In this paper, we consider the problem of spread pilot design and effective channel estimation in multiple-input multiple-output Zak-OTFS (MIMO-Zak-OTFS) with superimposed spread pilots, where data and spread pilot signals are superimposed in the same frame. To achieve good estimation performance in a MIMO setting, the spread pilots at different transmit antennas need to be effectively separated at the receiver. Towards this, we propose a spread pilot design that separates the pilot sequences in the cross-ambiguity domain and enables the estimation of the effective channel taps by a simple read-off operation. To further alleviate the effect of pilot-data interference on performance, we carry out turbo iterations between channel estimation and detection. Simulation results for $2\times 2$ and $3\times 3$ MIMO-Zak-OTFS with Gaussian-sinc pulse shaping filter for vehicular-A channel model show that the proposed pilot design and estimation scheme with three turbo iterations can achieve very good estimation/detection performance.

In orthogonal time frequency space (OTFS) modulation, the delay-Doppler (DD) spread in the channel causes interference across DD domain information symbols, degrading detection performance. In this paper, we propose and investigate a novel idea of DD channel projection in OTFS receivers towards the mitigation of interference due to DD channel spread. In conventional OTFS receivers, the received time domain (TD) signal is first transformed to frequency-time (FT) domain through a projection operation matched to the transmit waveform. The proposed idea in this paper is to achieve the TD to FT domain conversion without much distortion through the use of better orthonormal functions for projection. Towards this goal, the proposed receivers use projection functions that are based on DD channel knowledge. Two such receivers are proposed. The first receiver, termed as the effective path (EP) receiver, uses a projection function that is obtained based on an approximate characterization of the multipath channel as a channel with a single effective path, and the received signal is projected onto this effective path. A cost function is defined for this purpose, which is maximized to obtain the effective path. In the second receiver, termed as the concatenated paths (CP) receiver, the received signal is projected onto multiple paths and the resulting projected signals are concatenated to obtain the overall DD channel matrix. Simulation results show that the proposed EP and CP receivers offer good interference mitigation, resulting in significantly better performance compared to the conventional receiver.

In this paper, we consider the problem of inputoutput (I/O) relation estimation and signal detection in multipleinput multiple-output Zak-OTFS (MIMO-Zak-OTFS) systems. Towards this, we consider an embedded pilot framework, where pilot symbols meant for I/O relation estimation and data symbols co-exist in a given frame. We present an embedded pilot frame structure for a 2 × 2 MIMO-Zak-OTFS system and propose an I/O relation estimation scheme, considering different delay-Doppler (DD) pulse shaping filters, including sinc, Gaussian, and Gaussian-sinc filters. We evaluate the mean square error (MSE) performance of the proposed estimation scheme in Vehicular-A channel model with fractional delays and Dopplers. Our simulation results show that, due to its highly localized nature in the DD domain and hence low inter-symbol interference levels, Gaussian filter gives better MSE performance compared to the other two filters. Using the estimated I/O relation in a given frame, we detect the data symbols in the same frame using a local search based detection scheme. Our results show that, because of its good balance between main lobe and sidelobe characteristics, the Gaussian-sinc filter outperforms the other two filters in terms of bit error rate performance with estimated I/O relation.

Accurate estimation of the effective channel is crucial for reliable data detection in Zak-OTFS systems. Channel estimation using exclusive or embedded pilot frames with point pilot incurs throughput loss. In addition, frames with point pilot exhibit high peak-to-average power ratios. Superimposed spread pilot-based channel estimation can alleviate these issues. Conventional channel estimation using superimposed spread pilot involves computing the cross-ambiguity function and estimating the effective channel taps from a lattice that is twisted with respect to the period lattice on which the data signal is supported. However, this approach is affected by delay-Doppler (DD) domain aliasing in estimating the effective channel, and the estimation is further affected due to interference from the data signal and receiver noise. This compromises the estimation quality, which affects the detection performance. In this work, we propose a learning-based framework to enhance the estimation performance. Specifically, we propose a novel approach that treats the cross-ambiguity read-off as a two-dimensional (2D) image and uses a convolutional neural network (CNN) designed to enhance this image by jointly suppressing the DD aliasing and data interference, and denoising. Our simulation results with Vehicular-A channel model with fractional delays and Dopplers demonstrate that the proposed CNN-aided solution outperforms the conventional estimation method in terms of normalized mean squared error and bit error rate (BER), and achieves a BER performance close to that with perfect channel knowledge.

In this paper, we are concerned with Zak transform-based orthogonal time frequency space (Zak-OTFS) modulation in a multiple-input multiple-output (MIMO) setting with multiple antennas at the transmitter and receiver. We consider the problem of input-output (I/O) relation estimation and signal detection in MIMO-Zak-OTFS. Our contributions in this paper are as follows. First, we derive the system model for MIMO-Zak-OTFS. Next, we propose an I/O relation estimation scheme for MIMO-Zak-OTFS in a model-free framework. We evaluate the mean square error (MSE) performance of the proposed estimation scheme in Veh-A channel model with fractional delays and Dopplers, for different delay-Doppler (DD) pulse shaping filters, namely, sinc, Gaussian, and Gaussian-sinc filters. Gaussian filter is found to offer better MSE performance compared to sinc and Gaussian-sinc filters, because of the very low side lobes in Gaussian filter. Further, we assess the MIMO-Zak-OTFS signal detection performance using the estimated I/O relation. In this, Gaussian-sinc filter is found to achieve better bit error rate (BER) performance because of the good balancing characteristics of its main lobe and side lobes. We also show that a low-complexity local search based algorithm improves the minimum mean square error (MMSE) detection performance of MIMO-Zak-OTFS.

Zak-OTFS is a promising modulation scheme for$\mathbf{6 G}$and beyond due to its enhanced resilience to high Dopplers and its structured input-output relation through twisted convolution operation. In this paper, we analyze the diversity performance of Zak-OTFS under maximum-likelihood (ML) detection and perfect delay-Doppler (DD) domain channel state information (CSI). Our analysis provides a condition in the design of pulse shaping filters to achieve full DD domain diversity. Our results show that sinc and Gaussian filters achieve full DD diversity in Zak-OTFS. This is in contrast with the widely investigated multicarrier (MC) version of OTFS (MC-OTFS), whose diversity order is one and requires phase rotation operation on the transmit vector to achieve full DD diversity. Further, we analyze the bit error performance of Zak-OTFS under imperfect CSI. We carry out the analysis for 1) the mismatched ML detector, where the channel matrix in the conventional ML decision rule is replaced with the estimated channel matrix, and 2) the true ML detector which takes into account the CSI error statistics in the ML decision rule, and quantify the performance gap between the two detectors.

Zak transform-based orthogonal time frequency space (Zak-OTFS), a delay-Doppler (DD) domain modulation, is well-suited for general wireless channels, including channels which are highly doubly-dispersive in nature. Accurate inputoutput (I/O) relation estimation and signal detection at the receiver are crucial for reliable communication. In this paper, we propose a deep neural network (DNN) based Zak-OTFS receiver that jointly performs I/O relation estimation and signal detection, considering an exclusive pilot frame. We focus on two commonly considered DD pulse shaping filters, namely, sinc and Gaussian filters, to demonstrate the effectiveness of the DNN approach. A fully-connected DNN is trained to jointly learn the DD channel within a spatial coherence period and optimize the detection performance. Our simulation results demonstrate that the proposed DNN approach outperforms the conventional approach where model-free I/O relation estimation and minimum mean square error detection are performed separately.

Recently, there has been an increasing interest in the emerging Zak transform based orthogonal time frequency space (OTFS), termed Zak-OTFS, owing to 1) its increased resilience to high Dopplers (compared to the multicarrier version of OTFS (MC-OTFS) that has been widely studied in the past) due to its non-fading attribute, and 2) its structured input-output relation through twisted convolution operation, which renders the input-output relation to be predictable. Zak-OTFS research is in its nascent stages and several aspects of Zak-OTFS remain open for investigation. In this paper, we investigate one such aspect, namely, signal detection in Zak-OTFS. Early papers on Zak-OTFS have considered only minimum mean square error (MMSE) detection, whose performance is far from optimum. In this work, we consider an approximate maximum a posteriori probability (MAP) detection algorithm based on mixed Gibbs sampling (MGS), where sampling is done on a mixed distribution (a weighted mixture of the target distribution and uniform distribution). The mixing with uniform distribution helps to alleviate the stalling problem witnessed in sampling purely from the target distribution. The MGS algorithm is shown to achieve better performance compared to MMSE detection as well as message passing (MP) detection, which is a widely adopted detection scheme in MC-OTFS research, and achieves near optimal performance. The closeness to optimum maximum-likelihood (ML) performance is established using a lower bound on the ML performance obtained using reactive tabu search.

Orthogonal time frequency space (OTFS) modulation is emerging as a promising alternative to currently deployed multicarrier modulation schemes, particularly in high-Doppler wireless channels. The multicarrier (MC) version of OTFS (MC-OTFS) has dominated the OTFS research literature so far due to its compatibility with the prevailing MC modulation schemes. Recently, Zak transform based OTFS (Zak-OTFS) has gained prominence on account of its superior performance and low complexity. However, unlike in its MC counterpart, the transceiver signal processing aspects like equalization/detection and channel estimation in Zak-OTFS remain vastly unexplored. In this paper, we present an early investigation of low-complexity detection algorithms for Zak-OTFS that can scale efficiently for large frame sizes and achieve near-optimal performance. For this, we resort to efficient local search algorithms, namely, likelihood ascent search (LAS) and reactive tabu search (RTS) algorithms, that scale well for large dimensions. To assess the closeness of the performance of these algorithms to the optimum maximum likelihood (ML) performance, we obtain a lower bound on ML performance via RTS simulation using the transmit vector as the initial vector and defining a suitable neighborhood. Our simulation results indicate that while the performance of the popularly known minimum mean square error (MMSE) and message passing (MP) algorithms are far from the ML performance bound, LAS and RTS algorithms initialized with MMSE solution achieve close to ML performance bound within about 1 dB at a bit error rate of 10−5.

Orthogonal time frequency space (OTFS) modulation provides robust communication in doubly-selective channels owing to its non-fading nature in the delay-Doppler (DD) domain. In this paper, for the first time in the literature, we propose a novel transmission scheme where the performance of OTFS is further enhanced through the use of channel modulation (a.k.a media-based modulation). In channel modulation (CM), radio frequency (RF) mirrors placed in the near-field of the transmit antenna are controlled by information bits, which create different channel fade realizations that form the CM alphabet. The proposed OTFS-CM scheme is shown to simultaneously offer the benefits of robustness to high-Doppler due to DD signal processing in OTFS and an additional SNR gain due to the improved distance properties of the signal set due to CM. For example, simulation results show that, at a bit error rate (BER) of $10^{-4}$, the proposed OTFS-CM scheme achieves an SNR gain of about 1 to 4 dB compared to OTFS without CM, which is attributed to the enhanced distance profile of the OTFS-CM signal set. For the same reason, the SNR gain increases with increase in the dimensionality of the signal at the receiver and the number of RF mirrors.

Orthogonal time-frequency space (OTFS) modulation has been shown to be robust in channels with high Doppler spreads. Conventional approach of OTFS signaling involves two steps, viz., conversion from delay-Doppler (DD) domain to time-frequency (TF) domain and then to time domain (TD) for transmission. A more direct approach converts the DD domain symbols to TD directly using the inverse Zak transform in one step, which is performance-wise better for large channel spreads. In this paper, we consider discrete Zak transform based OTFS (DZT-OTFS) and propose a deep learning based low-complexity channel estimation algorithm for fractional DD channels. The proposed approach learns the delay-Doppler matrix (DDM) through training rather than analytically computing it explicitly, and this drastically reduces complexity. A key novelty in the proposed approach is that learning is carried out in the TF domain for DD domain channel estimation. This is motivated by the observation that the values in the channel matrix in TF domain has a smaller swing compared to that in DD domain, which is more favorable for training. Simulation results show that the proposed TF learning based channel estimation achieves almost the same performance as that of a state-of-the-art algorithm in the literature but at a significantly lesser complexity, making the proposed approach practically appealing.

Discrete Zak transform (DZT) based orthogonal time frequency space (OTFS) modulation provides robustness in high-mobility wireless channels and benefits in implementation complexity. Channel modulation (CM) and index modulation (IM) are promising physical layer techniques that offer improved spectral efficiencies and bit error performance. In this paper, we propose an OTFS-CM-IM scheme that integrates CM and delay-Doppler (DD) domain indexing that enhances the performance of DZT-OTFS. For the proposed OTFS-CM-IM scheme, we derive a compact input-output relation which enables system simulations and the computation of an upper bound on the bit error performance and the distance properties of the signal set. We consider two types of DD indexing, one with constellation indexing and one without. Our simulation results show that the proposed OTFS-CM-IM scheme performs better than the OTFS scheme (without CM and IM) and the OTFS-CM scheme (without IM). This enhanced performance is attributed to the improved distance properties of the proposed OTFS-CM-IM signal set.

Motivated by its inherent robustness to Doppler spread, Zak transform-based orthogonal time-frequency space (OTFS) modulation has emerged as a promising candidate for next-generation wireless technologies, particularly in the 6G and beyond framework. In this paper, we introduce a novel channel estimation algorithm for discrete Zak transform (DZT)-based OTFS, employing a superimposed pilot frame structure and capable of accommodating arbitrary pulse shapes and fractional delay-Dopplers (DD). The proposed algorithm leverages the DD channel invariance across multiple OTFS frames, which offers the benefit of multiple measurements in channel estimation. Extensive simulation results demonstrate that the proposed algorithm achieves good bit error rate (BER) and normalized mean square error (NMSE) performance, showcasing its effectiveness in practical communication settings. Impact of the use of different detectors on the iterative channel estimation/ detection performance is also studied.

Recently, Zak transform based orthogonal time frequency space (OTFS) waveform has generated new research interest owing to its better robustness to large channel spreads compared to that of the widely researched OTFS waveform based on inverse symplectic finite Fourier transform (ISFFT) and Heisenberg transform (HT). In this paper, we investigate the peak-to-average power ratio (PAPR) characteristics of discrete Zak transform based OTFS (DZT-OTFS), which has not been reported. We derive an upper bound on the PAPR of DZT-OTFS waveform for general transmit pulse shapes and a tighter upper bound for rectangular pulse, using Cauchy-Schwartz inequality. The PAPR upper bound for DZT-OTFS and two-step OTFS (based on ISFFT and HT) are shown to be the same for rectangular pulse, and hence the PAPR of DZT-OTFS with rectangular transmit pulse shape grows linearly in the number of Doppler bins. With non-rectangular transmit pulse, the results on complementary cumulative distribution function (CCDF) of PAPR show that DZT-OTFS can have better PAPR characteristics compared to that of two-step OTFS.

Reconfigurable intelligent surfaces (RIS) technology, orthogonal time frequency space (OTFS) modulation, and index modulation (IM) are promising physical layer techniques in wire-less communications. An RIS system steers the electromagnetic wave towards the receiver using an electronically tunable surface. OTFS delivers robust performance in high mobility scenarios using information signalling in the delay-Doppler (DD) domain, and IM can offer improved spectral efficiencies and bit error performance. In this paper, we propose an RIS-aided OTFS scheme in which IM is carried out in the DD domain. We call the proposed scheme as RIS-aided OTFS-IM scheme. We develop an end-to-end DD domain input-output relation for the proposed RIS-aided OTFS-IM scheme and evaluate its bit error performance. Our results show that 1) the performance of RIS-aided OTFS improves significantly with the proposed DD domain indexing and increased number of RIS elements, 2) among the phase selection schemes considered at the RIS, Frobenius norm based phase selection achieves superior performance, and 3) RIS-aided OTFS-IM performs better than RIS-aided OFDM-IM.

In orthogonal time frequency space (OTFS) modulation, Zak transform approach is a natural approach for converting information symbols multiplexed in the DD domain directly to time domain for transmission, and vice versa at the receiver. Past research on OTFS has primarily considered a two-step approach where DD domain symbols are first converted to time-frequency domain which are then converted to time domain for transmission, and vice versa at the receiver. The Zak transform approach can offer performance and complexity benefits compared to the two-step approach. This paper presents an early investigation on the bit error performance of OTFS realized using discrete Zak transform (DZT). We develop a compact DD domain input-output relation for DZT-OTFS using matrix decomposition that is valid for both integer and fractional delay-Dopplers. We analyze the bit error performance of DZT-OTFS using pairwise error probability analysis and simulations. Simulation results show that 1) both DZT-OTFS and two-step OTFS perform better than orthogonal frequency division multiplexing (OFDM), and 2) DZT-OTFS achieves better performance compared to two-step OTFS over a wide range of Doppler spreads.

Reconfigurable intelligent surface (RIS) technology uses electronically tunable surfaces in the far field of the transmit antenna for the purpose of beamforming towards receiver of interest. Media-based modulation (MBM) uses such surfaces in the near field of the transmit antenna for the purpose of modulation. RIS-aided MBM offers improved communication performance at low radio-frequency (RF) hardware complexity, combining the good attributes of both RIS and MBM. In this paper, we analyze the performance of RIS-aided MBM in the presence of imperfect channel state information (CSI) at the receiver and phase tuning errors at the RIS. We derive expressions for pairwise error probability and bit error probability for RIS-aided MBM with imperfect CSI and phase tuning errors. Bit error rate performance results obtained through analysis and simulations are presented. Results show improved bit error performance for increased number of RIS elements.

In this paper, we analyze the performance of multiple-input multiple-output orthogonal time frequency space (MIMO-OTFS) modulation with selective decode-and-forward (SDaF) relaying. Communication between the sender and destination nodes happens in two hops using multiple relays out of which some selected relays aid the communication. All the nodes are provided with multiple transmit and multiple receive antennas. We derive closed-form expressions for the end-to-end pairwise error probability and bit error probability upper bounds in MIMO-OTFS with SDaF relaying, and characterize the achieved asymptotic diversity orders. We also investigate the considered system when phase rotation of OTFS frames is performed to improve the diversity performance. Simulation results are shown to validate the analytically predicted diversity results.

Orthogonal time frequency space (OTFS) modulation and index modulation (IM) are promising techniques in wireless communications. OTFS excels in high mobility scenarios by using information signaling in the delay-Doppler domain, while IM offers improved spectral efficiencies and bit error performance. In this study, we analyze the performance of OTFS with IM (OTFS-IM) in a decode-and-forward (DaF) relay communication system. The communication involves two hops between the transmitter, receiver nodes through a relay node. We derive a closed-form expression for the end-to-end pairwise error probability in OTFS-IM with DaF relaying and assess the achieved asymptotic diversity order. Our simulation results show that i) the use of indexing improves the performance of OTFS with DaF relaying ii) the simulated upper bound on the bit error rate (BER) validates the analytically predicted diversity orders.

In this paper, we analyze the performance of multiple-input multiple-output orthogonal time frequency space (MIMO-OTFS) modulation with decode and forward (DaF) relaying. Communication between the transmitter and receiver nodes happens through a relay node in two hops. All the nodes are provided with multiple transmit and multiple receive antennas. We derive a closed-form expression for the end-to-end pairwise error probability in MIMO-OTFS with DaF relaying and characterize the achieved asymptotic diversity order. We also investigate the considered system when phase rotation of OTFS frames is performed to improve the diversity performance. Simulation results are shown to validate the analytically predicted diversity performance.

In this paper, we consider the problem of delay-Doppler (DD) channel estimation in orthogonal time frequency space (OTFS) modulation with fractional delays and Dopplers. Exclusive use of DD bins in a frame for pilot symbols causes rate loss. Superimposing pilot symbols over data symbols avoids this rate loss. Our contributions in this paper are two-fold. 1) We propose a sparse superimposed pilot (SSP) scheme where pilot and data symbols are superimposed in a few bins and the remaining bins carry data symbols only. This scheme offers the benefit of better inter-symbol leakage profile in a frame, while retaining full rate. 2) For the SSP scheme, we propose a recurrent neural network based learning architecture (referred to as SSPNet) trained to provide accurate channel estimates overcoming the leakage effects in channels with fractional DD. Simulation results show that the proposed SSP scheme along with fractional DD channel estimation using the proposed SSPNet performs better than a fully superimposed pilot scheme.

Orthogonal time frequency space (OTFS) implementation using discrete Zak transform (DZT) has performance and complexity advantages in channels with high Doppler spreads. In this paper, we propose a data-aided approach to channel estimation in DZT-based OTFS systems with fractional delays and Dopplers. The proposed method employs an embedded pilot frame (consisting of pilot and data symbols) for channel estimation and leverages detected data to enhance channel estimation accuracy. The algorithm adopts a path-by-path approach where the channel parameters for one path are estimated before proceeding to the next, without assuming the knowledge of the number of paths. Considering the embedded nature of the pilot and data symbols in a frame, the effect of data signal-to-noise ratio (SNR) on the channel estimation performance and the effect of pilot SNR on the data detection performance are evaluated, leading to the data-aided approach to achieve improved performance. Simulation results show that the proposed estimation algorithm achieves significantly better performance compared to threshold based estimation algorithm.

Reconfigurable intelligent surface (RIS) technology and media based modulation (MBM) are promising physical layer techniques in wireless communication. While RIS uses electronically tunable surfaces in the far field of the transmit antenna(s) for the purpose of beamforming towards the receiver of interest, MBM uses such surfaces in the near field for the purpose of modulation. Both RIS and MBM offer improved communication performance at low radio-frequency (RF) hardware complexity. In this paper, we investigate MBM aided by RIS and show interesting performance results. We develop the system model for an RIS-aided MBM (RIS-MBM) system and analyse its bit error performance through analysis and simulation. For this system, we propose two schemes for optimizing the phases at the RIS, one maximizing the Frobenius norm of the channel and the other maximizing a bound on the achievable rate. We also compare the performance of RIS-aided MBM with that of RIS-aided generalized spatial modulation (RIS-GSM). Our results show that i) the performance of MBM improves with the use of RIS, ii) RIS phase optimization using rate maximization is better compared to that using Frobenius norm maximization, and iii) for a given rate, RIS-aided MBM achieves better performance compared to RIS-aided GSM.

Traditional orthogonal time frequency space (OTFS) channel estimation schemes dedicate an entire frame or a part of the frame for accommodating pilot and guard symbols to avoid pilot-data interference, which compromises spectral efficiency. This spectral efficiency loss can be avoided using superimposed pilots, where delay-Doppler (DD) bins in the OTFS frame carries both data and pilot symbols. In this paper, we propose a sparse superimposed pilot scheme for channel estimation, where all the DD bins in a frame carry data symbols and pilot symbols are superimposed over some of them, sparsely. The proposed scheme does not suffer spectral efficiency loss due to pilot/guard symbols. It also has the advantage of more localized pilot-data interference profile that leads to better performance. We derive the minimum mean square error (MMSE) channel estimator for the proposed scheme. We obtain optimum number of pilot symbols per frame and power distribution among data and pilot symbols through simulations. Simulation results show that the proposed scheme achieves better performance at a lesser complexity compared to existing superimposed pilot scheme. An iterative scheme that further improves performance is also proposed.

