of a low latency decoding algorithm for turbo codes and repeat accumulate codes and compare the implementation results in terms of maximum available clock speed, resource consumption, error correction performance and the data (information bit) rate. In order to decrease the latency a parallellised decoder structure is introduced for these mentioned codes and the results are obtained by implementing the decoders on a field programmable gate array. The memory collision problem is avoided by using collision-free interleavers. Through a proposed quantisation scheme and normalisation in forward/backward recursions, computational issues are handled for overcoming the overflow and underflow issues in a fixed point arithmetic. Also, the effect of different implementation styles are observed.

Block fading channels present a realistic model in many communication scenarios. We propose a method by which the outage probability of block fading channels can be evaluated in a straighforward and computationally efficient manner by utilizing the moment generating function of a single block's mutual information. The flexibility of moment generating functions helps obtain outage probabilities in various cases such as wideband noise jamming and multi-access interference. The effect of discrete input alphabets on outage is also investigated and turns out to be vital especially under interference.

We show that any joint probability mass function (PMF) can be expressed as a product of parity check factors and factors of degree one with the help of some auxiliary variables, if the alphabet size is appropriate for defining a parity check equation. In other words, marginalization of a joint PMF is equivalent to a soft decoding task as long as a finite field can be constructed over the alphabet of the PMF. In factor graph terminology this claim means that a factor graph representing such a joint PMF always has an equivalent Tanner graph. We provide a systematic method based on the Hilbert space of PMFs and orthogonal projections for obtaining this factorization.

The case of rotation, in use together with coding in a channel with B fading blocks, is analyzed in terms of diversity properties of the coded systems with multi-dimensional rotated constellations (coded-rotated system) output. First closed-form expression obtained is related to the diversity performance of unrotated generic coding structures with given minimum distance, d, block length, and number of fading blocks. Afterwards, another closed-form expression is derived for distinguishing the effect of rotation applied on the given coding structures. This latter expression yields a strict lower bound on the probability of attaining full diversity for any coded-rotated system and gives us a tool to evaluate the improvement with respect to systems involving only coding and also systems with only rotation. The results shown summarize the benefits of utilizing rotation together with coding, even in the cases of very simple non-full-diversity rotations like DFT rotations.

Single carrier frequency domain equalization (SC-FDE) is receiving considerable attention recently due to its comparable complexity and performance with OFDM. In this paper, an iterative SC-FDE with decision feedback in frequency domain is proposed for wideband multiple-input multiple-output (MIMO) channels and more general multipath vector channels as a generalization of previous works considering FDE with decision feedback for single-input single-output (SISO) systems. The proposed detector is based on iterative forward and backward filtering followed by a MIMO multi-stream detector that uses a priori log-likelihood ratios (LLR) of coded symbols. Forward and feedback filters are jointly optimized according to the minimum mean square error (MMSE) criterion to minimize both self inter-symbol-interference (ISI) and interference from other streams transmitted at different antennas. It has been observed that the proposed structure exploits the multi-path diversity sources of the channel effectively and a performance very close to MIMO-OFDM outage probability can be achieved. Therefore, our proposed iterative SC-FDE technique for MIMO wideband channels can be viewed as a strong alternative to MIMO-OFDM schemes with similar complexity.

The iterative channel estimation and tracking problem is considered for time-varying frequency-flat fading multi-input multi-output (MIMO) systems. In order to jointly estimate and track the time-varying multi-antenna channel, the pilot symbol assisted modulation (PSAM) technique is generalized to the multi-antenna systems. By distributing the pilot symbols along the transmitted block, i.e., PSAM transmission, the proposed system gains the ability to track the channel variation with the same amount of pilots whereas the system with all the pilots are employed prior to the data block has no tracking capability. The error performance is further improved by iteratively estimating the channel which employs the optimal MMSE filtering and also makes use of the soft probabilities of the coded symbols provided by the decoder. In order to decrease the computational complexity due to the iterative usage of MMSE filtering, we introduce the low-complexity 2-way LMS algorithm based on the forward-backward operation of conventional forward only LMS algorithm. By simulations, 2-way LMS is shown to have a near optimal error performance and highly better channel tracking ability than the conventional LMS algorithm with no significant complexity increase.

A low-complexity iterative channel estimation (ICE) algorithm is proposed with the promise of improved error performance. The new algorithm operates the LMS filter both in the forward and the backward directions along a block. The feedback from the decoder to the estimator is in the form of soft decisions. The pilot symbol assisted modulation (PSAM) is used as the transmission technique. The effect of code choice on various ICE algorithms is also explored by considering the blockwise concatenated codes initially offered for block-fading channels. The performance of the new estimation algorithm with the proposed coding is shown to outperform the conventional estimation algorithms over a fast time-varying Rayleigh fading channel beside its low complexity structure.

It is known that rotated multidimensional constellations can be used effectively to achieve full-rate and full-diversity transmission in block fading channels. However, optimal decoding complexity is exponential with the number of fading blocks (or degrees of freedom). In this paper, we propose a reduced-complexity iterative receiver structure operating on a block basis for coded modulation schemes with rotated constellations. The proposed detector is based on iterative forward and backward filtering followed by a channel decoder that uses a priori log- likelihood ratios (LLR) of coded symbols. Forward and feedback filters are jointly optimized according to the minimum mean square error (MMSE) criterion to minimize the spatial interference induced by rotation. It is observed that the proposed structure achieves full diversity and performance close to outage probability for rotated inputs even with simple Discrete Fourier Transform (DFT) rotations.

Our main goal in this paper is to construct codes that can perform close to information-theoretic limits in time-varying channels. For this purpose, a new turbo-like code is first proposed for the block-fading channel which achieves the same error performance of a recently introduced blockwise concatenated code but with a lower complexity. The effectiveness of the codes are verified by comparing them with information-outage probability. In order to take the advantage of time diversity in time-varying fading channels, we introduce two new codes which are indeed extensions of the ones for block-fading channels. We report that error performance of the proposed codes is close to information- theoretic limits in time-varying channels set out by information-outage probability.

We develop a technique to upper bound the point-to-point MIMO limited rate feedback (LRF) capacity under a wide class of vector quantization schemes. The upper bound turns out to be tight and can also be used to obtain an absolute upper bound by using a bounding distribution for Grassmannian beamforming. The bounding technique can be applied to other problems requiring the exact evaluation of the expected value of matrix determinant.

Serial concatenated codes show very good performance at low signal to noise ratios. However, large decoding delays due to long input frame lengths constitute a major disadvantage for these type of codes. In this study we introduce a new class of concatenated convolutional codes which are very suitable for parallel decoding, thus have much less decoding delays and also show comparable performance to that of classical serial concatenated convolutional codes. The analytical upper bound expressions for performance of the proposed structures are derived using the uniform interleaver concept.

Virtual antenna arrays can be constructed via relaying even in the case that there is insufficient physical space or other resources for multiple antennae on wireless nodes. When there is a multiple access scenario, relaying offers a variety of ways to establish communication between source and destination nodes. We will compare a scheme based on space division multiple access to previously studied time division based ones. We observe that space division improves especially the ergodic capacity.

Finite length analysis of iterative decoders can be done by using the probabilistic models based on EXIT charts. The validity of these models are investigated by checking the performance of iterative decoding under various scenarios.