Two research topics, namely, reconfigurable intelligent surfaces (RIS) and orthogonal time frequency space (OTFS) modulation, have drawn significant interest in recent wireless research. While RIS technology can aid communication by favorably controlling the electromagnetic wave propagation towards the receiver, OTFS modulation can offer robust performance in high-Doppler channels. Both RIS and OTFS are envisioned to be promising technologies for 6G and beyond. This paper investigates a RIS-aided OTFS system. A novel and useful contribution in this paper is the detailed derivation of the end-to-end delay-Doppler (DD) domain input-output relation of a RIS-aided OTFS system, which can serve as a basic system model that can aid the investigation of efficient transceiver techniques/algorithms, performance evaluation, and implementation. We consider maximization of the Frobenius norm of the effective end-to-end DD channel matrix of the RIS-aided OTFS system to choose the phase vector at the RIS. Our simulation results show that RIS-aided OTFS performs significantly better compared to RIS-aided OFDM.

In this paper, we propose a learning based architecture for estimating the delay-Doppler (DD) channel in orthogonal time frequency space (OTFS) systems with embedded pilots. The proposed learning network, called DDNet, is based on a multi-layered recurrent neural network (RNN) framework with a novel training methodology that works seamlessly for both exclusive pilot frames as well as embedded pilot frames. This generalization is attributed to the training methodology, wherein multiple frame realizations with different guard band sizes are used to train the network. Simulation results demonstrate that the proposed DDNet achieves better mean square error and bit error performance compared to impulse based and threshold based DD channel estimation schemes.

Traditionally, channel estimation in orthogonal time frequency space (OTFS) is carried out in the delay-Doppler (DD) domain by placing pilot symbols surrounded by guard bins in the DD grid. This results in reduced spectral efficiency as the guard bins do not carry information. In the absence of guard bins, there is leakage from pilot symbols to data symbols and vice versa. Therefore, in this paper, we consider an interleaved pilot (IP) placement scheme with a lattice-type arrangement (which does not have guard bins) and propose a deep learning architecture using recurrent neural networks (referred to as IPNet) for efficient estimation of DD domain channel state information. The proposed IPNet is trained to overcome the effects of leakage from data symbols and provide channel estimates with good accuracy (e.g., the proposed scheme achieves a normalized mean square error of about 0.01 at a pilot SNR of 25 dB). Our simulation results also show that the proposed IPNet architecture achieves good bit error performance while being spectrally efficient. For example, the proposed scheme uses 12 overhead bins (12 pilot bins and no guard bins) for channel estimation in a considered frame while the embedded pilot scheme uses 25 overhead bins (1 pilot bin and 24 guard bins).

In this paper, we analyze the effect of imperfect delay-Doppler channel state information (CSI) on the bit error rate (BER) performance of orthogonal time frequency space (OTFS) modulation. We carry out the BER analysis when a mismatched maximum-likelihood (ML) detector is used, i.e., when an estimated channel matrix is used for detection in place of the true channel matrix. We derive an exact expression for the pairwise error probability (PEP) using the characteristic function of the decision statistic. Using the PEP expression, we obtain an upper bound on the BER. Our results show that the BER bound is tight at high SNRs. We also obtain the decision rule for the true ML detector with imperfect CSI, which takes into account the delay-Doppler channel estimation error statistics. We quantify the performance gap between the true ML detector and the mismatched ML detector through simulations.

Orthogonal time frequency space (OTFS) modulation is a recently introduced modulation which has been shown to perform better than OFDM in RF wireless communications. In this paper, we investigate OTFS in multi-LED indoor visible light wireless communications. We propose two multi-LED OTFS schemes, namely, quadrature spatial modulation OTFS (QSMOTFS) scheme and dual mode index modulation OTFS (DMIMOTFS) scheme. The proposed schemes use dual-LED complex modulation as the basic building block and offer enhanced rates compared to conventional index modulation schemes. The schemes also have the advantage of not requiring Hermitian symmetry and DC bias operations to obtain real, positive-valued signals suited for intensity modulation of LEDs. We obtain upper bounds on the bit error rate performance of the proposed schemes, which are tight at high signal-to-noise ratios. The proposed OTFS schemes are shown to perform better than their OFDM counterparts known in the literature. In addition, the spatial distribution of the performance gap between OTFS and OFDM across the room is captured using the ratio of the minimum distance of normalized received signal sets of the considered schemes as a metric.

Orthogonal time frequency space (OTFS) waveform based millimeter wave (mmWave) MIMO systems are capable of achieving high data rates in high-mobility scenarios. Hence, transceivers are designed for both analog beamforming (AB) and hybrid beamforming (HB), where we commence by deriving the delay-Doppler (DD)-domain input-output relationship considering a delay-Doppler-angular domain channel model. Subsequently, a novel two-stage procedure is developed for transmit beamformer (TBF)/ precoder (TPC) and receiver combiner (RC) design, and for estimating the DD-domain’s equivalent channel state information (CSI). The key feature of the proposed framework is that the RF TBF/ TPC and RC design maximizes the directional beamforming gains. It is also demonstrated that the low-dimensional baseband CSI of the DD-domain becomes sparse for mmWave-AB MIMO OTFS systems, and block-sparse for mmWave-HB MIMO OTFS systems. Subsequently, Bayesian learning (BL) and block-sparse BL (BS-BL) solutions are developed for improved CSI estimation. We also derive the Bayesian Cramer-Rao lower bounds (BCRLB) for benchmarking the mean-squared-error (MSE) of the CSI estimates. Finally, our simulation results demonstrate the improved efficacy of the proposed transceiver designs and confirm the enhanced CSI estimation performance of the BL-based schemes over other competing sparse signal recovery schemes.

In this paper, we investigate orthogonal time frequency space (OTFS) modulation in multi-LED indoor visible light wireless communications. Specifically, we propose two quad-LED OTFS schemes, namely, 1) quad-LED complex modulation OTFS (QCM-OTFS), and 2) spatial modulation dual-LED complex modulation OTFS (SM-DCM-OTFS). The proposed QCM-OTFS scheme sends the magnitudes of real and imaginary parts of complex signals through intensity modulation (IM) and their sign information through spatial indexing of LEDs. The proposed SM-DCM-OTFS scheme sends the magnitude and phase of complex signals (polar representation) through a pair of LEDs and frame indexing across two pairs of LEDs. The proposed schemes do not require Hermitian symmetry and DC bias operations to obtain real positive valued signals suited for IM of LEDs. We obtain upper bounds on the bit error rate (BER) performance of the proposed schemes, which are tight at high signal-to-noise ratios (SNR). Compared to the QCM-OFDM and SM-DCM-OFDM schemes known in the literature, the proposed schemes achieve significantly better BER performance. We also analyze the spatial distribution of the SNR gain in the proposed QCM-OTFS/SM-DCM-OTFS schemes compared to QCM-OFDM/SM-DCM-OFDM schemes using the ratio of minimum distance of normalized received signal sets as a metric.

In this paper, we present a deep neural network (DNN) based transceiver architecture for delay-Doppler (DD) channel training and detection of orthogonal time frequency space (OTFS) modulation signals along with IQ imbalance (IQI) compensation. The proposed transceiver learns the DD channel over a spatial coherence interval and detects the information symbols using a single DNN trained for this purpose at the receiver. The proposed transceiver also learns the IQ imbalances present in the transmitter and receiver and effectively compensates them. The transmit IQI compensation is realized using a single DNN at the transmitter which learns and provides a compensating modulation alphabet (to pre-rotate the modulation symbols before sending through the transmitter) without explicitly estimating the transmit gain and phase imbalances. The receive IQI imbalance compensation is realized using two DNNs at the receiver, one DNN for explicit estimation of receive gain and phase imbalances and another DNN for compensation. Simulation results show that the proposed DNN-based architecture provides very good performance, making it as a promising approach for the design of practical OTFS transceivers.

In this paper, we consider transmit antenna selection (TAS) in orthogonal time frequency space (OTFS) modulation and analyze its performance. We assume that the channel is quasi-static in the delay-Doppler (DD) domain and there is limited feedback from the receiver to the transmitter. The diversity performance of TAS is analyzed in a multiple-input multiple-output OTFS (MIMO-OTFS) system. Antenna selection is done based on the maximum channel Frobenius norm in the DD domain, where nsantennas are selected out of nttransmit antennas. Our analysis for one resolvable path in the DD channel (i.e., P = 1) shows that i) when ns= 1, full spatial diversity of nrnt(i.e., full receive diversity of nrand full transmit diversity of nt) is achieved since the underlying symbol difference matrix is full rank, and ii) when ns> 1, only nrth order receive diversity is achieved because of rank deficiency. Simulation results are shown to validate the analytically predicted diversity performance. For P > 1, diversity orders are predicted through rank of the difference matrices, validated through computation of pairwise error probability (PEP) bounds and simulations.

In this paper, we investigate indexing of delay-Doppler (DD) bins in orthogonal time frequency space (OTFS) modulation and propose indexing designs that enhance the diversity order of OTFS. It has been shown in the literature that the asymptotic diversity order of conventional OTFS (without indexing) is just one. In this paper, we show that indexing in the DD domain in OTFS can be used to enhance the asymptotic diversity order to two. Towards this, we consider 2-dimension indexing in OTFS, where indexing is done along both delay as well as Doppler axes. We achieve the enhanced diversity order of two by proposing indexing designs that provably eliminate all the rank one difference matrices. Our simulation results also validate this analytically proven diversity order of two in indexed OTFS. In addition, indexing is shown to offer improved PAPR (peak-to-average power ratio) performance of OTFS.

In this paper, we consider the problem of low-complexity detection of orthogonal time frequency space (OTFS) modulation signals using deep neural networks (DNN). We consider a DNN architecture in which each symbol multiplexed in the delay-Doppler grid is associated with a separate DNN. The considered symbol-level DNN has fewer parameters to learn compared to a full DNN that takes into account all symbols in an OTFS frame jointly, and therefore has less complexity. Under the assumption of static multipath channel with i.i.d. Gaussian noise, our simulation results show that the performance of the symbol-DNN detection is quite close to that of the full-DNN detection as well as the maximum-likelihood (ML) detection. Further, when the noise model deviates from the standard i.i.d. Gaussian model (e.g., non-Gaussian noise with t-distribution), because of its ability to learn the distribution, the symbol-DNN detection is found to perform better than the ML detection. A similar performance advantage is observed in multiple-input multiple-output OTFS (MIMO-OTFS) where the noise across multiple received antennas are correlated.

In this paper, we investigate the use of a new modulation scheme recently introduced in the RF domain, called orthogonal time frequency space (OTFS) modulation, in an indoor visible light communication (VLC) setting. In particular, we consider VLC systems that employ dual-LED schemes for transmission. The following dual-LED schemes are considered: 1) non-DC biased (NDC) scheme, and 2) dual-LED complex modulation (DCM) scheme. The proposed NDC-OTFS scheme uses 2-dimension (2D) Hermitian symmetry operation to convert complex signals to positive, real-valued signals suitable for transmission in the optical domain, and the proposed DCM-OTFS scheme achieves this by exploiting the polar representation of complex signals. We obtain analytical upper bounds on the bit error performance of the proposed NDC-OTFS and DCM-OTFS schemes, which are found to be tight at high signal-to-noise ratios (SNR). Our analytical and simulation results show that the proposed NDC-OTFS and DCM-OTFS schemes achieve better performance, respectively, compared to NDC-OFDM and DCM-OFDM schemes known in the VLC literature. Further, using the ratio of the minimum distance of different normalized received signal sets as a metric, we quantify the spatial distribution of the SNR gain of the proposed NDC-OTFS/DCM-OTFS schemes compared to NDC-OFDM/DCM-OFDM schemes.

In this paper, we design transceivers for fading channels using autoencoders and deep neural networks (DNN). Specifically, we consider the problem of finding (n, k) block codes such that the codewords are maximally separated in terms of their Hamming distance using autoencoders. We design an encoder and robust decoder for these block codes using DNNs. Towards this, we propose a novel training methodology for the DNN that attempts to maximize the minimum Hamming distance between codewords. We propose a loss function for this training which has stable weight updates during back propagation compared to other loss functions reported in the literature. The block codes learned using the proposed methodology are found to achieve the maximal Hamming distance separation that is known in theory. We also propose two different receiver architectures based on fully connected deep neural network (FCDNN) and bidirectional recurrent neural network (BRNN) that are suited for complex fading channels. The proposed DNN based receiver is shown to achieve significantly better error performance when compared to their classical counterparts in the presence of channel model mismatches. In the presence of model mismatches such as imperfect channel knowledge and noise correlation, the proposed DNN based transceiver is shown to offer increased reliability and robustness than the conventional transceiver.

In this paper, we consider non-orthogonal multiple access (NOMA) transmission with linear precoding techniques in downlink multiuser indoor multiple-input multiple-output (MIMO) visible light communication (VLC) systems. In particular, we propose a MIMO-NOMA transmission scheme in which the users having highly correlated channels are grouped into a single cluster and a common precoder is designed for all the users within this cluster. For the proposed scheme, we present an algorithm for grouping the users into clusters based on the correlation among their channel gains. Our performance results show that the proposed MIMO-NOMA transmission scheme achieves significantly higher spectral efficiency as compared to the conventional multiuser MIMO precoding schemes and can serve more number of users simultaneously.

Orthogonal time frequency space (OTFS) modulation is a new modulation scheme that operates in the delay-Doppler (DD) domain. In this paper, we consider the problem of delay-Doppler channel estimation in OTFS multiple access (OTFS-MA) systems on the uplink. Recognizing the inherent sparse nature of the delay-Doppler (DD) representation of time-varying channels, we model the DD channel estimation problem as a sparse signal recovery problem. To solve this problem, we employ compressed sensing (CS) based estimation techniques. Specifically, we present orthogonal matching pursuit (OMP) and modified subspace pursuit (MSP) based algorithms for DD channel estimation in uplink OTFS-MA. We compare the performance of the proposed CS-based estimation schemes with that of the impulse based channel estimation scheme reported in the OTFS literature. The proposed CS-based algorithms are shown to achieve superior normalized mean squared error and bit error performance compared to those of the impulse based channel estimation scheme.

Time-indexed media-based modulation (TI-MBM) is an index modulation scheme where time slots in a transmission frame are indexed to convey additional information bits in media-based modulation (MBM). It was shown in the literature that, in frequency selective fading channels with inter-symbol interference, TI-MBM with cyclic-prefixed single-carrier (CPSC) scheme can achieve better transmission rates, bit error performance, and multipath diversity gain compared to conventional MBM. In this paper, we analyze the capacity of TI-MBM with CPSC, which has not been reported before. We show that, for a given channel matrix, selecting the index of the activated time slots and RF mirrors according to uniform distribution is suboptimal. We derive the probabilities with which time slots and RF mirrors in TI-MBM can be activated such that the achievable transmission rate is maximized. Further, we prove that the transmit symbols from a Gaussian mixture distribution, whose mixture weights are chosen to be the product of these probabilities, can achieve capacity.

Efficient constellation design is important for improving performance in communication systems. The problem of multidimensional constellation design has been studied extensively in the literature in the context of multidimensional coded modulation and space-time coded MIMO systems. Such constellations are formally called as lattice codes, where a finite set of points from a certain high dimensional lattice is chosen based on some criteria. In this paper, we consider the problem of constellation/signal set design for media-based modulation (MBM), a recent MIMO channel modulation scheme with promising theoretical and practical benefits. Constellation design for MBM is fundamentally different from those for multidimensional coded modulation and conventional MIMO systems mainly because of the inherent sparse structure of the MBM signal vectors. Specifically, we need a structured sparse lattice code with good distance properties. In this work, we show that using an (N,K) non-binary block code in conjunction with the lattice based multilevel squaring construction, it is possible to systematically construct a signal set for MBM with certain guaranteed minimum distance. The MBM signal set obtained using the proposed construction is shown to achieve significantly improved bit error performance compared to conventional MBM signal set. In particular, the proposed signal set is found to achieve higher diversity slopes in the low-to-moderate SNR regime.

In this paper, two complex modulation schemes suited for use in multiple-input multiple-output (MIMO) visible light communication (VLC) systems are proposed and their performance investigated. The proposed schemes are quadrature spatial modulation (QSM) and dual mode index modulation (DMIM) with a dual-LED complex modulator (DCM) used as the basic building block (termed as DCM block) to transmit complex modulation symbols. The proposed schemes, referred to as QSM-DCM and DMIM-DCM schemes, do not require Hermitian symmetry operation to transmit complex modulation symbols. The proposed schemes are shown to achieve enhanced rates and good performance in indoor MIMO VLC settings. Compared to spatial modulation DCM (SM-DCM) scheme known in the recent literature, the proposed schemes achieve significantly better performance. Results show that, at a bit error rate of 10-5, performance gains up to 10.2 dB and 7.4 dB can be achieved using the proposed QSM-DCM and DMIM-DCM schemes, respectively. Also, the spatial performance investigation indicates that the proposed schemes outperform the SM-DCM scheme for most of the receiver locations across the room.

Media-based modulation (MBM) is a recently proposed modulation scheme, which conveys information using digitally controllable parasitic elements (a.k.a radio frequency mirrors) placed near the transmit antenna. In this paper, we investigate the performance of MBM in a two-way relaying network where two nodes exchange information with the help of a relay node. We consider full-duplex (FD) operation and MBM based transmission at all the nodes, and decode-and-forward protocol for relaying. We refer to the considered system as two-way FD relaying with MBM (TW-FDR-MBM) system. We introduce the TW-FDR-MBM system model and investigate its bit error performance. In particular, we carry out an average bit error probability (BEP) analysis of this system. Our performance results show that TW-FDR-MBM scheme achieves better performance compared to TW-FDR scheme that uses conventional modulation schemes like PSK/QAM.

In this paper, we consider downlink multiuser communication in indoor visible light communication (VLC) networks with multiple attocells using non-orthogonal multiple access (NOMA) transmission. We propose a joint NOMA transmission scheme, where the users in multi-cell overlapping regions are jointly served by all the corresponding VLC access points. For the proposed scheme, we consider efficient subcarrier allocation techniques, namely, area based subcarrier allocation and user based subcarrier allocation. Our performance results show that the proposed joint transmission scheme achieves significantly higher sum rates compared to the frequency reuse factor-2 (FR-2) NOMA scheme which uses independent transmission across multiple attocells. In particular, the area based subcarrier allocation scheme performs better than FR-2 NOMA for large number of users and the user based subcarrier allocation scheme performs better than FR-2 NOMA for any number of users.

In this paper, we consider a multiuser uplink scenario using orthogonal time frequency space (OTFS) modulation and propose a scheme for multiplexing users on an N × M time-frequency grid in which allocated time-frequency resource blocks for different users are non-contiguous and interleaved. The proposed scheme, termed as interleaved time-frequency multiple access (ITFMA), allows multiuser interference-free signal reception in the time-frequency domain thereby reduces the detection complexity. The proposed scheme is shown to achieve improved bit error performance compared to another recently proposed OTFS based multiple access scheme. We also consider the peakto-average power ratio (PAPR) of the proposed scheme and analytically characterize its complementary cumulative distribution function for large values of N/q, where q denotes the interleaving period in time. The use of DFT precoding is shown to improve the PAPR of the proposed scheme.

Orthogonal time frequency space (OTFS) modulation is a 2-dimensional modulation technique designed in delay-Doppler domain, specially suited for doubly- dispersive fading channels. OTFS modulation uses additional transform operations at the transmitter and receiver on top of conventional multicarrier modulation operations, and is shown to achieve superior performance compared to OFDM in high- Doppler channels. It has been shown in the recent literature that the asymptotic diversity order of OTFS modulation is one. Also, OTFS with phase rotation using transcendental numbers has been shown to achieve full diversity in the delay Doppler domain. In this paper, for the first time in the literature, we propose and investigate the use of space-time coding (STC) in OTFS modulation in a MIMO setting. We use the structure of Alamouti code, generalized to matrices, to achieve full transmit diversity in OTFS. We also show that the use of STC-OTFS along with phase rotation can achieve full diversity in both spatial and delay Doppler domains. Also, STC-OTFS black with phase rotation is found to achieve good diversity performance even with small frame sizes making it suited for low-latency applications.

Multiantenna transmission using load modulated arrays (LMAs) is gaining recent research interest. LMAs use a single central power amplifier and tune the antenna loads according to the information signal. In this paper, we propose a novel multiantenna transmitter architecture that can enable high-rate transmissions using LMAs. The proposed architecture uses channel modulation with RF mirrors in conjunction with antenna load modulation to transmit information bits. The proposed architecture has two key advantages: 1) it facilitates simple construction of high-rate signal sets suited for LMAs, and 2) it requires significantly fewer channel coefficients to be estimated at the receiver compared to conventional channel modulation architectures. The proposed architecture is shown to achieve improved bit error performance compared to conventional load modulation as well as spatial modulation, which are also single power amplifier transmission schemes. We also investigate the use of the proposed transmission scheme in a multiuser setting on the uplink. The proposed scheme not only offers the advantage of RF hardware simplicity at the user equipment but also requires fewer receive antennas at the base station to achieve a target bit error performance.

In this paper, we consider media-based modulation (MBM) in a cyclic-prefixed single-carrier setting (CPSC-MBM) in inter-symbol interference channels and focus on low-complexity signal detection at the receiver. For this, we exploit the structured sparsity that is inherently present in CPSC-MBM signals. We formulate the sparse vector detection problem of interest as an equivalent sparse matrix detection problem, whose reconstruction complexity can be significantly less without incurring much loss in recovery performance. This technique of recovering sparse matrices, termed as {\em sparse matrix sketching}, applied to CPSC-MBM signal recovery is shown to achieve good bit error performance with significant complexity gains compared to the sparse vector detection approach.

Time-indexed media-based modulation (TI-MBM) is a block transmission scheme, where a block of N time-slots forms a frame of which only K time-slots are used for data transmission (active slots) and the remaining N - K time-slots are left vacant (inactive slots). The choice of the active timeslots conveys additional information bits along with the bits conveyed by the MBM signals transmitted in the active timeslots. It has been shown that TI-MBM can achieve improved bit error performance compared to the conventional MBM scheme. However, a mathematical diversity analysis of TI-MBM has not been reported in the literature so far. In this paper, we view the time-slot indexing as coding across time (since the choice of active and inactive time-slots are dependent on each other) and carry out a mathematical analysis of the diversity performance of TIMBM. Our analytical results show that, while conventional MBM can not extract the multipath diversity of the channel, TI-MBM can achieve higher diversity orders by extracting the channel multipath diversity for suitable choice of system parameters. We provide simulation results that support the analytically predicted diversity orders.

In direct conversion radio frequency (RF) front-end architecture, RF impairments such as IQ imbalance (IQI), DC offset, flicker noise, and oscillator leakage can affect the performance. In this work, we study the performance of media-based modulation (MBM), an attractive channel modulation scheme, in the presence of transmit and receiver side IQI and propose efficient compensation techniques. MBM is shown to be more resilient to IQI compared to conventional modulation. A scheme which jointly estimates and compensates the channel and IQI parameters using widely linear least squares estimation is proposed. The proposed scheme is shown to alleviate the transmit and receive IQI-induced BER degradation in MBM.

Orthogonal time frequency space modulation (OTFS) modulation is a 2-dimensional modulation technique designed in delay-Doppler domain, suited for doubly dispersive wireless channels. OTFS modulation has been shown to achieve superior error performance compared to the conventional multi-carrier systems. In this paper, we investigate the effect of phase noise on the performance of OTFS modulation in mmWave communications, where oscillator phase noise and Doppler shifts are typically high. Towards this, we first develop a vectorized formulation of the input-output relation for OTFS modulation (with OFDM as the inner core) in the delay-Doppler domain, incorporating oscillator phase noise in the effective channel. Using a message passing based signal detection algorithm, we show that OTFS is more robust to oscillator phase noise than OFDM in high Doppler mmWave channels. At an SNR for 14 dB, OTFS achieves two to three order better BER performance compared to OFDM in the presence of oscillator phase noise in a 28 GHz system.

In visible light communication (VLC) systems, like in radio frequency (RF) wireless communication systems, the channel has to be estimated to aid transceiver operations such as data detection and precoding. The LEDs which serve as VLC transmitters have to maintain a desired average intensity as they are simultaneously used for both data transmission as well as lighting, and each LED also has a maximum power constraint. In this paper, we are concerned with channel estimation in VLC systems under these constraints. Specifically, we consider extensions to combinational codes for optimal pilot transmission assuming that the receiver employs a zero-forcing decoder. We construct optimal codes which need much fewer pilot channel uses for channel estimation compared to that needed by combinational codes. We propose a recursive algorithm to construct such codes that are short in length and meet the optimality constraints. The bit error performance achieved using the estimates of the channel obtained using the proposed codes are shown to be quite close to that with perfect channel knowledge.

Media-based modulation (MBM) is an attractive channel modulation scheme with rate, performance, and hardware advantages. In this paper, we are concerned with two important aspects of MBM. The first one is on the capacity of MBM and the other is on low-complexity detection of high-rate MBM signals using structured spare recovery techniques. We derive closed-form expression for the capacity of generalized MBM (GMBM). The main idea in the capacity analysis is to recognize that MBM uses two alphabets to convey information, namely, the source alphabet (e.g., QAM/PSK) and the channel alphabet (fade coefficients). This observation allows us to show that the capacity is achieved when the mutual information is maximized over the source-channel product alphabet. We then propose a greedy structured sparse recovery algorithm for the detection of GMBM signal vectors. The proposed algorithm is a two-stage algorithm in which support recovery is done in greedy manner first, followed by data detection in the nonzero positions. Simulation results show that the proposed algorithm achieves good performance at low complexity even when the system is highly underdetermined.

We consider generalized media-based modulation (GMBM), where transmit antennas and radio frequency (RF) mirrors (which are parasitic elements placed near the transmit antennas as digitally controlled scatterers) are indexed simultaneously to convey information bits. We develop low complexity receiver algorithms for the detection of high-rate, large-dimension GMBM signals. Message passing-based detection is a promising low-complexity approach. The elements in a GMBM transmit vector are interdependent. Message passing with a multi-layering approach is proposed to take care of this dependency. The proposed multi-layering approach decouples the dependencies through the addition of new layers and constraints that account for the antenna activation and RF mirror activation patterns. The proposed message passing detection with multi-layering, termed as multi-layered message passing detection, is shown to outperform message passing detection without multi-layering and constraints. In addition to exploiting multi-layering, the channel hardening property of large MIMO channels is exploited for GMBM signal detection and channel estimation. The algorithm based on this approach is termed as multi-layered channel hardening-exploiting message passing algorithm. The proposed algorithms scale well in complexity and achieve good bit error performance in high-rate, large-dimension GMBM systems.

Orthogonal time-frequency space (OTFS) is a two-dimensional (2D) modulation technique designed in the delay-Doppler domain. A key premise behind OTFS is the transformation of a time-varying multipath channel into an almost non-fading 2D channel in the delay-Doppler domain such that all symbols in a transmission frame experience the same channel gain. It has been suggested in the recent literature that the OTFS can extract full diversity in the delay-Doppler domain, where full diversity refers to the number of multipath components separable in either the delay or Doppler dimension, but without formal analysis. In this paper, we present a formal analysis of the diversity achieved by the OTFS modulation along with supporting simulations. Specifically, we prove that the asymptotic diversity order of the OTFS (as SNR → ∞) is one. However, in the finite SNR regime, the potential for a higher order diversity is witnessed before the diversity one regime takes over. Also, the diversity one regime is found to start at lower BER values for increased frame sizes. We also propose a phase rotation scheme for the OTFS using transcendental numbers and show that the OTFS, with this proposed scheme, extracts full diversity in the delay-Doppler domain.

Orthogonal time frequency space (OTFS) modulation is a recently introduced multiplexing technique designed in the 2-dimensional (2D) delay-Doppler domain suited for high-Doppler fading channels. OTFS converts a doubly-dispersive channel into an almost non-fading channel in the delay-Doppler domain through a series of 2D transformations. In this paper, we focus on MIMO-OTFS which brings in the high spectral and energy efficiency benefits of MIMO and the robustness of OTFS in high-Doppler fading channels. The OTFS channel-symbol coupling and the sparse delay-Doppler channel impulse response enable efficient MIMO channel estimation in high Doppler environments. We present an iterative algorithm for signal detection based on message passing and a channel estimation scheme in the delay-Doppler domain suited for MIMO-OTFS. The proposed channel estimation scheme uses impulses in the delay-Doppler domain as pilots for estimation. We also compare the performance of MIMO-OTFS with that of MIMO-OFDM under high Doppler scenarios.

Load modulated arrays (LMAs) is getting recent research attention as an attractive multiantenna transmission architecture in wireless communications. LMAs use a single power amplifier to drive the entire transmit antenna array and implement the multidimensional signaling constellation in the analog domain. In this paper, we consider LMAs in a multiuser setting on the uplink. In this setting, multiple user terminals, each using an LMA (e.g., with 2 or 4 antenna elements), communicate with a base station (BS) with multiple (tens to hundreds) receive antennas. For this system, we consider the problem of low-complexity signal detection at the BS receiver. Specifically, we propose a Markov Chain Monte Carlo (MCMC) sampling based detection algorithm. We evaluate the bit error rate performance of the algorithm via numerical simulations. Simulation results show that the proposed detection achieves very good performance, while also scaling well in complexity.

Dual-mode index modulation schemes are those where a subset of the transmitted modulation symbols are from a different constellation than the rest of the transmitted modulation symbols. The indices of the symbols from two different constellations convey information bits in addition to those conveyed by the modulation symbols. In this paper, we employ this constellation-indexing technique to develop two new modulation schemes for frequency selective fading channels using cyclic-prefixed single-carrier (CPSC). We refer to these schemes as the dual-mode time index modulation (DM-TIM) and dual-mode space-time index modulation (DM-STIM). The DM-TIM is a single transmit antenna modulation scheme and DM-STIM is a multi-antenna multiple-input multiple-output (MIMO) modulation scheme. In DM-TIM, information bits are conveyed through constellation indexing in the time domain as well as M-ary modulation symbols. In DM-STIM, in addition to the above two modes, information bits are also conveyed through antenna indexing in the spatial domain. Hence, the proposed index modulation schemes provide high data rate. We compare the proposed dual-mode index modulation schemes with state-of-art index modulation schemes and show that the proposed schemes can achieve better bit-error performance. Further, we present low-complexity message passing based algorithm for the detection of large-dimensional DM-TIM and DM-STIM signals.

In this paper, we consider generalized media- based modulation (GMBM) where transmit antennas and RF mirrors (which are parasitic elements placed near the transmit antennas as digitally controlled scatterers) are indexed simultaneously to convey information bits. GMBM systems offer the advantages of high rates, reduced transmit RF hardware complexity, and improved performance compared to conventional multi-antenna systems. This paper focuses on the detection of large- scale GMBM signals, where maximum-likelihood detection is not feasible due to its exponential complexity in the transmit rate. Message passing based detection is a promising low-complexity approach. However, message passing over a bipartite graph is not possible in GMBM signal detection because the elements of the GMBM transmit vector are interdependent. Our new contribution in this paper is that we propose a {\em multi-layered message passing (MLMP) algorithm} that decouples the %GMBM transmit vector elements dependencies through the addition of new layers and constraints that account for the antenna activation and RF mirror activation patterns. The proposed MLMP algorithm is shown to scale well in complexity and also to achieve good bit error performance in high-rate large- dimension systems.

Dual-LED complex modulation (DCM) and quad-LED complex modulation (QCM) are state-of-the-art MIMO modulation schemes which efficiently transmit complex-valued modulation symbols in visible light communication (VLC). DCM uses two LEDs to transmit complex symbols exploiting their polar form of representation. QCM uses four LEDs to transmit complex symbols through intensity modulation to convey the magnitude of real and imaginary parts of a complex symbol and spatial modulation to convey the sign information. In this paper, we introduce efficient precoding schemes for DCM and QCM schemes. The first proposed precoder is for DCM, and it is termed as optimized diagonally precoded DCM (ODP-DCM). In ODP-DCM, the magnitude and phase information are weighted such that the normalized minimum distance is maximized. The second precoder is for both DCM and QCM, and it is termed as pseudo-random phase precoded DCM/QCM (PRPP-DCM/QCM). In PRPP-DCM/QCM, pseudo-random phase matrices which do not need any channel knowledge at the transmitter for their construction are used as the precoding matrices. Numerical results show that the proposed precoding schemes achieve good performance and alleviate the effect of spatial correlation in MIMO VLC channels.

In multiple-input multiple-output (MIMO) indoor visible light communication (VLC) systems, channel gains are highly correlated. As a result, the bit error rate (BER) of the system is degraded. To improve the BER performance of the system, we propose two precoders, namely, an optimal precoder and a diagonal precoder for MIMO schemes in VLC systems with Ntlight emitting diodes (LED) and Nrphoto detectors (PD). The optimal precoder maximizes the minimum euclidean distance of the received signal set under non-negativity and maximum power constraints. The diagonal precoder, on the other hand, induces transmit power imbalance to alleviate the degradation due to channel correlation. We compare the performance of spatial multiplexing (SMP), generalized spatial modulation (GSM), and spatial modulation (SM) MIMO schemes with and without precoding. Our simulation results show that MIMO schemes with the proposed precoders outperform the MIMO schemes without precoder by up to 49 dB at 10-4BER, and that in the presence of precoding, SMP can outperform GSM and SM.

In multiple-input multiple-output (MIMO) indoor visible light communication (VLC) systems that employ non-imaging receivers, the bit error performance is degraded due to high spatial correlation. Imaging receivers can mitigate this degradation by concentrating the light energy, thereby reducing the correlation among the elements in the channel matrix. In this paper, we investigate the performance of the state-of-the-art MIMO VLC modulation schemes with convex lens-based imaging receivers. The MIMO modulation schemes considered include the well known spatial multiplexing (SMP) as well as other more recently proposed schemes such as generalized spatial modulation (GSM), quad-LED complex modulation (QCM), and dual-LED complex modulation (DCM). Performance gains up to 68 dB at $10^{-5}$ bit error rate are shown to be achieved with a convex lens based imaging receiver compared to a non-imaging receiver. We also study the spatial distribution of the best performing modulation scheme based on a minimum euclidean distance based metric. Results show that, with convex lens based imaging receiver, QCM and DCM outperform GSM and SMP.

This paper proposes two index modulation schemes for multiple-input multiple-output (MIMO) visible light communication (VLC) systems, referred to as time index modulated DCM (TIM-DCM) and space-time index modulated DCM (STIM-DCM) schemes. The proposed schemes use dual-LED complex modulator (DCM) as a basic unit (termed as DCM block) to transmit complex modulation symbols. In TIM-DCM scheme, a time slot in given frame can be used or unused, and the pattern in which the slots are used for transmission also conveys information bits (referred to as slot index bits) besides the information bits conveyed through complex modulation symbols. In STIM-DCM scheme, in addition to the slot index bits and modulation bits, spatial index bits are conveyed by activating one among the available DCM blocks in every used time slot. Hence, the proposed schemes can achieve high rates. We study the bit error rate (BER) performance of the proposed schemes and compare with that of the state-of-art modulation schemes such as spatial modulation DCM (SM-DCM) scheme. Results show that the proposed schemes can achieve better BER performance. Also, results on the spatial distribution of best performing modulation scheme indicates that the proposed schemes are favorable for different receiver locations across the room.

Load modulated arrays (LMAs) are gaining research attention as an attractive transmitter architecture for multiple-input multiple-output (MIMO) systems. A key advantage of LMAs is that they eliminate the need for RF chains at the transmitter (consisting of DACs, mixers, filters) and use only one central power amplifier for any number of antenna elements. The algorithmic complexity of the construction of high spectral efficiency load modulation (LM) signal sets for large arrays that attempts to maximize the angular separation between load impedance vectors is high. In this paper, we propose high spectral efficiency LM signal sets for large arrays. In particular, we propose random phase modulation (RPM) for LMAs, where randomly chosen phase vectors constitute the LM signal set. The LM signal sets generated using RPM are shown to achieve performance close to within a fraction of a dB compared to the performance achieved by algorithmically constructed LM signal sets, particularly when the signal set size and signal dimension are large. Further, we propose the use of random phase precoding (RPP) and precoder index modulation (PIM) in LMAs, which is shown to achieve a performance improvement of about 7-8 dB at 104bit error rate.

In this paper, we consider the problem of low-complexity detection and channel estimation in multiuser media-based modulation (MBM). MBM is an attractive modulation scheme which can achieve high data rates using multiple radio frequency (RF) mirrors (parasitic elements) and fewer transmit antennas/RF chains. A large-scale multiuser system with tens of users and a base station with tens to hundreds of receive antennas is considered. Each user employs MBM for transmission using one transmit antenna surrounded by multiple RF mirrors. We propose message passing based detection algorithms which provide very good bit error performance at low computational complexities. For the proposed message passing detection, we present a low-complexity channel estimation scheme exploiting the `channel hardening' phenomenon that occurs in large MIMO channels. We compare the performance of the proposed receiver algorithms with that of the minimum mean square error based receiver and compressive sensing based reconstruction algorithms, and show that the proposed algorithms are not only computationally less complex but also provide better performance in large-scale multiuser MBM systems.

Media-based modulation (MBM) is a promising modulation scheme which is attracting recent research attention. In MBM, radio frequency (RF) mirrors are used to create a channel modulation alphabet based on the ON/OFF (i.e., transparent/opaque) status of these mirrors. The index of the mirror activation pattern in a channel use conveys information bits in addition to the bits conveyed through conventional modulation symbols. MBM has been shown to achieve improved performance compared to conventional modulation schemes. In this paper, we introduce time-slot indexing to MBM,which further improves the performance. The proposed time-indexed MBM (TI-MBM) is a block transmission scheme, where a time slot in a given frame can be used or unused, and the choice of the slots used for transmission conveys time-index bits. We study the proposed TI-MBM scheme in frequency-selective channels and show that TI-MBM achieves better performance compared to conventional MBM. Further, recognizing that the TI-MBM signal structure promotes sparsity, we exploit the use of sparse recovery algorithms for the detection of TI-MBM signals. We show that compressive sampling matching pursuit (CoSaMP) and subspace pursuit (SP) based TI-MBM signal detection can achieve significantly improved performance compared to conventional minimum mean square (MMSE) detection.

High spatial correlation in line-of-sight multiple-input multiple-output (LOS MIMO) channels in mmWave communication is a cause for the channel matrices to have low rank. However, with proper placement of the transmit and receive antennas, the channel matrix can be made full/high rank. While optimum placements for full rank can be realized with uniform linear arrays (ULA), this may not be the case with uniform circular arrays (UCA). This motivates the need to investigate efficient signaling schemes for LOS MIMO schemes for different array configurations. Accordingly, in this work, we study various signaling schemes including spatial multiplexing (SMP), spatial modulation (SM), and generalized spatial modulation (GSM) in the context of both ULA and UCA. Our analytical and simulation results show that GSM achieves better performance compared to SMP and SM. We also propose a new signaling scheme, termed as subarray index modulation (SAIM) scheme, where groups of antennas in the array (subarrays) are indexed to convey information bits and each antenna within an activated subarray carries an independent modulation symbol. It is found that the proposed SAIM scheme can achieve better performance compared to SMP, SM, and GSM schemes.

Presence of strong line of sight (LOS) components in multiple-input multiple-output (MIMO) systems operating at mmWave frequencies result in ill-conditioned channel matrices. However, optimum inter-antenna spacing can result in orthogonal channel matrices under LOS conditions. This optimal spacing is typically large (of the order of tens of wavelengths). Antennas separated by less than optimal spacing result in degraded performance due to high spatial correlation. This motivates the need to investigate techniques that can reduce the spacing without compromising much in performance. In this work, we propose random phase precoding (RPP) as an attractive method to achieve this objective. Our contributions in this paper are two-fold. First, RPP for reducing inter-antenna spacing in mmWave communications is novel and has not been reported before. Our results show that, using RPP, the inter-antenna spacing can be reduced to the order of wavelength (5mm at 60 GHz frequency) compared to optimal spacing which is of the order of tens of wavelengths. This is achieved without the need for channel state information at the transmitter. We also present an analysis that shows that RPP reduces the effective correlation which, in turn, aids compact spacing. Second, we study an index modulation scheme where the random phase precoder matrices are indexed to convey additional information bits. The indexed RPP scheme is found to perform better than the non-indexed RPP scheme.

In this paper, we present a new multi-antenna modulation scheme, termed as space-time index modulation (STIM). In STIM, information bits are conveyed through antenna indexing in the spatial domain, slot indexing in the time domain, and M-ary modulation symbols. A time slot in a given frame can be used or unused, and the choice of the slots used for transmission conveys slot index bits. In addition, antenna index bits are conveyed in every used time slot by activating one among the available antennas. M-ary symbols are sent on the active antenna in a used time slot. We study STIM in a cyclic-prefixed single-carrier (CPSC) system in frequency-selective fading channels. It is shown that, for the same spectral efficiency and single transmit RF chain, STIM can achieve better performance compared to conventional orthogonal frequency division multiplexing (OFDM). Low-complexity iterative algorithms for the detection of large-dimensional STIM signals are also presented.

Use of multiple light emitting diodes (LED) is an attractive way to increase spectral efficiency in visible light communications (VLC). A non-DC-biased OFDM (NDC OFDM) scheme that uses two LEDs has been proposed in the literature recently. NDC OFDM has been shown to perform better than other OFDM schemes for VLC like DC-biased OFDM (DCO OFDM) and asymmetrically clipped OFDM (ACO OFDM) in multiple LEDs settings. In this paper, we propose an efficient multiple LED OFDM scheme for VLC which uses coded index modulation. The proposed scheme uses two transmitter blocks, each having a pair of LEDs. Within each block, NDC OFDM signaling is done. The selection of which block is activated in a signaling interval is decided by information bits (i.e., index bits). In order to improve the reliability of the index bits at the receiver (which is critical because of high channel correlation in multiple LEDs settings), we propose to use coding on the index bits alone. We call the proposed scheme as CI-NDC OFDM (coded index NDC OFDM) scheme. We present the performance results of CI-NDC OFDM scheme with the index bits coded by (i) LDPC and (ii) Walsh-Hadamard codes. Simulation results show that, for the same spectral efficiency, CI-NDC OFDM that uses coding on the index bits performs better than NDC OFDM.

In this paper, we investigate the detection problem in large-scale multiuser generalized spatial modulation MIMO (GSM-MIMO) systems on the uplink. The inherent sparsity present in multiuser GSM-MIMO signals enables us to view the signal detection problem as one of sparse signal recovery in underdetermined systems using compressed sensing techniques. Accordingly, we propose a FOCUSS (FOCal Underdetermined System Solver) based algorithm for GSM-MIMO signal detection. Viewing the FOCUSS based detection as a sequence of weighted 2-norm minimizations, we compare the performance of the FOCUSS based detection with that of the classical l2-norm minimizer, the MMSE detection. Simulation results show that the FOCUSS based detection beats the MMSE detection by about 10 dB at 10-3BER at a system loading factor of 1.1. This SNR gain of FOCUSS based detection over MMSE detection is found to increase with increasing system loading factors. Also, the FOCUSS based detection is shown to achieve better performance compared to OMP and CoSaMP based detection.

Precoder index modulation (PIM) is a recently proposed transmission scheme in which the index of the chosen precoder matrix from a set of predetermined pseudo-random phase precoder (PRPP) matrices will also convey information bits in addition to the information bits conveyed through conventional modulation symbols. In this paper, first we derive lower and upper bounds on the capacity of PIM. Second, since the optimum PIM detection has an exponential complexity in the precoder size, we propose a low complexity message passing based detection algorithm suited for large precoder sizes. Simulation results show that PIM with a precoder matrix of size 150 × 150 and BPSK achieves a BER of 10-5at an SNR of about 10 dB using the proposed detection algorithm in flat Rayleigh fading channels. Third, we also propose an enhanced PIM (E-PIM) scheme which provides additional signaling support to the index bits, but without loosing spectral efficiency compared to PIM. Simulation results show that the proposed E-PIM scheme achieves better performance compared to PIM.

In this paper, we propose a simple and novel complex modulation scheme for multiple-LED wireless communication, termed as quad-LED complex modulation (QCM). The proposed QCM scheme uses four LEDs (hence the name `quad-LED'), one LED each to map positive real, negative real, positive imaginary, and negative imaginary parts of complex modulation symbols like QAM symbols. The QCM scheme does not need Hermitian symmetry operation to generate LED compatible positive real transmit signals. Instead it exploits spatial indexing of LEDs to convey sign information. The proposed QCM module can serve as a basic building block to bring in the benefits of complex modulation to VLC. For example, QCM with phase rotation (QAM-PR) where the complex modulation symbols are rotated in phase before mapping the signals to the LEDs achieves improved bit error performance. We also find that the proposed QCM when used along with OFDM, termed as QCM-OFDM, achieves very good performance.

In this paper, the Gaussian many-to-one X channel (XC), which is a special case of general multiuser XC, is studied. In the Gaussian many-to-one XC, communication links exist between all transmitters and one of the receivers, along with a communication link between each transmitter and its corresponding receiver. As per the XC assumption, transmission of messages is allowed on all the links of the channel. This communication model is different from the corresponding manyto-one interference channel (IC). Transmission strategies, which involve using Gaussian codebooks and treating interference from a subset of transmitters as noise, are formulated for the above channel. Sum-rate is used as the criterion of optimality for evaluating the strategies. Initially, a 3 × 3 many-to-one XC is considered and three transmission strategies are analyzed. The first two strategies are shown to achieve sum-rate capacity under certain channel conditions. For the third strategy, a sum-rate outer bound is derived and the gap between the outer bound and the achieved rate is characterized. These results are later extended to the K × K case. Next, a region in which the many-to-one XC can be operated as a many-to-one IC without the loss of sum-rate is identified. Furthermore, in the above region, it is shown that using Gaussian codebooks and treating interference as noise achieve a rate point that is within K/2 - 1 bits from the sum-rate capacity. Subsequently, some implications of the above results to the Gaussian many-to-one IC are discussed. Transmission strategies for the many-to-one IC are formulated, and channel conditions under which the strategies achieve sum-rate capacity are obtained. A region where the sum-rate capacity can be characterized to within K/2 - 1 bits is also identified. Finally, the regions where the derived channel conditions are satisfied for each strategy are illustrated for a 3 × 3 many-to-one XC and the corresponding many-to-one IC.

In this paper, we investigate the performance of generalized spatial modulation (GSM) in indoor wireless visible light communication (VLC) systems. GSM uses $N_t$ light emitting diodes (LED), but activates only $N_a$ of them at a given time. Spatial modulation and spatial multiplexing are special cases of GSM with $N_{a}=1$ and $N_{a}=N_t$, respectively. We first derive an analytical upper bound on the bit error rate (BER) for maximum likelihood (ML) detection of GSM in VLC systems. Analysis and simulation results show that the derived upper bound is very tight at medium to high signal-to-noise ratios (SNR). The channel gains and channel correlations influence the GSM performance such that the best BER is achieved at an optimum LED spacing. Also, for a fixed transmission efficiency, the performance of GSM in VLC improves as the half-power semi-angle of the LEDs is decreased. We then compare the performance of GSM in VLC systems with those of other MIMO schemes such as spatial multiplexing (SMP), space shift keying (SSK), generalized space shift keying (GSSK), and spatial modulation (SM). Analysis and simulation results show that GSM in VLC outperforms the other considered MIMO schemes at moderate to high SNRs; for example, for 8 bits per channel use, GSM outperforms SMP and GSSK by about 21 dB, and SM by about 10 dB at $10^{-4}$ BER.

In this paper, we study the Gaussian MIMO Z channel and the Gaussian MIMO X channel. The MIMO X channel (XC) consists of two multiple antenna transmit-receive pairs, where each transmitter communicates with both receivers. The MIMO Z channel (ZC) is obtained from the MIMO X channel by eliminating one of the links and its corresponding message. First, we derive a sum-rate upper bound for the MIMO Z channel and compare it with an existing bound in literature. Next, we consider the MIMO X channel and propose a new sum-rate upper bound by utilizing the sum-rate upper bound for the MIMO ZC. Subsequently, we derive another upper bound for the MIMO XC by assuming receiver cooperation and deriving the worst noise covariance matrix for the resulting two-user MAC. We compare the above two upper bounds for the MIMO XC with the MaddahAli-Motahari-Khandani (MMK) scheme. Then, we consider some consequences of the above results for the MIMO interference channel. Finally, we present some numerical results. The numerical results suggest that the proposed sum-rate capacity upper bounds are tighter than existing bounds.

Generalized spatial modulation (GSM) uses nttransmit antenna elements but fewer transmit radio frequency (RF) chains, nrf. Spatial modulation (SM) and spatial multiplexing are special cases of GSM with nrf= 1 and nrf= nt, respectively. In GSM, in addition to conveying information bits through nrf conventional modulation symbols (for example, QAM), the indices of the nrfactive transmit antennas also convey information bits. In this paper, we investigate GSM for large-scale multiuser MIMO communications on the uplink. Our contributions in this paper include: 1) an average bit error probability (ABEP) analysis for maximum-likelihood detection in multiuser GSM-MIMO on the uplink, where we derive an upper bound on the ABEP, and 2) low-complexity algorithms for GSM-MIMO signal detection and channel estimation at the base station receiver based on message passing. The analytical upper bounds on the ABEP are found to be tight at moderate to high signal-to-noise ratios (SNR). The proposed receiver algorithms are found to scale very well in complexity while achieving near-optimal performance in large dimensions. Simulation results show that, for the same spectral efficiency, multiuser GSM-MIMO can outperform multiuser SM-MIMO as well as conventional multiuser MIMO, by about 2 to 9 dB at a bit error rate of 10-3. Such SNR gains in GSM-MIMO compared to SM-MIMO and conventional MIMO can be attributed to the fact that, because of a larger number of spatial index bits, GSM-MIMO can use a lower-order QAM alphabet which is more power efficient.

Spatial modulation (SM) is a transmission scheme that uses multiple transmit antennas but only one transmit RF chain. At each time instant, only one among the transmit antennas will be active and the others remain silent. The index of the active transmit antenna will also convey information bits in addition to the information bits conveyed through modulation symbols. Pseudo-random phase precoding (PRPP) is a technique that can achieve high diversity orders even in single antenna systems without the need for channel state information at the transmitter and transmit power control. In this paper, we exploit the advantages of both SM and PRPP simultaneously. We propose a pseudo-random phase precoded SM (PRPP-SM) scheme, where both the modulation bits and the antenna index bits are precoded by pseudo-random phases. The proposed PRPP-SM system gives significant performance gains over SM system without PRPP and PRPP system without SM. Since maximum likelihood (ML) detection becomes exponentially complex in large dimensions, we propose a low complexity local search based detection (LSD) algorithm suited for PRPP-SM systems with large precoder sizes. Our simulation results show that with 4 transmit antennas, 1 receive antenna, 5 × 20 pseudo-random phase precoder matrix and BPSK modulation, the performance of PRPP-SM using ML detection is better than SM without PRPP with ML detection by about 9 dB at 102BER. This performance advantage gets even better for large precoding sizes. We also propose a precoder index modulation (PIM) scheme, which conveys additional information bits through the choice of a precoding matrix among a set of pre-determined PRPP matrices. Finally, combining the PIM and PRPP-SM schemes, we propose a PIM-SM scheme which conveys bits through both antenna index as well as precoder index.

In this paper, we consider transmitter optimization in multiple-input single-output (MISO) broadcast channel with common and secret messages. The secret message is intended for K users and it is transmitted with perfect secrecy with respect to J eavesdroppers which are also assumed to be legitimate users in the network. The common message is transmitted at a fixed rate Äo and it is intended for all K users and J eavesdroppers. The source operates under a total power constraint. It also injects artificial noise to improve the secrecy rate. We obtain the optimum covariance matrices associated with the common message, secret message, and artificial noise, which maximize the achievable secrecy rate and simultaneously meet the fixed rate Äo for the common message.

We study the Gaussian many-to-one interference network which is a special case of general interference network, where only one receiver experiences interference. We allow transmission of messages on all the links of the network. This communication model is different from the corresponding many-to-one interference channel. We formulate three transmission strategies for the above network, which involve using Gaussian codebooks and treating interference from a subset of the transmitters as noise. We use sum-rate as the criterion of optimality for evaluating the strategies. For the first two strategies, we characterize the sum-rate capacity under certain channel conditions, while for the other strategy, we derive a sum-rate outer bound and characterize the gap between the outer bound and the achievable sum-rate of the strategy. Finally, we illustrate the regions where the derived channel conditions are satisfied for each strategy.

In this paper, we propose a non-binary belief propagation approach (NB-BP) for detection of M-ary modulation symbols and decoding of q-ary LDPC codes in large-scale multiuser MIMO systems. We first propose a message passing based symbol detection algorithm which computes vector messages using a scalar Gaussian approximation of interference, which results in a total complexity of just O(KN √M), where K is the number of uplink users and N is the number of base station (BS) antennas. We then design optimized q-ary LDPC codes by matching the EXIT charts of the proposed detector and the LDPC decoder. Simulation results show that the proposed NB-BP detection-decoding approach using the optimized LDPC codes achieve significantly better performance (by about 1 dB to 7 dB at 10-5coded BER for various system loading factors with number of users ranging from 16 to 128 and number of BS antennas fixed at 128) compared to using linear detectors and off-the-shelf q-ary irregular LDPC codes.

In this paper, we propose algorithms for signal detection in large-scale multiuser {\em spatial modulation multiple-input multiple-output (SM-MIMO)} systems. In large-scale SM-MIMO, each user is equipped with multiple transmit antennas (e.g., 2 or 4 antennas) but only one transmit RF chain, and the base station (BS) is equipped with tens to hundreds of (e.g., 128) receive antennas. In SM-MIMO, in a given channel use, each user activates any one of its multiple transmit antennas and the index of the activated antenna conveys information bits in addition to the information bits conveyed through conventional modulation symbols (e.g., QAM). We propose two different algorithms for detection of large-scale SM-MIMO signals at the BS; one is based on {\em message passing} and the other is based on {\em local search}. The proposed algorithms are shown to achieve very good performance and scale well. Also, for the same spectral efficiency, multiuser SM-MIMO outperforms conventional multiuser MIMO (recently being referred to as massive MIMO) by several dBs; for e.g., with 16 users, 128 antennas at the BS and 4 bpcu per user, SM-MIMO with 4 transmit antennas per user and 4-QAM outperforms massive MIMO with 1 transmit antenna per user and 16-QAM by about 4 to 5 dB at 10-3uncoded BER. This SNR advantage essentially comes about because the spatial index bits allow SM-MIMO to achieve a given spectral efficiency using a lower order modulation alphabet than in conventional multiuser MIMO.

In this paper, we propose a multiple-input multiple-output (MIMO) receiver algorithm that exploits channel hardening that occurs in large MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of the HHH matrix become increasingly weaker compared to the diagonal terms as the size of the channel gain matrix H increases. Specifically, we propose a message passing detection (MPD) algorithm which works with the real-valued matched filtered received vector (whose signal term becomes HTHx, where x is the transmitted vector), and uses a Gaussian approximation on the off-diagonal terms of the HTH matrix. We also propose a simple estimation scheme which directly obtains an estimate of HTH (instead of an estimate of H), which is used as an effective channel estimate in the MPD algorithm. We refer to this receiver as the channel hardening-exploiting message passing (CHEMP) receiver. The proposed CHEMP receiver achieves very good performance in large-scale MIMO systems (e.g., in systems with 16 to 128 uplink users and 128 base station antennas). For the considered large MIMO settings, the complexity of the proposed MPD algorithm is almost the same as or less than that of the minimum mean square error (MMSE) detection. This is because the MPD algorithm does not need a matrix inversion. It also achieves a significantly better performance compared to MMSE and other message passing detection algorithms using MMSE estimate of H.

We study the Gaussian one-to-many interference network which is obtained as a special case of a general interference network, where only one transmitter generates interference in the network. We allow transmission of messages on all the links of the network. This communication model is different from the corresponding one-to-many interference channel. We formulate two transmission strategies for the above network, which involve using Gaussian codebooks and treating interference as noise at a subset of the receivers. We use sum-rate as the criterion of optimality for evaluating the strategies. For the first strategy, we characterize the sum-rate capacity under certain channel conditions, while for the second strategy, we derive a sum-rate outer bound and characterize the gap between the outer bound and the achievable sum-rate of the strategy. Next, we show that the solution approach for the second strategy has applications to the cascade Gaussian Z network, a network consisting of parallel point-to-point links, where each transmitter except the last has a communication link to the adjacent receiver. Lastly, we illustrate the regions corresponding to the derived channel conditions for each strategy.

In this paper, we consider space-shift keying (SSK) in dual-hop decode-and-forward (DF) cooperative multicast networks, where a source node communicates with multiple destination nodes with the help of relay nodes. We consider a topology consisting of a single source, two relays, and multiple destinations. For such a system, we propose a scheme to select a single relay among the two when SSK is used for transmission on each of the links in the cooperative system. We analyze the end-to-end average bit error probability (ABEP) of this system. For binary SSK, we derive an exact expression for the ABEP in closed-form. Analytical results exactly match the simulation results validating the analysis. For non-binary SSK, we derive an approximate ABEP expression, where the analytical ABEP results closely follow simulation results. We also derive the diversity order of the system through asymptotic ABEP analysis.

In this paper, we study beamforming techniques for secrecy with worst case signal-to-interference-plus-noise ratio (SINR) guarantees in cooperative communications with imperfect channel state information (CSI). The worst case SINRs are the minimum SINR at the intended destination and the maximum SINR at the eavesdroppers. We consider a norm bounded CSI error model. With the available imperfect channel estimates, we design beamformers such that the minimum SINR receivable by the intended destination is above a certain threshold, while the maximum value of SINRs receivable at the eavesdroppers are below another lower threshold. We consider amplify-and-forward (AF) and decode-and-forward (DF) relaying schemes. The relays do the worst case transmit beamforming and injection of artificial noise (AN). We jointly optimize the beamformers and the AN for the AF and DF schemes subject to the worst case SINR constraints at the destination and the eavesdroppers. We solve the corresponding optimization problems as semi-definite programming (SDP) problems by rank relaxation and S-procedure. Numerical results show that AN injection at the relays significantly reduces the average total transmit power required to meet the worst case SINR constraints, and improves the solution feasibility of the optimization problems.

In this paper, we compute worst case secrecy rates in amplify-and-forward (AF) relay beamforming with cooperative jamming (CJ) in the presence of imperfect channel state information (CSI). A source-destination pair aided by M relays is considered. Number of eavesdroppers J can be more than the number of relays. Out of the M relays, k1relays (1 ≤ k1≤ M) act as data relays and the remaining k2= M - k1relays act as jamming relays. Data relays aid the communication by relaying data in AF mode, and jamming relays cooperate by transmitting jamming signals (artificial noise). The jamming signals are created such that they degrade the eavesdroppers' channels but do not significantly affect the intended receiver's channel, thereby improving secrecy rate. Imperfection in the CSI is modeled using a norm-bounded error model. We solve for the optimum (k1, k2) and the weights of data relays and jamming relays that maximize the secrecy rate subject to a total relay power constraint. We relax the rank-one constraint on the complex semi-definite data relays and jamming relays weight matrices and reformulate the optimization problem into a form that can be solved using convex semi-definite programming. Numerical results on the secrecy rate that illustrate the effect of cooperative jamming, imperfect CSI, and number of eavesdroppers are presented.

The problem of searching the closest lattice point in large dimensional lattices finds many applications in single and/or multiple antenna communications. In this paper, we propose a Gaussian sampling based lattice decoding algorithm (GSLD). The algorithm iteratively updates each coordinate by sampling from a continuous Gaussian distribution and then quantizes the sampled value to the nearest alphabet point. The algorithm complexity per iteration is independent of the size of the alphabet, and hence is of high interest in higher order modulation schemes. We show that the algorithm is able to achieve near-optimal performance in polynomial complexity in different wireless communication system models.

MIMO systems with several antennas at the transmitter and receiver have the potential to enable high throughputs. One of the challenges in realizing this potential is the design of receivers that scale in terms of computation and performance. Towards this end, in this paper, we propose a receiver that uses a committee of linear receivers, whose parameters are estimated from training data using a variant of the AdaBoost algorithm, a celebrated supervised classification algorithm in machine learning. We call our receiver boosted MMSE (B-MMSE) receiver and we study its performance via simulations. The channel matrix is estimated from the pilot using the MMSE technique. We find that for a 4 × 4 system with a Rayleigh fading channel, using BPSK at a bit error rate (BER) of 10-2, our receiver using the estimated channel matrix needs 2 dB less power than the plain MMSE receiver based on the estimated channel matrix. On an average, excluding the training phase, the receiver complexity equals 1.25 linear receivers. Thus the BMMSE receiver is slightly more complex than the MMSE receiver and substantially less complex than the maximum-likelihood receiver. We also show that the coded BER performance with an outer rate-3/4 Turbo-code has a gain of 5 dB at 10-4coded BER when the demodulated output from the proposed method is used in place of plain MMSE detection with MMSE estimated channel.

Multiple input multiple output (MIMO) systems with large number of antennas have been gaining wide attention as they enable very high throughputs. A major impediment is the complexity at the receiver needed to detect the transmitted data. To this end we propose a new receiver, called LRR (Linear Regression of MMSE Residual), which improves the MMSE receiver by learning a linear regression model for the error of the MMSE receiver. The LRR receiver uses pilot data to estimate the channel, and then uses locally generated training data (not transmitted over the channel), to find the linear regression parameters. The proposed receiver is suitable for applications where the channel remains constant for a long period (slowfading channels) and performs quite well: at a bit error rate (BER) of 10-3, the SNR gain over MMSE receiver is about 7 dB for a 16 × 16 system; for a 64 × 64 system the gain is about 8.5 dB. For large coherence time, the complexity order of the LRR receiver is the same as that of the MMSE receiver, and in simulations we find that it needs about 4 times as many floating point operations. We also show that further gain of about 4 dB is obtained by local search around the estimate given by the LRR receiver.

Space shift keying (SSK) is an attractive modulation technique for multi-antenna communications. In SSK, only one among the available transmit antennas is activated during one channel use, and the index of the chosen transmit antenna conveys information. In this paper, we analyze the performance of SSK in multi-hop, multi-branch cooperative relaying systems. We consider the decode-and-forward relaying protocol, where a relay forwards the decoded symbol if it decodes the symbol correctly from the received signal. We derive closed-form expressions for the end-to-end bit error rate of SSK in this system. Analytical and simulation results match very well.

Generalized spatial modulation (GSM) is a relatively new modulation scheme for multi-antenna wireless communications. It is quite attractive because of its ability to work with less number of transmit RF chains compared to traditional spatial multiplexing (V-BLAST system). In this paper, we show that, by using an optimum combination of number of transmit antennas (Nt) and number of transmit RF chains (Nrf), GSM can achieve better throughput and/or bit error rate (BER) than spatial multiplexing. First, we quantify the percentage savings in the number of transmit RF chains as well as the percentage increase in the rate achieved in GSM compared to spatial multiplexing; 18.75% savings in number of RF chains and 9.375% increase in rate are possible with 16 transmit antennas and 4-QAM modulation. A bottleneck, however, is the complexity of maximum-likelihood (ML) detection of GSM signals, particularly in large MIMO systems where the number of antennas is large. We address this detection complexity issue next. Specifically, we propose a Gibbs sampling based algorithm suited to detect GSM signals. The proposed algorithm yields impressive BER performance and complexity results. For the same spectral efficiency and number of transmit RF chains, GSM with the proposed detection algorithm achieves better performance than spatial multiplexing with ML detection.

Space shift keying (SSK) is a special case of spatial modulation (SM), which is a relatively new modulation technique that is getting recognized to be attractive in multi-antenna communications. Our new contribution in this paper is an analytical derivation of exact closed-form expression for the end-to-end bit error rate (BER) performance of SSK in decode-and-forward (DF) cooperative relaying. An incremental relaying (IR) scheme with selection combining (SC) at the destination is considered. In SSK, since the information is carried by the transmit antenna index, traditional selection combining methods based on instantaneous SNRs can not be directly used. To overcome this problem, we propose to do selection between direct and relayed paths based on the Euclidean distance between columns of the channel matrix. With this selection metric, an exact analytical expression for the end-to-end BER is derived in closed-form. Analytical results are shown to match with simulation results.

In multiuser communication on the uplink, all subscribed users may not be active simultaneously. This leads to sparsity in the activity pattern in the users' transmissions, which can be exploited in the multiuser MIMO receiver at the base station (BS). Because of no transmissions from inactive users, joint detection at the BS has to consider an augmented signal set that includes zero. In this paper, we propose a receiver that exploits this inactivity-induced sparsity and considers the zero-augmented signal set. The proposed receiver is based on Markov Chain Monte Carlo techniques. Near-optimal performance and increased system capacity (in terms of number of users in the system) are demonstrated. For example, a multiuser MIMO system with N = 32 receive antennas at the BS and an user activity factor of 0.2 supports 51 uplink users meeting a QoS of 10-3coded bit error rate.

Spatial modulation (SM) and space shift keying (SSK) are relatively new modulation techniques which are attractive in multi-antenna communications. Single carrier (SC) systems can avoid the peak-to-average power ratio (PAPR) problem encountered in multicarrier systems. In this paper, we study SM and SSK signaling in cyclic-prefixed SC (CPSC) systems on MIMO-ISI channels. We present a diversity analysis of MIMO-CPSC systems under SSK and SM signaling. Our analysis shows that the diversity order achieved by (nt, nr) SSK scheme and (nt, nr, ΘM) SM scheme in MIMO-CPSC systems under maximum-likelihood (ML) detection is nr, where nt, nrdenote the number of transmit and receive antennas and ΘMdenotes the modulation alphabet of size M. Bit error rate (BER) simulation results validate this predicted diversity order. Simulation results also show that MIMO-CPSC with SM and SSK achieves much better performance than MIMO-OFDM with SM and SSK.

In this paper, we consider low-complexity turbo equalization for multiple-input multiple-output (MIMO) cyclic prefixed single carrier (CPSC) systems in MIMO inter-symbol interference (ISI) channels characterized by large delay spreads. A low-complexity graph based equalization is carried out in the frequency domain. Because of the reduction in correlation among the noise samples that happens for large frame sizes and delay spreads in frequency domain processing, improved performance compared to time domain processing is shown to be achieved. This improved performance is attractive for equalization in severely delay spread ISI channels like ultrawideband channels and underwater acoustic channels.

In this paper, we employ message passing algorithms over graphical models to jointly detect and decode symbols transmitted over large multiple-input multiple-output (MIMO) channels with low density parity check (LDPC) coded bits. We adopt a factor graph based technique to integrate the detection and decoding operations. A Gaussian approximation of spatial interference is used for detection. This serves as a low complexity joint detection/decoding approach for large dimensional MIMO systems coded with LDPC codes of large block lengths. This joint processing achieves significantly better performance than the individual detection and decoding scheme.

In this paper, we propose a cooperative particle swarm optimization (CPSO) based channel estimation/equalization scheme for multiple-input multiple-output zero-padded single-carrier (MIMO-ZPSC) systems with large dimensions in frequency selective channels. We estimate the channel state information at the receiver in time domain using a PSO based algorithm during training phase. Using the estimated channel, we perform information symbol detection in the frequency domain using FFT based processing. For this detection, we use a low complexity OLA (OverLap Add) likelihood ascent search equalizer which uses minimum mean square (MMSE) equalizer solution as the initial solution. Multiple iterations between channel estimation and data detection are carried out which significantly improves the mean square error and bit error rate performance of the receiver.

In this paper, we address the design of codes which achieve modulation diversity in block fading single-input single-output (SISO) channels with signal quantization at the receiver. With an unquantized receiver, coding based on algebraic rotations is known to achieve maximum modulation coding diversity. On the other hand, with a quantized receiver, algebraic rotations may not guarantee gains in diversity. Through analysis, we propose specific rotations which result in the codewords having equidistant component-wise projections. We show that the proposed coding scheme achieves maximum modulation diversity with a low-complexity minimum distance decoder and perfect channel knowledge. Relaxing the perfect channel knowledge assumption we propose a novel channel training/estimation technique to estimate the channel. We show that our coding/training/estimation scheme and minimum distance decoding achieves an error probability performance similar to that achieved with perfect channel knowledge.

In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly sparse signals from noisy measurements can be viewed as a problem of recovery of approximately sparse signals from noiseless measurements, making the approach applicable to strictly sparse signal recovery from noisy measurements. The support recovery embedded in the approach makes it suitable for recovery of signals with same sparsity profiles, as in the problem of multiple measurement vectors (MMV). Simulation results show that the proposed algorithm, termed as JSSR-MP (joint support and signal recovery via message passing) algorithm, achieves performance comparable to that of sparse Bayesian learning (M-SBL) algorithm in the literature, at one order less complexity compared to the M-SBL algorithm.

In this paper, we investigate the achievable rate region of Gaussian multiple access channels (MAC) with finite input alphabet and quantized output. With finite input alphabet and an unquantized receiver, the two-user Gaussian MAC rate region was studied. In most high throughput communication systems based on digital signal processing, the analog received signal is quantized using a low precision quantizer. In this paper, we first derive the expressions for the achievable rate region of a two-user Gaussian MAC with finite input alphabet and quantized output. We show that, with finite input alphabet, the achievable rate region with the commonly used uniform receiver quantizer has a significant loss in the rate region compared. It is observed that this degradation is due to the fact that the received analog signal is densely distributed around the origin, and is therefore not efficiently quantized with a uniform quantizer which has equally spaced quantization intervals. It is also observed that the density of the received analog signal around the origin increases with increasing number of users. Hence, the loss in the achievable rate region due to uniform receiver quantization is expected to increase with increasing number of users. We, therefore, propose a novel non-uniform quantizer with finely spaced quantization intervals near the origin. For a two-user Gaussian MAC with a given finite input alphabet and low precision receiver quantization, we show that the proposed non-uniform quantizer has a significantly larger rate region compared to what is achieved with a uniform quantizer.

Low-complexity near-optimal detection of signals in MIMO systems with large number (tens) of antennas is getting increased attention. In this paper, first, we propose a variant of Markov chain Monte Carlo (MCMC) algorithm which i) alleviates the stalling problem encountered in conventional MCMC algorithm at high SNRs, and ii) achieves near-optimal performance for large number of antennas (e.g., 16×16, 32×32, 64×64 MIMO) with 4-QAM. We call this proposed algorithm as randomized MCMC (R-MCMC) algorithm. Second, we propose an other algorithm based on a random selection approach to choose candidate vectors to be tested in a local neighborhood search. This algorithm, which we call as randomized search (RS) algorithm, also achieves near-optimal performance for large number of antennas with 4-QAM. The complexities of the proposed R-MCMC and RS algorithms are quadratic/sub-quadratic in number of transmit antennas, which are attractive for detection in large-MIMO systems. We also propose message passing aided R-MCMC and RS algorithms, which are shown to perform well for higher-order QAM.

We consider precoding strategies at the secondary base station (SBS) in a cognitive radio network with interference constraints at the primary users (PUs). Precoding strategies at the SBS which satisfy interference constraints at the PUs in cognitive radio networks have not been adequately addressed in the literature so far. In this paper, we consider two scenarios: i) when the primary base station (PBS) data is not available at SBS, and ii) when the PBS data is made available at the SBS. We derive the optimum MMSE and Tomlinson-Harashima precoding (THP) matrix Alters at the SBS which satisfy the interference constraints at the PUs for the former case. For the latter case, we propose a precoding scheme at the SBS which performs pre-cancellation of the PBS data, followed by THP on the pre-cancelled data. The optimum precoding matrix filters are computed through an iterative search. To illustrate the robustness of the proposed approach against imperfect CSI at the SBS, we then derive robust precoding filters under imperfect CSI for the latter case. Simulation results show that the proposed optimum precoders achieve good bit error performance at the secondary users while meeting the interference constraints at the PUs.

In this paper, we address the design of codes which achieve modulation diversity in block fading single-input single-output (SISO) channels with signal quantization at receiver and low-complexity decoding. With an unquantized receiver, coding based on algebraic rotations is known to achieve modulation coding diversity. On the other hand, with a quantized receiver, algebraic rotations may not guarantee diversity. Through analysis, we propose specific rotations which result in the codewords having equidistant component-wise projections. We show that the proposed coding scheme achieves maximum modulation diversity with a low-complexity minimum distance decoder.

In this paper, we focus on increasing the throughput and diversity of network coded MIMO transmissions in bidirectional multi-pair wireless relay networks. All nodes have multi-antenna capability. Pairs of nodes want to exchange messages via a relay having multi-antenna and encoding/decoding capability. Nodes transmit their messages to the relay in the first (MAC) phase. The relay decodes all the messages and XORs them and broadcasts the XORed message in the second (BC) phase. We develop a generalized framework for bidirectional multi-pair multi-antenna wireless network coding, which models different MIMO transmission schemes including spatial multiplexing (V-BLAST), orthogonal STBC (OSTBC), and non-orthogonal STBC (NO-STBC) in a unified way. Enhanced throughputs are achieved by allowing all nodes to simultaneously transmit at their full rate. High diversity orders are achieved through the use of NO-STBCs, characterized by full rate and full transmit diversity. We evaluate and compare the performance of VBLAST, OSTBC, and NO-STBC schemes in one-dimensional 1-pair linear network (one pair of nodes and a relay) and two-dimensional 2-pair `cross' network (two pairs of nodes and a relay).

In this paper, we consider a slow-fading nt×nrmultiple-input multiple-output (MIMO) channel subjected to block fading. Reliability (in terms of achieved diversity order) and rate (in number of symbols transmitted per channel use) are of interest in such channels. We propose a new precoding scheme which achieves both full diversity (nt×nrth order diversity) as well as full rate (ntsymbols per channel use) using partial channel state information at the transmitter (CSIT). The proposed scheme achieves full diversity and improved coding gain through an optimization over the choice of constellation sets. The optimization maximizes dmin2for our precoding scheme subject to an energy constraint. The scheme requires feedback of nt- 1 angle parameter values, compared to 2ntnrreal coefficients in case of full CSIT. Further, for the case of nt× 1 system, we prove that the capacity achieved by the proposed scheme is same as that achieved with full CSIT. Error rate performance results for nt= 3,4,8 show that the proposed scheme performs better than other precoding schemes in the literature; the better performance is due to the choice of the signal sets and the feedback angles in the proposed scheme.

In this letter, we are concerned with low-complexity detection in large multiple-input multiple-output (MIMO) systems with tens of transmit/receive antennas. Our new contributions in this letter are two-fold. First, we propose a low-complexity algorithm for large-MIMO detection based on a layered low-complexity local neighborhood search. Second, we obtain a lower bound on the maximum-likelihood (ML) bit error performance using the local neighborhood search. The advantages of the proposed ML lower bound are i) it is easily obtained for MIMO systems with large number of antennas because of the inherent low complexity of the search algorithm, ii) it is tight at moderate-to-high SNRs, and iii) it can be tightened at low SNRs by increasing the number of symbols in the neighborhood definition. The proposed detection algorithm based on the layered local neighborhood search achieves bit error performances which are quite close to this lower bound for large number of antennas and higher-order QAM.

Abstract—We consider a slow fading multiple-input multiple-output (MIMO) system with channel state information at both the transmitter and receiver. A well-known precoding scheme is based upon the singular value decomposition (SVD) of the channel matrix, which transforms the MIMO channel into parallel subchannels. Despite having low maximum likelihood decoding (MLD) complexity, this SVD precoding scheme provides a diversity gain which is limited by the diversity gain of the weakest subchannel. We therefore propose X- and Y-Codes, which improve the diversity gain of the SVD precoding scheme but maintain the low MLD complexity, by jointly coding information across a pair of subchannels. In particular, subchannels with high diversity gain are paired with those having low diversity gain. A pair of subchannels is jointly encoded using a 2 2 real matrix, which is fixed a priori and does not change with each channel realization. For X-Codes, these rotation matrices are parameterized by a single angle, while for Y-Codes, these matrices are left triangular matrices. Moreover, we propose X-, Y-Precoders with the same structure as X-, Y-Codes, but with encoding matrices adapted to each channel realization. We observed that X-Codes/Precoders are good for well-conditioned channels, while Y-Codes/Precoders are good for ill-conditioned channels. Index Terms—Condition number, diversity, error probability, MIMO, precoding, singular value decomposition. I.

We consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a non diagonal precoder based on the X-Codes in to increase the mutual information. The MIMO channel is transformed into a set of parallel subchannels using singular value decomposition (SVD) and X-Codes are then used to pair the subchannels. X-Codes are fully characterized by the pairings and a 2 × 2 real rotation matrix for each pair (parameterized with a single angle). This precoding structure enables us to express the total mutual information as a sum of the mutual information of all the pairs. The problem of finding the optimal precoder with the above structure, which maximizes the total mutual information, is solved by: i) optimizing the rotation angle and the power allocation within each pair and ii) finding the optimal pairing and power allocation among the pairs. It is shown that the mutual information achieved with the proposed pairing scheme is very close to that achieved with the optimal pre coder by Cruz et al., and is significantly better than Mercury/waterfllling strategy by Lozano et al. Our approach greatly simplifies both the precoder optimization and the detection complexity, making it suitable for practical applications.

In this paper, we are concerned with low-complexity detection in large multiple-input multiple-output (MIMO) systems with tens of transmit/receive antennas. Our new contributions in this paper are two-fold. First, we propose a low-complexity algorithm for large-MIMO detection based on a layered low-complexity local neighborhood search. Second, we obtain a lower bound on the maximum-likelihood (ML) bit error performance using the local neighborhood search. The advantages of the proposed ML lower bound are i) it is easily obtained for MIMO systems with large number of antennas because of the inherent low complexity of the search algorithm, ii) it is tight at moderate-to-high SNRs, and iii) it can be tightened at low SNRs by increasing the number of symbols in the neighborhood definition. Interestingly, the proposed detection algorithm based on the layered local search achieves bit error performances which are quite close to this lower bound/or large number of antennas and higher-order QAM. For e.g., in a 32 × 32 V-BLAST MIMO system, the proposed detection algorithm performs close to within 1.7 dB of the proposed ML lower bound at 10-3BER for 16-QAM (128 bps/Hz), and close to within 4.5 dB of the bound for 64-QAM (192 bps/Hz).

We consider a time division duplex multiple-input multiple-output (nt× nrMIMO). Using channel state information (CSI) at the transmitter, singular value decomposition (SVD) of the channel matrix is performed. This transforms the MIMO channel into parallel subchannels, but has a low overall diversity order. Hence, we propose X-Codes which achieve a higher diversity order by pairing the subchannels, prior to SVD preceding. In particular, each pair of information symbols is encoded by a fixed 2 × 2 real rotation matrix. X-Codes can be decoded using nrvery low complexity two-dimensional real sphere decoders. Error probability analysis for X-Codes enables us to choose the optimal pairing and the optimal rotation angle for each pair. Finally, we show that our new scheme outperforms other low complexity precoding schemes.

In uplink orthogonal frequency division multiple access (OFDMA), carrier frequency offsets (CFO) and/or timing offsets (TO) of other users with respect to a desired user can cause significant multiuser interference (MUI). In this paper, we derive an analytical bit error rate (BER) expression that quantify the degradation in BER due to the combined effect of both CFOs and TOs in uplink OFDMA on Rician fading channels. Such an analytical BER derivation for uplink OFDMA with CFOs and TOs on Rician fading channels has not been reported so far. For the case of non-zero CFOs/TOs, we obtain an approximate BER expression involving a single integral. Analytical and simulation BER results are shown to match very well.

In this paper, we present a belief propagation (BP) based equalizer for ultrawideband (UWB) multiple-input multiple-output (MIMO) inter-symbol interference (ISI) channels characterized by severe delay spreads. We employ a Markov random field (MRF) graphical model of the system on which we carry out message passing. The proposed BP equalizer is shown to perform increasingly closer to optimal performance for increasing number of multipath components (MPC) at a much lesser complexity than that of the optimum equalizer. The proposed equalizer performs close to within 0.25 dB of SISO AWGN performance at 10-3bit error rate on a severely delay-spread MIMO-ISI channel with 20 equal-energy MPCs. We point out that, although MIMO/UWB systems are characterized by fully/densely connected graphical models, the following two proposed features are instrumental in achieving near-optimal performance for large number of MPCs at low complexities: i) use of pairwise compatibility functions in densely connected MRFs, and ii) use of damping of messages.

In this paper, we shed light on the cross-layer interactions between the PHY, link and routing layers in networks with MIMO links operating in the diversity mode. Many previous studies assume an overly simplistic PHY layer model that does not sufficiently capture these interactions. We show that the use of simplistic models can in fact lead to misleading conclusions with regards to the higher layer performance with MIMO diversity. Towards understanding the impact of various PHY layer features on MIMO diversity, we begin with a simple but widely-used model and progressively incorporate these features to create new models. We examine the goodness of these models by comparing the simulated performance results with each, with measurements on an indoor 802.11 n testbed. Our work reveals several interesting cross-layer dependencies that affect the gains due to MIMO diversity. In particular, we observe that relative to SISO links: (a) PHY layer gains due to MIMO diversity do not always carry over to the higher layers, (b) the use of other PHY layer features such as FEC codes significantly influence the gains due to MIMO diversity, and (c) the choice of the routing metric can impact the gains possible with MIMO.

We consider a time division duplex (TDD) nt× nrmultiple-input multiple-output (MIMO) system with known channel state information (CSI) at both transmitter and receiver. Using singular value decomposition (SVD) precoding at the transmitter, the MIMO channels are transformed into parallel subchannels. To improve the low diversity order, we propose X- and Y-Codes, prior to SVD precoding, to pair subchannels having different diversity orders. Specifically, a pair of channels is jointly encoded using a 2 × 2 real matrix, which is fixed a priori and does not change with each channel realization. Moreover, we propose X-, Y-Precoders with the same encoding matrices as X-, Y-Codes, which adapt to each channel realization. The optimal encoding matrices for X- and Y-Codes/Precoders are derived analytically to minimize the average error probability. Finally, we see that X-, Y-Codes/Precoders indeed achieve higher diversity gains at very low encoding/decoding complexity for both well- and ill-conditioned channels, respectively, when compared to other precoding schemes in the literature. We also observe that for the Rayleigh fading channel model X- and Y-Codes/Precoders exhibit the best average error performance.

We consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a non-diagonal precoder based on X-Codes in to increase the mutual information. The MIMO channel is transformed into a set of parallel subchannels using Singular Value Decomposition (SVD) and X-codes are then used to pair the subchannels. X-Codes are fully characterized by the pairings and the 2 × 2 real rotation matrices for each pair (parameterized with a single angle). This precoding structure enables to express the total mutual information as a sum of the mutual information of all the pairs. The problem of finding the optimal precoder with the above structure, which maximizes the total mutual information, is equivalent to i) optimizing the rotation angle and the power allocation within each pair and ii) finding the optimal pairing and power allocation among the pairs. It is shown that the mutual information achieved with the proposed pairing scheme is very close to that achieved with the optimal precoder by Cruz et al., and significantly better than mercury/waterfilling strategy by Lozano et al.. Our approach greatly simplifies both the precoder optimization and the detection complexity, making it suitable for practical applications.

In this paper, we consider a robust design of MIMO-relay precoder and receive filter for the destination nodes in a non-regenerative multiple-input multiple-output (MIMO) relay network. The network consists of multiple source-destination node pairs assisted by a single MIMO-relay node. The source and destination nodes are single antenna nodes, whereas the MIMO-relay node has multiple transmit and multiple receive antennas. The channel state information (CSI) available at the MIMO-relay node for precoding purpose is assumed to be imperfect. We assume that the norms of errors in CSI are upper-bounded, and the MIMO-relay node knows these bounds. We consider the robust design of the MIMO-relay precoder and receive filter based on the minimization of the total MIMO-relay transmit power with constraints on the mean square error (MSE) at the destination nodes. We show that this design problem can be solved by solving an alternating sequence of minimization and worst-case analysis problems. The minimization problem is formulated as a convex optimization problem that can be solved efficiently using interior-point methods. The worst-case analysis problem can be solved analytically using an approximation for the MSEs at the destination nodes. We demonstrate the robust performance of the proposed design through simulations.

Consider L independent and identically distributed exponential random variables (r.vs) X1, X2,...,XLand positive scalars b1, b2,...,bL. In this letter, we present the probability density function (pdf), cumulative distribution function and the Laplace transform of the pdf of the composite r.v Z = (Σ(j=1)LXj)2/(Σ(j=1}LbjXj). We show that the r.v Z appears in various communication systems such as i) maximal ratio combining of signals received over multiple channels with mismatched noise variances, ii) M-ary phase-shift keying with spatial diversity and imperfect channel estimation, and iii) coded multi-carrier code-division multiple access reception affected by an unknown narrow-band interference, and the statistics of the r.v Z derived here enable us to carry out the performance analysis of such systems in closed-form.

In this paper, we present a comparison between the sensitivity of SC-FDMA and OFDMA schemes to large carrier frequency offsets (CFO) and timing offsets (TO) of different users on the uplink. Our study shows the following observations: 1) In the ideal case of zero CFOs and TOs (i.e., perfect synchronization), the uncoded BER performance of SC-FDMA with frequency domain MMSE equalizer is better than that of OFDMA due to the inherent frequency diversity that is possible in SC-FDMA. Also, because of inter-symbol interference in SC-FDMA, the performance of SC-FDMA with MMSE equalizer can be further improved by using low-complexity interference cancellation (IC) techniques. 2) In the presence of large CFOs and TOs, significant multiuser interference (MUI) gets introduced, and hence the performance of SC-FDMA with MMSE equalizer can get worse than that of OFDMA. However, the performance advantage of SC-FDMA with MMSE equalizer over OFDMA (due to the potential for frequency diversity benefit in SC-FDMA) can be restored by adopting multistage IC techniques, using the knowledge of CFOs and TOs of different users at the receiver.

We propose a novel equalizer for ultra wideband (UWB) multiple-input multiple-output (MIMO) channels characterized by severe delay spreads. The proposed equalizer is based on reactive tabu search (RTS), which is a heuristic originally designed to obtain approximate solutions to combinatorial optimization problems. The proposed RTS equalizer is shown to perform increasingly better for increasing number of multipath components (MPC), and achieve near maximum likelihood (ML) performance for large number of MPCs at a much less complexity than that of the ML detector. The proposed RTS equalizer is shown to perform close to within 0.4 dB of single-input multiple-output AWGN performance at 10-3uncoded BER on a severely delay-spread UWB MIMO channel with 48 equal-energy MPCs.

In this paper, we propose a training-based channel estimation scheme for large non-orthogonal space-time block coded (STBC) MIMO systems. The proposed scheme employs a block transmission strategy where an Nttimes Ntpilot matrix is sent (for training purposes) followed by several Nttimes Ntsquare data STBC matrices, where Ntis the number of transmit antennas. At the receiver, we iterate between channel estimation (using an MMSE estimator) and detection (using a low-complexity likelihood ascent search (LAS) detector) till convergence or for a fixed number of iterations. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed scheme at low complexities. The fact that we could show such good results for large STBCs (e.g., 16times16 STBC from cyclic division algebras) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot-based channel estimation and turbo coding) establishes the effectiveness of the proposed scheme.

Non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA) are attractive because they can simultaneously achieve both high spectral efficiencies (same spectral efficiency as in V-BLAST for a given number of transmit antennas) as well as full transmit diversity. Decoding of non-orthogonal STBCs with hundreds of dimensions has been a challenge. In this paper, we present a probabilistic data association (PDA) based algorithm for decoding non-orthogonal STBCs with large dimensions. Our simulation results show that the proposed PDA-based algorithm achieves near SISO AWGN uncoded BER as well as near-capacity coded BER (within 5 dB of the theoretical capacity) for large non-orthogonal STBCs from CDA.We study the effect of spatial correlation on the BER, and show that the performance loss due to spatial correlation can be alleviated by providing more receive spatial dimensions. We report good BER performance when a training-based iterative decoding/channel estimation is used (instead of assuming perfect channel knowledge) in channels with large coherence times. A comparison of the performances of the PDA algorithm and the likelihood ascent search (LAS) algorithm (reported in our recent work) is also presented.

Non-orthogonal space-time block codes (STBC) with large dimensions are attractive because they can simultaneously achieve both high spectral efficiencies (same spectral efficiency as in V-BLAST for a given number of transmit antennas) as well as full transmit diversity. Decoding of non-orthogonal STBCs with large dimensions has been a challenge. In this paper, we present a reactive tabu search (RTS) based algorithm for decoding non-orthogonal STBCs from cyclic division algebras (CDA) having large dimensions. Under i.i.d fading and perfect channel state information at the receiver (CSIR), our simulation results show that RTS based decoding of 12 × 12 STBC from CDA and 4-QAM with 288 real dimensions achieves i) 10−3uncoded BER at an SNR of just 0.5 dB away from SISO AWGN performance, and ii) a coded BER performance close to within about 5 dB of the theoretical MIMO capacity, using rate-3/4 turbo code at a spectral efficiency of 18 bps/Hz. RTS is shown to achieve near SISO AWGN performance with less number of dimensions than with LAS algorithm (which we reported recently) at some extra complexity than LAS.We also report good BER performance of RTS when i.i.d fading and perfect CSIR assumptions are relaxed by considering a spatially correlatedMIMO channelmodel, and by using a training based iterative RTS decoding/channel estimation scheme.

In this paper, we present a belief propagation (BP) based algorithm for decoding non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA) having large dimensions. The proposed approach involves message passing on Markov random field (MRF) representation of the STBC MIMO system. Adoption of BP approach to decode non-orthogonal STBCs of large dimensions has not been reported so far. Our simulation results show that the proposed BP-based decoding achieves increasingly closer to SISO AWGN performance for increased number of dimensions. In addition, it also achieves near-capacity turbo coded BER performance; for e.g., with BP decoding of 24 × 24 STBC from CDA using BPSK (i.e., 576 real dimensions) and rate-1/2 turbo code (i.e., 12 bps/Hz spectral efficiency), coded BER performance close to within just about 2.5 dB from the theoretical MIMO capacity is achieved.

In this paper, we present novel precoder designs for V-BLAST systems which achieve full-rate. We first present a precoding scheme based on algebraic lattices over real number fields. We prove that this full-rate scheme achieves full-diversity, assuming availability of full channel state information at the transmitter. We then propose a precoding scheme which achieves full-rate and high orders of diversity with limited feedback. The proposed scheme involves a precoder codebook design consisting of unitary matrices parametrized by a single angular parameter, thereby requiring less feedback overhead. Our simulation results show that the proposed limited feedback precoding scheme provides a performance improvement of 1.5 dB and 2.5 dB at a bit error rate of 10-3over existing schemes for 2×2 and 4×4 V-BLAST systems, respectively, using 4-QAM.

In this paper, we propose new non-coherent spacetime block code (STBC) designs, which achieve full transmit diversity as well as high rates. We first present a search procedure to generate full-diversity non-coherent unitary space-time codebooks for any number of transmit antennas (nt) and time slots (T ¿ 2nt), using radial coordinates of points lying on the surface of a sphere in RT-nt. The search method generates codebooks having a specified minimum chordal distance, which allows flexibility in achieving coding gain. Further, we propose another unitary design using circulant matrices for any nt, by restricting the search only to suitable constellation sets in R2for the case of T = 2nt. For the latter design, we present two different optimizations; i) to maximize the minimum chordal distance, and ii) to maximize the expected chordal distance. The proposed designs use an analytical design criterion which guarantees full diversity. The proposed designs are shown to outperform Jing and Hassibi codes reported previously in the literature.

In uplink orthogonal frequency division multiple access (OFDMA), carrier frequency offsets (CFO) and/or timing offsets (TO) of other users with respect to a desired user can cause significant multiuser interference (MUI). In this paper, we derive analytical bit error rate (BER) expressions that quantify the degradation of BER due to the combined effect of both CFOs as well as TOs; such an analytical BER derivation has not been reported so far for uplink OFDMA in the presence of CFOs and TOs. For the case when the desired user is perfectly frequency/time aligned (and other users have non-zero CFOs/TOs), we obtain an exact closed-form expression for the BER. For the case when the desired user also has non-zero CFO/TO, we obtain an approximate BER expression involving a single integral. Analytical and simulation results are shown to match quite well.

In this paper, we consider a robust distributed beamforming design that minimizes total relay transmit power with signal-to-noise ratio (SNR) constraint for a wireless relay network in the presence of imperfect channel state information (CSI) at the relays. We consider a system with a transmit and a receive node, and a set of relay nodes. We assume there is no direct link between the transmit and receive nodes. Each node is equipped with a single antenna. The relay nodes perform amplify-and-forward (AF) relaying. The distributed beamforming design based on the assumption of perfect CSI at the relays fails to guarantee the SNR when the CSI available at the relay nodes is imperfect. We present a robust design which ensures that the SNR constraint is satisfied in the presence of imperfect CSI. We adopt a worst-case design and formulate the problem as a convex optimization problem that can be solved efficiently. The robustness of the proposed design to imperfections in CSI is illustrated through simulations.

We study the problem of joint channel estimation and detection in MIMO systems using belief propagation (BP). We propose a BP based algorithm which jointly estimates the MIMO channel matrix and detects the data symbols in a frame (consisting of pilot and data symbols) through message passing in two passes; one pass from the start to the end of a frame and another from the end to the start. A message comprises a small number of parameters that characterize the computed densities of the marginal probabilities. We study the performance of the proposed algorithm in V-BLAST and STBC MIMO systems for varying pilot density and pilot/data power allocation in a frame. Our simulation results show that a close to perfect CSIR performance is achieved by the proposed algorithm using a nonuniform pilot/data power allocation scheme based on the knowledge of the average channel SNR. We show that the proposed BP based joint channel estimation/detection scheme performs better than MMSE channel estimation followed by maximum-likelihood (ML) detection in slow fading.

In this paper, we consider non-linear transceiver designs for multiuser multi-input multi-output (MIMO) downlink in the presence of imperfections in the channel state information at the transmitter (CSIT). The base station (BS) is equipped with multiple transmit antennas and each user terminal is equipped with multiple receive antennas. The BS employs Tomlinson-Harashima preceding (THP) for inter-user interference pre-cancellation at the transmitter. We investigate robust THP transceiver designs based on the minimization of BS transmit power with mean square error (MSE) constraints, and balancing of MSE among users with a constraint on the total BS transmit power. We show that these design problems can be solved by iterative algorithms, wherein each iteration involves a pair of convex optimization problems. The robustness of the proposed algorithms to imperfections in CSIT is illustrated through simulations.

In this paper, we present two robust nonlinear transceiver designs for multiuser multi-input multi-output (MIMO) downlink in the presence of imperfections in the channel state information at the transmitter (CSIT). Both the base station (BS) as well as the users are equipped with multiple antennas. The BS employs Tomlinson-Harashima precoding (THP) for inter-user interference pre-cancellation at the transmitter. First, we consider the case where the CSIT error is Gaussian-distributed. In this case, the robust transceiver design seeks to minimize a stochastic function of the sum mean square error (SMSE) under a constraint on the total BS transmit power. We propose an iterative algorithm to solve this problem. Each iteration involves the solution of a second order cone program (SOCP). Next, we consider the case where the CSIT error can be specified by an uncertainty set. In this case, we consider a minimax design for the robust transceiver, where the worst-case SMSE is minimized under a constraint on the total BS transmit power. We show that this design problem can be solved by an iterative algorithm, wherein each iteration involves a pair of semi-definite programs (SDP). Further, we consider an extension of the proposed algorithm to the case with per-antenna power constraints. We illustrate the robustness of the proposed algorithms to imperfections in CSIT through simulations.

In uplink orthogonal frequency division multiple access (OFDMA), large timing offsets (TO) and/or carrier frequency offsets (CFO) of other users with respect to a desired user can cause significant multiuser interference (MUI). In this letter, we analytically characterize the degradation in the average output signal-to-interference ratio (SIR) due to the combined effect of both TOs as well as CFOs in uplink OFDMA. Specifically, we derive closed-form expressions for the average SIR at the DFT output in the presence of large CFOs and TOs. The analytical expressions derived for the signal and various interference terms at the DFT output are used to devise an interference cancelling receiver to mitigate the effect of CFO/TOinduced interferences.

A relay network with N relays and a single source destination pair is called a partially-coherent relay channel (PCRC) if the destination has perfect channel state information (CSI) of all the channels and the relays have only the phase information of the source-to-relay channels. In this paper, first, a new set of necessary and sufficient conditions for a space-time block code (STBC) to be single-symbol decodable (SSD) for colocated multiple antenna communication is obtained. Then, this is extended to a set of necessary and sufficient conditions for a distributed STBC (DSTBC) to be SSD for a PCRC. Using this, several SSD DSTBCs for PCRC are identified. It is proved that even if a SSD STBC for a co-located MIMO channel does not satisfy the additional conditions for the code to be SSD for a PCRC, single-symbol decoding of it in a PCRC gives full-diversity and only coding gain is lost. It is shown that when a DSTBC is SSD for a PCRC, then arbitrary coordinate interleaving of the in-phase and quadrature-phase components of the variables does not disturb its SSD property for PCRC. Finally, it is shown that the possibility of channel phase compensation operation at the relay nodes using partial CSI at the relays increases the possible rate of SSD DSTBCs from 2/N when the relays do not have CSI to 1/2, which is independent of N.

Large MIMO systems with tens of antennas in each communication terminal using full-rate non-orthogonal space- time block codes (STBC) from cyclic division algebras (CDA) can achieve the benefits of both transmit diversity as well as high spectral efficiencies. Maximum-likelihood (ML) or near-ML decoding of these large-sized STBCs at low complexities, however, has been a challenge. In this paper, we establish that near-ML decoding of these large STBCs is possible at practically affordable low complexities. We show that the likelihood ascent search (LAS) detector, reported earlier by us for V-BLAST, is able to achieve near-ML uncoded BER performance in decoding a 32 times 32 STBC from CDA, which employs 32 transmit antennas and sends 322= 1024 complex data symbols in 32 time slots in one STBC matrix (i.e., 32 data symbols sent per channel use). In terms of coded BER, with a 16 times 16 STBC, rate-3/4 turbo code and 4-QAM (i.e., 24 bps/Hz), the LAS detector performs close to within just about 4 dB from the theoretical MIMO capacity. Our results further show that, with LAS detection, information lossless (ILL) STBCs perform almost as good as full-diversity ILL (FD-ILL) STBCs. Such low-complexity detectors can potentially enable implementation of high spectral efficiency large MIMO systems that could be considered in wireless standards.

In this paper, we investigate cooperative OFDM communications using amplify-and-forward (AF) protocol at the relays, in the presence of imperfect timing synchronization. In most studies on cooperative communications, perfect time synchronization among cooperating nodes is assumed. In practice, however, due to imperfect time synchronization, orthogonality among the subcarriers of the different nodes' signals at the destination receiver can be lost, causing inter-symbol interference (ISI). In this paper, we derive analytical expressions for the average SINR at the DFT output at the destination as a function of timing offset in cooperative OFDM with AF protocol, and illustrate the SINR degradation as a function of the timing offset. We also present an interference canceling (IC) receiver to mitigate the effects of ISI when there is timing offset. We show that the proposed IC receiver achieves improved BER performance even when timing offsets are large.

In this paper, we consider robust joint linear precoder/receive filter design for multiuser multi-input multi-output (MIMO) downlink that minimizes the sum mean square error (SMSE) in the presence of imperfect channel state information (CSI). The base station is equipped with multiple transmit antennas, and each user terminal is equipped with multiple receive antennas. The CSI is assumed to be perturbed by estimation error. The proposed transceiver design is based on jointly minimizing a modified function of the MSE, taking into account the statistics of the estimation error under a total transmit power constraint. An alternating optimization algorithm, wherein the optimization is performed with respect to the transmit precoder and the receive filter in an alternating fashion, is proposed. The robustness of the proposed algorithm to imperfections in CSI is illustrated through simulations.

We consider large MIMO systems, where by 'large' we mean number of transmit and receive antennas of the order of tens to hundreds. Such large MIMO systems will be of immense interest because of the very high spectral efficiencies possible in such systems. We present a low-complexity detector which achieves uncoded near-exponential diversity performance for hundreds of antennas in V-BLAST (i.e., achieves near SISO AWGN performance in a large MIMO fading environment) with an average per-bit complexity of just 0(NtNr), where Ntand Nrdenote the number of transmit and receive antennas, respectively. With an outer turbo code, the proposed detector achieves good coded bit error performance as well. For example, in a 600 transmit and 600 receive antennas V-BLAST system with a high spectral efficiency of 200 bps/Hz (using BPSK and rate-1/3 turbo code), our simulation results show that the proposed detector performs close to within about 4.6 dB of the theoretical capacity. We also adopt the proposed detector for the low-complexity decoding of high-rate non-orthogonal space- time block codes (STBC) from division algebras (DA). We have decoded the 16x16 full-rate STBC from DA using the proposed detector and show that it performs close to within about 5.5 dB of the capacity using 4-QAM and rate-3/4 turbo code at a spectral efficiency of 24 bps/Hz. The practical feasibility of the proposed high-performance low-complexity detector could trigger wide interest in the implementation of large MIMO systems.

Space-time block codes (STBCs) that are single-symbol decodable (SSD) in a co-located multiple antenna setting need not be SSD in a distributed cooperative communication setting. A relay network with N relays and a single source-destination pair is called a partially-coherent relay channel (PCRC) if the destination has perfect channel state information (CSI) of all the channels and the relays have only the phase information of the source- to-relay channels. In this paper, first, a new set of necessary and sufficient conditions for a STBC to be SSD for co-located multiple antenna communication is obtained. Then, this is extended to a set of necessary and sufficient conditions for a distributed STBC (DSTBC) to be SSD for a PCRC, by identifying the additional conditions. Using this, several SSD DSTBCs for PCRC are identified among the known classes of STBCs. It is proved that even if a SSD STBC for a co-located MIMO channel does not satisfy the additional conditions for the code to be SSD for a PCRC, single-symbol decoding of it in a PCRC gives full-diversity and only coding gain is lost.

In this paper, we present a low-complexity, near maximum-likelihood (ML) performance achieving detector for large MIMO systems having tens of transmit and receive antennas. Such large MIMO systems are of interest because of the high spectral efficiencies possible in such systems. The proposed detection algorithm, termed as multistage likelihood-ascent search (M-LAS) algorithm, is rooted in Hopfield neural networks, and is shown to possess excellent performance as well as complexity attributes. In terms of performance, in a 64 × 64 V-BLAST system with 4-QAM, the proposed algorithm achieves an uncoded BER of 10−3at an SNR of just about 1 dB away from AWGN-only SISO performance given by Q(√SNR). In terms of coded BER, with a rate-3/4 turbo code at a spectral efficiency of 96 bps/Hz the algorithm performs close to within about 4.5 dB from theoretical capacity, which is remarkable in terms of both high spectral efficiency as well as nearness to theoretical capacity. Our simulation results show that the above performance is achieved with a complexity of just O(NtNr) per symbol, where Ntand Nrdenote the number of transmit and receive antennas.

Space-time block codes (STBCs) that are single-symbol decodable (SSD) in a co-located multiple antenna setting need not be SSD in a distributed cooperative communication setting. A relay network with N relays and a single source-destination pair is called a partially-coherent relay channel (PCRC) if the destination has perfect channel state information (CSI) of all the channels and the relays have only the phase information of the source-to-relay channels. In our earlier work, we had derived a set of necessary and sufficient conditions for a distributed STBC (DSTBC) to be SSD for a PCRC. Using these conditions, in this paper we show that the possibility of channel phase compensation operation at the relay nodes using partial CSI at the relays increases the possible rate of SSD DSTBCs from 2/N when the relays do not have CSI to 1/2 , which is independent of N. We also show that when a DSTBC is SSD for a PCRC, then arbitrary coordinate interleaving of the in-phase and quadrature-phase components of the variables does not disturb its SSD property. Using this property we are able to construct codes that are SSD and have higher rate than 2/N but giving full diversity only for signal constellations satisfying certain conditions.

Recently, we reported a low-complexity likelihood ascent search (LAS) detection algorithm for large MIMO systems with several tens of antennas that can achieve high spectral efficiencies of the order of tens to hundreds of bps/Hz. Through simulations, we showed that this algorithm achieves increasingly near SISO AWGN performance for increasing number of antennas in i.i.d. Rayleigh fading. However, no bit error performance analysis of the algorithm was reported. In this paper, we extend our work on this low-complexity large MIMO detector in two directions: i)We report an asymptotic bit error probability analysis of the LAS algorithm in the large system limit, where Nt, Nr→ ∞ keeping Nt= Nr, where Ntand Nrare the number of transmit and receive antennas, respectively. Specifically, we prove that the error performance of the LAS detector for V-BLAST with 4-QAM in i.i.d. Rayleigh fading converges to that of the maximum-likelihood (ML) detector as Nt,Nr→ ∞ keeping Nt= Nr. ii)We present simulated BER and nearness to capacity results for V-BLAST as well as high-rate non-orthogonal STBC from Division Algebras (DA), in a more realistic spatially correlated MIMO channel model. Our simulation results show that a) at an uncoded BER of 10−3, the performance of the LAS detector in decoding 16×16 STBC from DA with Nt=Nr=16 and 16-QAM degrades in spatially correlated fading by about 7 dB compared to that in i.i.d. fading, and b) with a rate-3/4 outer turbo code and 48 bps/Hz spectral efficiency, the performance degrades by about 6 dB at a coded BER of 10−4. Our results further show that providing asymmetry in number of antennas such thatNr≫Ntkeeping the total receiver array length same as that for Nr=Nt, the detector is able to pick up the extra receive diversity thereby significantly improving the BER performance.

In this paper, we consider the problem of preceding in large multiuser MISO systems, where by 'large' we mean (i) large number of transmit antennas (Nt) at the base station of the order of tens to hundreds of transmit antennas, and (ii) large number of downlink users (Nu) of the order of tens to hundreds of users where each user has one receive antenna. Such large MISO systems will be of immense interest because of the high capacities (sum-rates) of the order of hundreds of bits/channel use possible in such systems. We propose a vector perturbation based low-complexity precoder, termed as norm descent search (NDS) precoder, which has a complexity of just O(NuNt) per information symbol. This low complexity attribute of the precoder is achieved by searching for the perturbation vector over a reduced search space. Interestingly, in terms of BER performance, the proposed precoder achieves increasingly better BER for increasing Nt, Nu, such that for large Nt, Nuit achieves near-exponential diversity with some SNR loss, thus making it suited for large MISO systems both in terms of complexity as well as performance. The results of uncoded/turbo-coded simulations without and with channel estimation errors are presented.

In this paper, we propose two robust precoder designs for multiple-input multiple-output (MIMO) broadcast channels with imperfect channel state information (CSI). First,we consider a precoder design for a multiuser multiple-input single-output (MISO) downlink, where a base station (BS) equipped with multiple transmit antennas communicates with user terminals which are equipped with a single receive antenna. For this scenario, we propose a robust precoder design based on the minimization of the total BS transmit power under constraints on individual user signal-to-interference-plus-noise ratio (SINR). We show that this problem can be formulated as a second order cone program (SOCP) that can be solved efficiently. Next, we consider a precoder design for a multiuser MIMO downlink, where the user terminals are equipped with multiple receive antennas. For this scenario, we propose a robust joint precoder/receive filter design based on the minimization of a stochastic function of the sum mean square error (SMSE), under a constraint on the total BS transmit power. We solve this problem through an iterative algorithm, wherein the optimization is performed with respect to the transmit precoder and the receive filter in an alternating fashion.

The thirteen papers in this special issue focus on multiuser detection for advanced communication systems and networks. The papers can be divided into three thematic groups: Multiuser detection (MUD) in i) CDMA; ii) MIMO and Multicarrier CDMA/OFDM; and iii) Cooperative Communications.

We consider large MIMO systems, where by 'large' we mean number of transmit and receive antennas of the order of tens to hundreds. Such large MIMO systems will be of immense interest because of the very high spectral efficiencies possible in such systems. We present a low-complexity detector which achieves uncoded near-exponential diversity performance for hundreds of antennas (i.e., achieves near SISO AWGN performance in a large MIMO fading environment) with an average per-bit complexity of just O(NtNr), where Ntand Nrdenote the number of transmit and receive antennas, respectively. With an outer turbo code, the proposed detector achieves good coded bit error performance as well. For example, in a 600 transmit and 600 receive antennas V-BLAST system with a high spectral efficiency of 450 bps/Hz (using BPSK and rate-3/4 turbo code), our simulation results show that the proposed detector performs to within about 7 dB from capacity. This practical feasibility of the proposed high-performance, low-complexity detector could potentially trigger wide interest in the theory and implementation of large MIMO systems. We also illustrate the applicability of the proposed detector in the low-complexity detection of high-rate, non-orthogonal space-time block codes and large multicarrier CDMA (MC-CDMA) systems. In large MC-CDMA systems with hundreds of users, the proposed detector is shown to achieve near single-user performance at an average per-bit complexity linear in number of users, which is quite appealing for its use in practical CDMA systems.

In this letter, we are concerned with adaptive ARQ techniques combined with backoff strategies that exploit the bursty nature of wireless links for improved energy savings. Specifically, we propose an adaptive Go-back-N/Stop-and-Wait (GBN/SAW) protocol with backoff and present a renewal reward analysis of the throughput and energy efficiency performance of the proposed scheme. We show that the GBN protocol with a linear backoff (LBO) strategy results in energy savings of about 2 dB compared to GBN with no backoff (NBO) on highly correlated fading channels when the round-trip delays (RTD) are small, and this energy saving decreases as RTD increases. With adaptive GBN/SAW protocol with LBO, however, the energy saving is retained high even for large RTDs. In fact, the proposed adaptive GBN/SAW protocol with LBO performs quite close to that of an ideal (though not practical) backoff scheme which assumes a priori knowledge of the channel status in each slot.

In this paper, taking the view that a linear parallel interference canceller (LPIC) can be seen as a linear matrix filter, we propose new linear matrix filters that can result in improved bit error performance compared to other LPICs in the literature. The motivation for the proposed filters arises from the possibility of avoiding the generation of certain interference and noise terms in a given stage that would have been present in a conventional LPIC (CLPIC). In the proposed filters, we achieve such avoidance of the generation of interference and noise terms in a given stage by simply making the diagonal elements of a certain matrix in that stage equal to zero. Hence, the proposed filters do not require additional complexity compared to the CLPIC, and they can allow achieving a certain error performance using fewer LPIC stages. We also extend the proposed matrix filter solutions to a multicarrier DS-CDMA system, where we consider two types of receivers. In one receiver (referred to as Type-I receiver), LPIC is performed on each subcarrier first, followed by multicarrier combining (MCC). In the other receiver (called Type-II receiver), MCC is performed first, followed by LPIC. We show that in both Type-I and Type-II receivers, the proposed matrix filters outperform other matrix filters. Also, Type-II receiver performs better than Type-I receiver because of enhanced accuracy of the interference estimates achieved due to frequency diversity offered by MCC.

Multicode operation in space-time block coded (STBC) multiple input multiple output (MIMO) systems can provide additional degrees of freedom in code domain to achieve high data rates. In such multicode STBC systems, the receiver experiences code domain interference (CDI) in frequency selective fading. In this paper, we propose a linear parallel interference cancellation (LPIC) approach to cancel the CDI in multicode STBC signals in frequency selective fading. The proposed detector first performs LPIC followed by STBC decoding. We present an SINK for the proposed detector. We evaluate the bit error rate (BER) performance of the system, and show that the proposed detector effectively cancels the CDI and achieves improved error performance. Our BER results further illustrate how the combined effect of interference cancellation, transmit diversity, and RAKE diversity affects the performance of the system.

A linear processing complex orthogonal design (LPCOD) is a ptimesn matrix epsiv, (pgesn) in k complex indeterminates x1,x2,...,xksuch that (i) the entries of epsiv are complex linear combinations of 0, plusmnxi, i=1,...,k and their conjugates, (ii) epsivHepsiv=D, where epsivHis the Hermitian (conjugate transpose) of epsiv and D is a diagonal matrix with the (i,i)-th diagonal element of the form l1(i)|x1|2+l2(i)|x2|2+...+lk(i)|xk|2where lj(i),i=1,2,...,n, j=1,2,...,k are strictly positive real numbers and the condition l1(i)=l2(i)=...=lk(i), called the equal- weights condition, holds for all values of i. For square designs it is known that whenever a LPCOD exists without the equal-weights condition satisfied then there exists another LPCOD with identical parameters with l1(i)=l2(i)=...=lk(i)=1. This implies that the maximum possible rate for square LPCODs without the equal-weights condition is the same as that of square LPCODs with equal-weights condition. In this paper, this result is extended to a subclass of non-square LPCODs. It is shown that, a set of sufficient conditions is identified such that whenever a non- square (p>n) LPCOD satisfies these sufficient conditions and do not satisfy the equal-weights condition, then there exists another LPCOD with the same parameters n, k and p in the same complex indeterminates with l1(i)=l2(i)=...=lk(i)=1.

In this paper, we propose and analyze a novel idea of performing interference cancellation (IC) in a distributed/cooperative manner, with a motivation to provide multiuser detection (MUD) benefit to nodes that have only a single user detection capability. In the proposed distributed interference cancellation (DIC) scheme, during phase-1 of transmission, an MUD capable cooperating relay node estimates all the sender nodes' bits through multistage interference cancellation. These estimated bits are then sent by the relay node on orthogonal tones in phase-2 of transmission. The destination nodes receive these bit estimates and use them for interference estimation/cancellation, thus achieving IC benefit in a distributed manner. For this DIC scheme, we analytically derive an exact expression for the bit error rate (BER) in a basic five-node network (two source-destination node pairs and a cooperating relay node) on AWGN channels. Analytical BER results are shown to match with simulation results. For more general system scenarios, including more than two source-destination pairs and fading channels without and with space-time coding, we present simulation results to establish the potential for improved performance in the proposed distributed approach to interference cancellation. We also present a linear version of the proposed DIC.

In this paper, taking the view that a linear parallel interference canceller (LPIC) can be seen as a linear matrix filter, we propose new linear matrix filters that can result in improved bit error performance compared to other LPICs in the literature. The motivation for the proposed filters arises from the possibility of avoiding the generation of certain interference and noise terms in a given stage that would have been present in a conventional LPIC (CLPIC). In the proposed filters, we achieve such avoidance of the generation of interference and noise terms in a given stage by simply making the diagonal elements of a certain matrix in that stage equal to zero. Hence, the proposed filters do not require additional complexity compared to the CLPIC, and they can allow achieving a certain error performance using fewer LPIC stages.

Multicode operation in space-time block coded (STBC) multiple input multiple output (MIMO) systems can provide additional degrees of freedom in code domain to achieve high data rates. In such multicode STBC systems, the receiver experiences code domain interference (CDI) in frequency selective fading. In this paper, we propose a linear parallel interference cancellation (LPIC) approach to cancel the CDI in multicode STBC in frequency selective fading. The proposed detector first performs LPIC followed by STBC decoding. We evaluate the bit error performance of the detector and show that it effectively cancels the CDI and achieves improved error performance. Our results further illustrate how the combined effect of interference cancellation, transmit diversity, and RAKE diversity affect the bit error performance of the system.

Synchronization issues pose a big challenge in cooperative communications. The benefits of cooperative diversity could be easily undone by improper synchronization. The problem arises because it would be difficult, from a complexity perspective, for multiple transmitting nodes to synchronize to a single receiver. For OFDM based systems, loss of performance due to imperfect carrier synchronization is severe, since it results in inter-carrier interference (ICI). The use of space-time/space- frequency codes from orthogonal designs are attractive for cooperative encoding. But orthogonal designs suffer from inter- symbol interference (ISI) due to the violation of quasi-static assumption, which can arise due to frequency- or time-selectivity of the channel. In this paper, we are concerned with combating the effects of (i) ICI induced by carrier frequency offsets (CFO), and (ii) ISI induced by frequency selectivity of the channel, in a cooperative communication scheme using space-frequency block coded (SFBC) OFDM. Specifically, we present an iterative interference cancellation (IC) algorithm to combat the ISI and ICI effects. The proposed algorithm could be applied to any orthogonal or quasi-orthogonal designs in cooperative SFBC OFDM schemes.

In uplink OFDMA, carrier frequency offsets (CFO) and/or timing offsets (TO) of other users with respect to a desired user can cause multiuser interference (MUI). In practical uplink OFDMA systems (e.g., IEEE 802.16e standard), effect of this MUI is made acceptably small by requiring that frequency/timing alignment be achieved at the receiver with high precision (e.g., CFO must be within 1 % of the subcarrier spacing and TO must be within l/8th of the cyclic prefix duration in IEEE 802.16e), which is realized using complex closed-loop frequency/timing correction between the transmitter and the receiver. An alternate open-loop approach to handle the MUI induced by large CFOs and TOs is to employ interference cancellation techniques at the receiver. In this paper, we first analytically characterize the degradation in the average output signal-to-interference ratio (SIR) due to the combined effect of large CFOs and TOs in uplink OFDMA. We then propose a parallel interference canceller (PIC) for the mitigation of interference due to CFOs and TOs in this system. We show that the proposed PIC effectively mitigates the performance loss due to CFO/TO induced interference in uplink OFDMA.

Abstract — Use of space-frequency block coded (SFBC) OFDM signals is advantageous in high-mobility broadband wireless access, where the channel is highly time- as well as frequency-selective because of which the receiver experiences both inter-symbol interference (ISI) as well as inter-carrier interference (ICI). ISI occurs due to the violation of the ‘quasi-static ’ fading assumption caused due to frequency- and/or time-selectivity of the channel. In addition, ICI occurs due to time-selectivity of the channel which results in loss of orthogonality among the subcarriers. In this paper, we are concerned with the detection of SFBC-OFDM signals on time- and frequency-selective MIMO channels. Specifically, we propose and evaluate the performance of an interference cancelling receiver for SFBC-OFDM which alleviates the effects of ISI and ICI in highly time- and frequency-selective channels. I.

In this paper, we are concerned with energy efficient area monitoring using information coverage in wireless sensor networks, where collaboration among multiple sensors can enable accurate sensing of a point in a given area-to-monitor even if that point falls outside the physical coverage of all the sensors. We refer to any set of sensors that can collectively sense all points in the entire area-to-monitor as a full area information cover. We first propose a low-complexity heuristic algorithm to obtain full area information covers. Using these covers, we then obtain the optimum schedule for activating the sensing activity of various sensors that maximizes the sensing lifetime. The scheduling of sensor activity using the optimum schedules obtained using the proposed algorithm is shown to achieve significantly longer sensing lifetimes compared to those achieved using physical coverage. Relaxing the full area coverage requirement to a partial area coverage (e.g., 95% of area coverage as adequate instead of 100% area coverage) further enhances the lifetime.

In this paper, we consider the design and bit-error performance analysis of linear parallel interference cancellers (LPIC) for multicarrier (MC) direct-sequence code division multiple access (DS-CDMA) systems. We propose an LPIC scheme where we estimate and cancel the multiple access interference (MAI) based on the soft decision outputs on individual subcarriers, and the interference cancelled outputs on different subcarriers are combined to form the final decision statistic. We scale the MAI estimate on individual subcarriers by a weight before cancellation. In order to choose these weights optimally, we derive exact closed-form expressions for the bit-error rate (BER) at the output of different stages of the LPIC, which we minimize to obtain the optimum weights for the different stages. In addition, using an alternate approach involving the characteristic function of the decision variable, we derive BER expressions for the weighted LPIC scheme, matched filter (MF) detector, decorrelating detector, and minimum mean square error (MMSE) detector for the considered multicarrier DS-CDMA system. We show that the proposed BER-optimized weighted LPIC scheme performs better than the MF detector and the conventional LPIC scheme (where the weights are taken to be unity), and close to the decorrelating and MMSE detectors.

In uplink orthogonal frequency division multiple access (OFDMA) systems, multiuser interference (MUI) occurs due to different carrier frequency offsets (CFO) of different users at the receiver. In this paper, we present a multistage linear parallel interference cancellation (LPIC) approach to mitigate the effect of this MUI in uplink OFDMA. The proposed scheme first performs CFO compensation (in time-domain) followed by K DFT operations (where K is the number of users) and multistage LPIC on these DFT outputs. We scale the MUI estimates by weights before cancellation and optimize these weights by maximizing the average signal-to-interference ratio (SIR) at the output of the different stages of the LPIC. We derive closed-form expressions for these optimum weights. The proposed LPIC scheme is shown to effectively cancel the MUI caused by the other user CFOs in uplink OFDMA. While our proposed approach performs CFO compensation in time-domain, an alternate approach proposed recently by Huang and Letaief performs CFO compensation and interference cancellation in frequency-domain. We show that our approach performs better than the Huang & Letaief's approach when the magnitude of the CFO differences (between desired user CFO and other user CFOs) are small, whereas their approach performs better when the magnitude of the individual CFOs (of other users) are small. Since the CFO values can be arbitrary at the receiver, in order to make the receiver robust under various CFO conditions, we propose simple metrics based on CFO knowledge, which the receiver can compute and use to choose between the time-domain (ours) and the frequency-domain (Huang & Letaief's) cancellers so that better performance among the two approaches is achieved under various CFO conditions.

Employing multiple base stations is an attractive approach to enhance the lifetime of wireless sensor networks. In this paper, we address the fundamental question concerning the limits on the network lifetime in sensor networks when multiple base stations are deployed as data sinks. Specifically, we derive upper bounds on the network lifetime when multiple base stations are employed, and obtain optimum locations of the base stations (BSs) that maximize these lifetime bounds. For the case of two BSs, we jointly optimize the BS locations by maximizing the lifetime bound using a genetic algorithm based optimization. Joint optimization for more number of BSs is complex. Hence, for the case of three BSs, we optimize the third BS location using the previously obtained optimum locations of the first two BSs. We also provide simulation results that validate the lifetime bounds and the optimum locations of the BSs.

In a mobile ad-hoc network scenario, where communication nodes are mounted on moving platforms (like jeeps, trucks, tanks, etc.), use of V-BLAST requires that the number of receive antennas in a given node must be greater than or equal to the sum of the number of transmit antennas of all its neighbor nodes. This limits the achievable spatial multiplexing gain (data rate) for a given node. In such a scenario, we propose to achieve high data rates per node through multicode direct sequence spread spectrum techniques in conjunction with V-BLAST. In the considered multicode V-BLAST system, the receiver experiences code domain interference (CDI) in frequency selective fading, in addition to space domain interference (SDI) experienced in conventional V-BLAST systems. We propose two interference cancelling receivers that employ a linear parallel interference cancellation approach to handle the CDI, followed by conventional V-BLAST detector to handle the SDI, and then evaluate their bit error rates.

In uplink orthogonal frequency division multiple access (OFDMA) systems, multiuser interference (MUI) occurs due to different carrier frequency offsets (CFO) of different users at the receiver. In this paper, we present a multistage linear parallel interference cancellation (LPIC) approach to mitigate the effect of this MUI in uplink OFDMA. The proposed scheme first performs CFO compensation (in time domain) followed by K DFT operations (where K is the number of users) and multi-stage LPIC on these DFT outputs. We present a detailed performance and complexity comparison of the proposed scheme with another scheme proposed recently by Huang and Letaief which performs CFO compensation and interference cancellation in frequency domain using Circular Convolution (we refer to this scheme as HLCC scheme). We show that the HLCC scheme performs better than our scheme when the individual CFO values are small, whereas our scheme performs better than the HLCC scheme when the CFO differences are small (even if the individual CFO values are large). Also, our scheme has lesser complexity than HLCC scheme when the number of subcarriers is large, which is typical in OFDMA systems.

In this paper, we develop first-order Markov models that characterize the packet error processes on Rayleigh fading channels considering binary DPSK/NCFSK modulation. Such models available in the literature so far consider only the fading process ignoring the underlying modulation used. Our contribution in this paper is that we consider first-order Markov models for binary DPSK/NCFSK modulation. To derive the Markov model parameters, we first derive expressions for the second-order statistics of the channel error process (specifically, the auto-correlation function of the bit error process as well as the packet error process), and obtain the Markov model parameters, in closed-form, as a function of normalized Doppler bandwidth, average received SNR and packet length. We also verify the accuracy of the proposed Markov model by deriving closed-form expressions for the mutual information of the channel error process

In uplink orthogonal frequency division multiple access (OFDMA) systems, multiuser interference (MUI) occurs due to different carrier frequency offsets (CFO) of different users at the receiver. In this paper, we present a minimum mean square error (MMSE) based approach to MUI cancellation in uplink OFDMA. We derive a recursion to approach the MMSE solution. We present a structure-wise and performance-wise comparison of this recursive MMSE solution with a linear PIC receiver as well as other detectors recently proposed in the literature. We show that the proposed recursive MMSE solution encompasses several known detectors in the literature as special cases

Increasing network lifetime is important in wireless sensor/ad-hoc networks. In this paper, we are concerned with algorithms to increase network lifetime and amount of data delivered during the lifetime by deploying multiple mobile base stations in the sensor network field. Specifically, we allow multiple mobile base stations to be deployed along the periphery of the sensor network field and develop algorithms to dynamically choose the locations of these base stations so as to improve network lifetime. We propose energy efficient low-complexity algorithms to determine the locations of the base stations; they include i) top-Kmaxalgorithm, ii) maximizing the minimum residual energy (max-min-RE) algorithm, and iii) minimizing the residual energy difference (MinDiff-RE) algorithm. We show that the proposed base stations placement algorithms provide increased network lifetimes and amount of data delivered during the network lifetime compared to single base station scenario as well as multiple static base stations scenario, and close to those obtained by solving an integer linear program (ILP) to determine the locations of the mobile base stations. We also investigate the lifetime gain when an energy aware routing protocol is employed along with multiple base stations

In this paper, we present the design and bit error performance analysis of weighted linear parallel interference cancellers (LPIC) for multicarrier (MC) DS-CDMA systems. We propose an LPIC scheme where we estimate (and cancel) the multiple access interference (MAI) based on the soft outputs on individual subcarriers, and the interference cancelled outputs on different subcarriers are combined to form the final decision statistic. We scale the MAI estimate on individual subcarriers by a weight before cancellation; these weights are so chosen to maximize the signal-to-interference ratios at the individual subcarrier outputs. For this weighted LPIC scheme, using an approach involving the characteristic function of the decision variable, we derive exact bit error rate (BER) expressions for different cancellation stages. Using the same approach, we also derive exact BER expressions for the matched filter (MF) and decorrelating detectors for the considered MC DS-CDMA system. We show that the proposed weighted LPIC scheme performs better than the MF detector and the conventional LPIC (where the weights are taken to be unity), and close to the decorrelating detector

In uplink orthogonal frequency division multiple access (OFDMA) systems, multiuser interference (MUI) occurs due to different carrier frequency offsets (CFO) of different users at the receiver. In this paper, we present a multistage linear parallel interference cancellation (LPIC) approach to mitigate the effect of this MUI in uplink OFDMA. The proposed scheme first performs CFO compensation (in time domain), followed by K DFT operations (where K is the number of users) and multistage LPIC on these DFT outputs. We scale the MUI estimates by weights before cancellation and optimize these weights by maximizing the signal-to-interference ratio (SIR) at the output of the different stages of the LPIC. We derive closed-form expressions for these optimum weights. The proposed LPIC scheme is shown to effectively cancel the MUI caused by the other user CFOs in uplink OFDMA

In this letter, we derive analytical expressions for the bit error rate (BER) of space-time block codes (STBC) from complex orthogonal designs (COD) using quadrature amplitude modulation (QAM) on Rayleigh fading channels. We take a bit log-likelihood ratio (LLR) based approach to derive the BER expressions. The approach presented here can be used in the BER analysis of any STBC from COD with linear processing for any value of M in an M-QAM system. Here, we present the BER analysis and results for a 16-QAM system with i) (2-Tx, L-Rx) antennas using Alamouti code (rate-1 STBC), ii) (3-Tx, L-Rx) antennas using a rate-1/2 STBC, and iii) (5-Tx, L-Rx) antennas using a rate-7/11 STBC. In addition to being used in the BER analysis, the LLRs derived can also be used as soft inputs to decoders for various coded QAM schemes, including turbo coded QAM with space-time coding as in high speed downlink packet access (HSDPA) in 3G.

In this letter, we present a weighted linear parallel interference canceller (LPIC) where the multiple access interference (MAI) estimate in a stage is weighted by a factor before cancellation on Rayleigh fading and diversity channels. We obtain exact expressions for the average signal-to-interference ratio (SIR) at the output of the cancellation stages which we maximize to obtain the optimum weights for different stages. We also obtain closed-form expressions for the optimum weights for the different stages. We show that this SIR-optimized weighted LPIC scheme clearly outperforms both the matched filter (MF) detector as well as the conventional LPIC (where the weight is taken to be unity for all stages), in both near-far as well as non-near-far conditions on Rayleigh fading and diversity channels

In this paper, we consider the design and bit error performance analysis of linear parallel interference cancellers (LPIC) for multicarrier (MC) DS-CDMA systems. We propose an LPIC scheme where we estimate (and cancel) the multiple access interference (MAI) based on the soft decision outputs on individual subcarriers, and the interference cancelled outputs on different subcarriers are combined to form the final decision statistic. We scale the MAI estimate on individual subcarriers by a weight before cancellation. In order to choose these weights optimally, we derive exact closed-form expressions for the bit error rate (BER) at the output of different stages of the LPIC, which we minimize to obtain the optimum weights for the different stages. We show that the proposed BER-optimized weighted LPIC scheme performs better than the MF detector and the conventional LPIC scheme (where the weights are taken to be unity), and close to the decorrelating detector

In this paper, we propose and analyze novel and efficient cross-layer designs involving joint optimization of physical, link, and TCP layers in wireless. Particularly, we investigate the design of symbol mapping diversity (SMD) schemes using M-QAM at the physical layer for optimal goodput performance at the TCP layer. We present the design and TCP goodput analysis of two SMD schemes, one applying SMD at the TCP packet level, termed as full packet SMD (FP SMD), and the other applying SMD at the link layer (LL) packet level, termed as LL ARQ SMD. We show that although the LL ARQ SMD scheme offers good TCP goodput at high SNR, it performs poorer compared to the FP SMD scheme at low SNR because of increased delays incurred due to increased LL retransmissions at low SNR. We therefore propose and analyze a hybrid SMD scheme which adaptively switches modes (between LL ARQ SMD and FP SMD) based on measured LL packet error rate. We show that the hybrid SMD scheme combines the best TCP performance of both LL ARQ SMD and FP SMD under varying channel conditions.

Backoff algorithms can be employed on point-to-point wireless fading links to improve energy efficiency., particularly when the link experiences long deep fades and bursty errors. A backoff scheme at the link layer (LL), applying an appropriate backoff rule upon each LL packet loss event due to channel errors, can intentionally leave the channel idle (i.e., not transmit) for some specified number of slots, thereby reducing the possible energy wastage due to packet transmissions in error. Our new contribution in this paper is that we consider the use of backoff algorithms on wireless fading links with large round-trip delays, propose a go-back-N (GBN) protocol with backoff, and present a renewal-reward analysis of the throughput and energy efficiency performance of the proposed scheme. We show that the GBN protocol with a linear backoff (LBO) strategy results in energy savings of about 2 dB compared to GBN with no backoff (NBO), even in the case of large round-trip delays. In addition, we also propose and analyze an adaptive go-back-N/stop-and-wait (GBN/SAW) ARQ scheme with LL backoff. We show that this scheme with LBO achieves energy efficiency performance quite close to that of an ideal (though not practical) backoff scheme which assumes a priori knowledge of the channel status in each slot.

In this paper, we present weighted linear parallel interference cancellers (LPIC) where the estimated multiple access interference (MAI) from each interfering user is weighted by a factor before cancellation on Rayleigh fading and diversity channels. We obtain exact expressions for the signal-to-interference ratio (SIR) at the output of the cancellation stages which we maximize to obtain the optimum weights for each interfering user in each cancellation stage. For a system that uses same weight for all interfering users in a given stage, we obtain exact closed-form expressions for the optimum weights for the different stages of the LPIC. We show that this SIR-optimized weighted LPIC scheme clearly outperforms both the matched filter (MF) detector as well as the conventional LPIC (where the weight is taken to be unity for all interfering users and for all stages), in both near-far as well as non-near-far conditions.

In this paper, we present an approach for power allocation to maximize the effective system throughput with pricing on the downlink in a CDMA system. We present a pricing policy and obtain the optimum powers for the users to maximize the effective system throughput incorporating this pricing policy. We also study the asymptotic behavior of the system (i.e., when the number of users and the available bandwidth are large). We show that in such a system, all users obtain equal SIR at the optimum point irrespective of their locations and processing gains. We also derive an expression for the maximum asymptotic spectral efficiency

In this paper, we present the optimum selection combining (SC) scheme for M-QAM which minimizes the average bit error rate (BER) on fading channels. We show that the selection combining scheme, where each bit in a QAM symbol selects the diversity branch with the largest magnitude of the log-likelihood ratio (LLR) of that bit, is optimum in the sense that it minimizes the average BER. In this optimum SC scheme, different bits in a given QAM symbol may select different diversity branches (since the largest LLRs for different bits may occur on different diversity branches), and hence its complexity is high. However, this scheme provides the best possible BER performance for M-QAM with selection combining, and can serve as a benchmark to compare the performance of other SC schemes (e.g., selection based on maximum SNR). We compare the BER performance of this optimum SC scheme with other SC schemes where the diversity selection is done based on maximum SNR and maximum symbol LLR.

We obtain closed-form expressions for the bit error rate (BER) of a conventional linear parallel interference canceller (LPIC), where the interference from all other users is estimated and cancelled on Rayleigh fading and diversity channels. We also propose an improved LPIC scheme which cancels the interference from only those users whose instantaneous SNRs exceed a certain threshold on Rayleigh fading channels. We obtain the optimum threshold by optimizing an approximate expression for the SIR at the canceller output. We show that the proposed threshold-based LPIC scheme performs better than the matched filter (MF) detector as well as the conventional LPIC scheme.

In this paper, we present a performance analysis of the bit error performance of detectors in multiuser systems, considering diversity reception with imperfect channel estimation. The detectors we consider are the decorrelating (DC) detector and the conventional matched filter (MF) detector. We consider a pilot-based channel estimation scheme in flat as well as diversity fading channels, and analytically quantify the degradation in the bit error performance of the DC and the MF detectors due to imperfect channel estimates. We show that, while imperfect channel estimates degrade performance compared to perfect channel estimates, the degradation in the bit error performance can be compensated by using a larger number of receive antennas.

We present and analyze the performance of a parallel interference cancellation (PIC) scheme for multicarrier (MC) direct-sequence code-division multiple-access (DS-CDMA) systems. At each cancellation stage in the proposed PIC scheme, on each subcarrier, a weighted sum of the soft outputs of the other users in the current stage is cancelled from the soft output of the desired user (rather than making hard bit decisions of the other users and regenerating and canceling the interfering signals) to form the input to the next stage. At the last stage, the interference cancelled outputs from all the subcarriers are maximal ratio combined (MKC) to form the decision statistic. The scheme has the advantage of not requiring the amplitude estimates of the other users. We derive analytical expressions for the bit error rate (BER) at different stages in the proposed PIC scheme on Rayleigh fading channels. Analytical results are found to agree well with the simulation results. The results show that the proposed PIC scheme offers better interference suppression capability than the conventional matched filter receiver. We also obtain bounds on the coded BER of the proposed PIC scheme for a convolutionally coded multicarrier DS-CDMA system where the PIC-MRC output feeds a soft decision Viterbi decoder.

We derive analytical expressions for the bit error rate (BER) of space-time block codes (STBC) from complex orthogonal designs (COD) with quadrature amplitude modulation (QAM) on Rayleigh fading channels. We take a bit log-likelihood ratio (LLR) based approach to derive the BER expressions. We first derive the LLRs for the various bits forming the QAM symbol and use these LLRs to derive analytical expressions for the error rate of the individual bits forming the QAM symbol and hence the average BER of the system. The approach presented in this paper can be used in the BER analysis of any STBC from COD with linear processing, for any value of M in a M-QAM system. Here, we present the BER analysis and results for a 16-QAM system with i) (2-Tx, L-Rx) antennas using Alamouti code (rate-1 STBC), ii) (3-Tx, L-Rx) antennas using a rate-1/2 STBC and iii) (5-Tx, L-Rx) antennas using a rate-7/11 STBC. The LLRs derived can also be used as soft inputs to decoders for various coded QAM schemes, including turbo coded QAM with space-time coding.

In this paper, we provide an analytical performance comparison of various selection combining (SC) schemes for binary noncoherent frequency-shift keying (NCFSK) signals operating on independent and nonidentically distributed (i.n.d.) Rayleigh fading channels. With this motivation, we first derive the receiver structure for the optimum SC scheme, which combines one out of the available L diversity branches so as to minimize the probability of bit error. We show that the optimum SC scheme chooses the diversity branch having the largest magnitude of the logarithm of the a posteriori probability ratio (LAPPR) of the transmitted information bit. We also show that: 1) the optimum noncoherent diversity receiver, for binary NCFSK signals, is equivalent to combining the LAPPRs of all the diversity branches; 2) the SC scheme proposed by Neasmith and Beaulieu is a special case of the optimum SC scheme for independent and identically distributed (i.i.d.) Rayleigh fading; and 3) for i.n.d. fading with dual diversity (i.e., L=2), the performance of the optimum SC scheme is the same as that of the optimum noncoherent diversity receiver, whereas the Neasmith and Beaulieu SC scheme gives the performance of the suboptimum equal gain combining receiver. Bit-error rate (BER) results show that, at 10/sup -4/ BER, for i.i.d. Rayleigh fading, the proposed optimum SC scheme performs better than the existing SC schemes by 0.5-0.9 dB for L=3 and by 0.8-1.5 dB for L=5, and performs within 0.3 dB of the optimum noncoherent diversity receiver for L=3,5, and for i.n.d. Rayleigh fading with L=5, the optimum SC scheme gives an additional gain of about 2.0 dB over the Pierce SC scheme. Further, for i.i.d. Rayleigh fading, we derive the bit-error probability expression for a (3,L) selection scheme which combines three branches whose LAPPR magnitudes are the largest among the available L branches. Numerical results for this (3,L) selection scheme show that for L=5 at a BER of 10/sup -4/, combining the three branches with the largest LAPPR magnitudes yields almost the full performance of the optimum noncoherent diversity receiver, whereas, for L=7, it is just about 0.2 dB away from the latter.

In this paper, we develop analytical tools for the performance analysis of coded, coherent communication systems on independent and identically distributed Nakagami-m fading channels with selection combining (SC) diversity. First, we derive an exact expression for the moment generation function (MGF) of the signal-to-noise ratio (SNR) of a code symbol at the output of the selection combiner. Next, based on Gauss-Chebyshev quadrature and Gauss-Laguerre quadrature rules, we propose a simple to compute, yet accurate, numerical solution for the pairwise error probability (PEP) of coded M-phase-shift keying (PSK) signals. Using the PEP expressions, we present the union bound-based bit-error performance of trellis-coded modulation schemes and turbo codes. Finally, we derive an exact expression for the computational cutoff rate of a coded system with M-PSK signaling and SC diversity, and show that the cutoff rate expression is a simple function of the MGF of the SNR at the output of the diversity combiner.

In this paper, we present a log-likelihood ratio (LLR) based approach to analyze the bit error rate (BER) performance of quadrature amplitude modulation (QAM) on Rayleigh fading channels without and with transmit diversity. We derive LLRs for the individual bits forming a QAM symbol both on flat fading channels without diversity as well as on channels with transmit diversity using two transmit antennas (Alamouti's scheme) and multiple receive antennas. Using the LLRs of the individual bits forming the QAM symbol, we derive expressions for the probability of error for various bits in the QAM symbol, and hence the average BER. In addition to being used in the BER analysis, the LLRs derived can be used as soft inputs to decoders for various coded QAM schemes including turbo coded QAM with transmit diversity, as in high speed downlink packet access (HSDPA) in 3G.

In this paper, we propose and analyze the bit error performance of a generalized selection combining (GSC) receiver for M-ary non-coherent frequency shift keying (NCFSK) signals on i.i.d. Rayleigh fading channels with L antennas at the receiver. For each of the M hypotheses, the receiver combines the K largest outputs among the L available square-law detector outputs before proceeding to the bit detection process. We derive a closed-form expression for the bit error probability of the proposed (K, L) GSC receiver, and present numerical results to illustrate the bit error performance of this receiver for different values of M, K, and L. We also show that our generalized (K, L) GSC scheme and analysis encompass the previously reported schemes/analyses by Chyi et al. and Hahn a special cases for K = 1 and K = L, respectively.

In this paper, we present a comparative performance evaluation of adaptive multiuser detectors, including stochastic gradient (SG) and recursive least squares (RLS) algorithms (which require training data), and minimum output energy (MOE) and subspace-based MMSE (S-MMSE) algorithms (which do not require training data), under near-far conditions in a space-time coded CDMA system. VVe show that, in a near-far multiuser scenario, increasing the number of transmit antennas degrade the near-far resistance performance of the SG and MOE detectors significantly at high near-far ratios, to the extent that the diversity benefit of multiple transmit antennas is nullified. The RLS and S-MMSE algorithms, on the other hand, are shown to maintain their near-far resistance without loosing much on the diversity gain, when the number of transmit antennas is increased.

In this paper, we analyze the performance of a signal-to-interference ratio (SIR)-based admission control strategy on the uplink in cellular code-division multiple-access (CDMA) systems with voice and data traffic. Most studies in the current literature to estimate CDMA system capacity with both voice and data traffic do not take into account admission control based on SIR constraints. Here, we present an analytical approach to evaluate the outage probability for voice traffic, the average system throughput, and the mean delay for data traffic in a voice/data CDMA system, which employs an SIR-based admission control. We make two main approximations in the voice call outage analysis-one based on the central limit theorem (CLT) and the other based on the Fenton's method. We apply the Fenton's method approximation to compute the retransmission probability and the mean delay for data traffic, and the average system throughput. We show that for a voice-only system, a capacity improvement of about 30% is achieved with the SIR-based admission control as compared with the code availability-based admission control. For a mixed voice/data system with 10 Erlangs of voice traffic, an improvement of about 40% in the mean delay for data is shown to be achieved. Also, for a mean delay of 50 ms with 10 Erlangs of voice traffic, the data Erlang capacity improves by about 50%.

Backoff algorithms are typically employed in multiple-access networks (e.g., Ethernet) to recover from packet collisions. We propose and carry out the analysis for three types of link-layer backoff schemes, namely linear backoff, exponential backoff, and geometric backoff, on point-to-point wireless fading links where packet errors occur non-independently. In such a scenario, the backoff schemes are shown to achieve better energy efficiency without compromising much on the link layer throughput performance.

We analyze the performance of an SIR based admission control strategy in cellular CDMA systems with both voice and data traffic. Most studies in the current literature to estimate CDMA system capacity with both voice and data traffic do not take signal-to-interference ratio (SIR) based admission control into account. In this paper, we present an analytical approach to evaluate the outage probability for voice traffic, the average system throughput and the mean delay for data traffic for a voice/data CDMA system which employs an SIR based admission control. We show that for a data-only system, an improvement of about 25% in both the Erlang capacity as well as the mean delay performance is achieved with an SIR based admission control as compared to code availability based admission control. For a mixed voice/data system with 10 Erlangs of voice traffic, the improvement in the mean delay performance for data is about 40%. Also, for a mean delay of 50 ms with 10 Erlangs voice traffic, the data Erlang capacity improves by about 50%.

In this paper, we derive a new selection combining (SC) scheme for noncoherent binary FSK signals on independent (but not necessarily identically distributed) Rayleigh fading channels with L-antenna diversity reception. With this combining scheme, we choose the diversity branch having the largest magnitude of the logarithm of the ratio of the a posteriori probabilities (log-APP ratio - LAPPR) of the transmitted information bit. We show that this scheme minimizes the probability of bit error, thus proving the optimality. We also show that a) the traditional square-law combining of all L diversity branches is equivalent to combining the LAPPR of all the L diversity branches, and b) the SC scheme proposed by Neasmith and Beaulieu (1998) is a special case of the proposed optimum SC scheme for independent and identically distributed (i.i.d) Rayleigh fading. Bit error probability results show that, at 10/sup -4/ BER, a) for i.i.d Rayleigh fading, the proposed optimum SC combining scheme performs better than the existing SC schemes by 0.5 dB for L = 3 and 1.5 dB for L = 5, and performs within 0.5 dB of the scheme which square-law combines all the L diversity branches, and b) for independent Rayleigh fading, the proposed optimum SC scheme gives an additional gain of 2.0 dB over the SC schemes of Pierce (1958) and Chyi et al. (1989).

In a previous paper, we derived the optimum selection combining (OSC) scheme for binary noncoherent FSK (NCFSK) signals on independent (but not necessarily identically distributed) Rayleigh fading channels with L-antenna diversity reception. In the OSC scheme, the diversity branch having the largest magnitude of the logarithm of the ratio of the a posteriori probabilities (log-APP ratio - LAPPR) of the transmitted information bit is chosen. In this paper, we derive the bit error performance of a (3, L) selection combining scheme for binary NCFSK signals which combines the three branches whose LAPPR magnitudes are the largest among the available L branches in i.i.d Rayleigh fading. Numerical results for this (3, L) selection scheme show that, for L=5, combining the three branches with the largest LAPPR magnitudes yields almost the full performance of the square-law combining of all the L=5 branches. For L=7, the performance of combining the three branches with the largest LAPPR magnitudes is just about 0.2 dB worse from the performance of square-law combining of all the L=7 branches. We also compare the performance of the proposed (3, L) selection scheme with the (3, L) selection combining scheme of Chyi et al. (1989).

In this paper, we analyze the performance of trellis coded modulation (TCM) schemes with generalized selection combining (GSC) on fading channels. We first derive the computational cutoff rate, R/sub 0/, for coherent TCM schemes on i.i.d. Rayleigh fading channels with (K, L) GSC diversity which combines the K paths with the largest instantaneous SNR among the L available diversity paths. The cutoff rate is shown to be a simple function of the moment generating function (MGF) of the SNR at the output of the (K, L) GSC receiver. The cutoff rate results show that, at a cutoff rate of 1 bit/sec/Hz, 8-PSK modulation with (1, 3) GSC requires about the same E/sub b//N/sub 0/ as QPSK modulation with (2,3) GSC. Also, at 1.5 bits/sec/Hz, 8-PSK with (1, 3) GSC and QPSK with (3,3) GSC require about the same E/sub b//N/sub 0/. This illustrates that in TCM schemes with GSC diversity, the modulation complexity (i.e., alphabet size, M) and the GSC receiver complexity (i.e., the number of combined diversity paths, K) can be traded off to achieve a desired performance. Next, we derive the union bound on the bit error probability of TCM schemes with (K, L) GSC reception in the form of a simple, finite integral. The effectiveness of this bound is verified through simulations.

In this paper, we propose a protocol for routing in Bluetooth scatternets. The protocol uses the available battery power in the Bluetooth (BT) devices as a cost metric in choosing the routes. We evaluate the throughput performance as a function of packet arrival rate and number of piconets. A throughput of about 120 kbps/piconet is shown to be achieved in a 5-piconet scatternet. We propose two techniques, namely a) battery power level based master-slave switch and b) distance based power control, to increase the network lifetime in scatternets. The master-slave switch technique is motivated by the fact that a piconet master has to handle the packet transmissions to/from all its slaves, and hence may drain its battery soon. We propose a role switching idea where each BT device in a piconet may have to play the master role depending on its available battery power. In the second technique, we propose that the BT devices choose their transmit powers based on their distances from their respective masters. Our performance results show that a considerable gain in network lifetime can be achieved using these two power saving techniques.

We propose a first-order Markov model for generalized Nakagami-m (1960) flat fading channels. Using a moment generating function (MGF) approach, we derive the parameters of the proposed model for any value of the fading severity index m /spl ges/ 0.5. The proposed model is a generalized version of the one proposed earlier by Zorzi et al. (1995) for flat Rayleigh fading channels. For m = 1, we show that our generalized model gives the same parameter values obtained using Zorzi's approach. Our generalized model thus encompasses Zorzi's model as a special case. We illustrate the usefulness of our proposed Markov model by applying it to the analysis of the throughput and energy efficiency performance of a link layer (LL) protocol with backoff on wireless fading links with different values of the m-parameter (= 0.5,1,4).

We analyze the outage and capacity performance of an interference based admission control strategy in cellular CDMA systems. Most approaches to estimate the outage probability and the system capacity of CDMA systems in the literature do not take interference based admission control into account. In this paper, we present an analytical model to evaluate the outage probability and the capacity on the reverse link of cellular CDMA systems with interference based admission control. We make two main approximations in the outage analysis-one based on the central limit theorem (CLT) and the other based on the Chernoff bound (CB). We also obtain an improved approximation to the outage probability using Edgeworth expansion. It is shown that the considered admission control policy results in increased system capacity compared to that with no admission control, by about 30% for an outage probability of 0.01.

In this paper, we analyze the performance of battery power management schemes in wireless mobile devices using a queueing theory approach. We model the battery as a server with finite service capacity and data packets as customers to be served. With an intent to exploit the recharging capability of the battery when left idle, we allow the battery to go on intentional vacations during which the battery can recharge itself. The recharge thus built up can effectively increase the number of customers served (in other words, battery life can be extended). Such improved battery life performance would, however, come at the expense of increased packet delay performance. We quantify the battery life gain versus delay performance trade-off in this approach through analysis and simulations. By considering a continuous recharge model of the battery, we derive expressions for the number of customers served and the mean delay for an M/GI/1 queueing system without and with server vacations. We show that allowing intentional vacations during busy periods helps to increase battery life, and that this approach can be beneficial when applied to the traffic of delay-tolerant applications. We also propose a packet delay constrained power saving algorithm that will exploit the recharge phenomenon when packet delay constraints are imposed.

We propose an online signal-to-noise ratio (SNR) estimation scheme for Nakagami-m (1960) fading channels with L branch equal gain combining (EGC) diversity. We derive the SNR estimate based on the statistical ratio of certain observables over a block of data, and use the SNR estimates in the iterative decoding of turbo codes on Nakagami-m fading channels with L branch EGC diversity. We evaluate the turbo decoder performance using the SNR estimate under various fading and diversity scenarios (m = 0.5, 1, 5 and L = 1, 2, 3) and compare it with the performance using perfect knowledge of the SNR and the fade amplitudes.

In this paper, we analyze the throughput and energy efficiency performance of user datagram protocol (UDP) using linear, binary exponential, and geometric backoff algorithms at the link layer (LL) on point-to-point wireless fading links. Using a first-order Markov chain representation of the packet success/failure process on fading channels, we derive analytical expressions for throughput and energy efficiency of UDP/LL with and without LL backoff. The analytical results are verified through simulations. We also evaluate the mean delay and delay variation of voice packets and energy efficiency performance over a wireless link that uses UDP for transport of voice packets and the proposed backoff algorithms at the LL. We show that the proposed LL backoff algorithms achieve energy efficiency improvement of the order of 2-3 dB compared to LL with no backoff, without compromising much on the throughput and delay performance at the UDP layer. Such energy savings through protocol means will improve the battery life in wireless mobile terminals.

We are concerned with the performance of turbo codes on Rayleigh fading channels when noncoherent detection is employed. Performance of turbo codes with noncoherent detection on AWGN channels has been analyzed by E.K. Hall and S.G. Wilson (see Proc. IEEE Commun. Theory Mini-Conf, p.66-70, 1997). They compared the performance of turbo codes with the achievable information theoretic channel capacity for noncoherent detection on AWGN channels. We derive the information theoretic channel capacity for noncoherent detection on Rayleigh fading channels, and show that the noncoherent turbo decoder achieves performance close to this theoretical capacity (within 1.5 dB). We further show that the performance of noncoherent turbo decoder without the knowledge of channel fades is quite close (within 0.5 dB at 10/sup -5/ BER) to that with perfect knowledge of the channel fades. Optimum decoding of turbo codes requires the knowledge of channel SNR. With this requirement in mind, we propose online SNR estimation schemes, based on the ratio of certain observables at the output of the noncoherent detector, which when used in the turbo decoder gives performance very close to that with perfect knowledge of channel SNR.

We derive bit error performance bounds for turbo codes on Nakagami fading channels with diversity combining. We first derive the average pairwise error probability expressions for turbo codes with maximal ratio combining (MRC), equal gain combining (EGC), and selection combining (SC) on Nakagami fading channels. Using the pairwise error probability expressions and the union bounding technique, we then obtain bounds on the bit error probability of turbo codes for MRC, EGC, and SC diversity schemes. We present the modified log-MAP turbo decoder for MRC, EGC, and SC, and compare the analytical bounds with simulation results for the special case of 2-antenna diversity with Nakagami parameter m=1 (i.e., Rayleigh fading). Results indicate that the EGC scheme with turbo coding performs close to MRC scheme for i.i.d Rayleigh fading.

We propose an online SNR estimation scheme for generalized fading channels. We derive the SNR estimate based on a statistical ratio of observables over a block of data, when the channel undergoes Nakagami fading. An online SNR estimator for AWGN channels has been derived by Summers and Wilson (see IEEE Trans. Commun., vol.46, no.4, p.421-23, 1998). Our SNR estimation scheme in this paper is for a general Nakagami fading channel, where the SNR estimates in Rayleigh fading and AWGN can be obtained as special cases corresponding to the Nakagami parameter m=1 and m=/spl infin/, respectively. As an example, we use our SNR estimate in the iterative decoding of turbo codes on both i.i.d and correlated Rayleigh fading channels. We show that the turbo decoder performance on Rayleigh fading channels using our SNR estimate is close to the performance using perfect knowledge of the fade amplitudes and the SNR.

We analyze the throughput, delay and energy efficiency performance of space diversity slotted ALOHA when multibeam smart antenna arrays capable of steering the beams selectively on smaller sectors, are used at the base station receiver. Analytical expressions to establish the effect of different beamwidths, number of beams, beam steering patterns, and beam service times on the achieved performance of S-ALOHA an derived. We show that under high load conditions steered beams with long beam service times offer better performance, whereas under light loads static coverage patterns an better. We propose and analyze an energy efficient version of S-ALOUA which uses a beam sensed backoff algorithm at the user terminal. We show that the beam sensed backoff algorithm results in significant energy saving that could potentially increase battery life in wireless user terminals.

We consider interference suppression for direct sequence code division multiple access systems when long codes are used for spreading. In particular, we evaluate the performance of a least mean square (LMS) type adaptive receiver on AWGN and correlated Rayleigh fading channels. The receiver uses a chip matched filter followed by an adaptive equalizer structure which performs despreading and interference suppression. The receiver requires only the knowledge of the long code and timing of the desired user. The probability of the error performance of the long code LMS (LC-LMS) receiver is estimated for varying degrees of near-far ratio (NFR), mobile user speed (equivalently, the Doppler bandwidth), and long code period (expressed in number of information bits). Performance results indicate that the given adaptive receiver outperforms the conventional linear correlation receiver by a considerable margin in high NFR and low mobility (i.e., small Doppler bandwidth) scenarios.

Backoff algorithms are traditionally employed in multiple access networks, like Ethernet, to recover from packet collisions. We propose and carry out the analysis for three types of link layer backoff schemes-linear, binary exponential, geometric-on point-to-point wireless fading links, where packet errors occur non-independently. In such a scenario, the back-off schemes are shown to achieve better energy efficiency without compromising much on the link layer throughput performance.

We investigate the performance of TCP Tahoe and NewReno on wireless links with a FEC/ARQ protocol at the link layer. The effect of link layer (LL) parameters like the LL packet size, number of LL transmission attempts, and FEC code rate on the TCP throughput is evaluated. It is shown that the retransmissions at the link layer must persist long enough to outlast the average bad state duration of the Rayleigh fading process in order to achieve performance better than TCP without an ARQ at the link layer. It is further shown that with a suitable link layer in place, TCP Tahoe offers as high a throughput as offered by other enhanced versions like NewReno in the considered wireless environment.

In this paper, the bulk throughput performance of TCP NewReno over wireless fading links having memory is studied. Like TCP Tahoe, the NewReno version of TCP implements a fast retransmit procedure, but it uses a different congestion window adaptation algorithm. In this study, we show that, for the default parameters of the BSD implementation of TCP over a 1.5 Mbps wireless link having a very small bandwidth-delay product, and as long as sufficiently large advertised window sizes are used, the burstiness in packet errors caused by slow multipath fading (experienced by slow moving users) significantly benefits NewReno compared to i.i.d. packet errors (experienced at vehicular user speeds). We further show that, in such slow fading conditions, NewReno performs no better than Tahoe, mainly due to the high degree of correlation in the fading process.

We are concerned with the performance at the media access control (MAC) layer of the protocol stack when multibeam adaptive antenna arrays are employed at the base station site. Specifically, we analyze the performance of slotted ALOHA when the base station receiver uses multibeam antenna arrays capable of steering the beams selectively on smaller sectors. The effect of different beamwidths, number of beams, beam steering patterns, and beam service times on the achieved throughput-delay performance of slotted-ALOHA is evaluated. It is observed that under high load conditions steered beams with long beam service times offer better performance, whereas under light load conditions static coverage patterns are better.

When user terminals powered by a finite battery source are used for wireless communications, energy constraints are likely to influence the design/choice of media access protocols. We analyze the energy efficiency of a multichannel wireless access protocol using a finite energy source in a mobile radio environment. The average number of correctly transmitted packets for a given amount of allocated energy is used as the appropriate energy efficiency metric. The mobile radio channel itself is characterized by a correlated Rayleigh fading process, whose memory parameters depend on the speed of the user terminal, the data rate, and the physics of the channel. We show that the protocol which recovers erroneous data packets through retransmission is more energy efficient at low channel correlations.

As mobile terminals are powered by a finite battery source, energy constraints play a major role in the design of wireless communications systems. In this letter, based on a general analytical framework, we study the energy efficiency of a class of multiple access schemes, using the average number of correctly transmitted packets for a given amount of allocated energy as an appropriate metric. We show that a good choice of the protocol rules can significantly improve the energy efficiency.

The throughput performance of a wireless media access protocol taking into account the effect of correlated channel fading, capture, and propagation delay is analyzed. For efficient access on the uplink (mobile-to-base-station link), the protocol makes use of the uplink channel status information which is conveyed to the mobiles through a busy/idle flag broadcast on the downlink (base-station-to-mobile link). A first-order Markov model is used to describe the correlation in the packet success/failure process on a Rayleigh-fading channel. The analytical results obtained through the first-order Markov approximation of the channel are compared to those obtained from an independent and identically distributed (i.i.d.) channel model. The Markovian-fading channel model is shown to provide better performance results than the i.i.d. channel model. Simulations show that a first-order Markov approximation of the Rayleigh-fading process is quite accurate. An enhanced version of the access protocol to take advantage of the memory in the fading channel behavior is proposed and analyzed. The effect of retransmission of erroneous data packets and propagation delay on the throughput is also analyzed. It is shown that the access protocol with an error detect (ED) feature is efficient in slow fading (e.g., pedestrian user speeds), whereas a retransmission protocol is more efficient in fast fading (e.g., vehicular user speeds).

The effect of phase noise on the capacities of coherently demodulated hybrid frequency-division multiple access/code division multiple-access (FDMA/CDMA) systems operating over a multipath Rayleigh fading channel is investigated. Using an approximate upper bound on the bit-error rate performance, which has been derived and presented in a previous paper, the capacities of the FDMA/CDMA systems are estimated for several combinations of channel and system parameters. Simulation results are also included to show the effect of the bounding error.