In this paper, we consider an orthogonal time frequency space (OTFS) system in time-varying channels with overspread Doppler shifts, typically found in non-terrestrial multi-satellite links. The overspread Doppler shifts with magnitude greater than half of the subcarrier spacing, result in aliased Doppler shifts in the delay-Doppler (DD) domain due to the OTFS modulo operation. This makes channel estimation very challenging and the traditional channel estimation methods become ineffective. To address this challenge, we propose a DD training frame and a two-stage channel estimation method. The training frame comprises a cosine pilot signal and a pilot symbol. In the first stage of the channel estimation, the pilot symbol in the DD domain is utilized to estimate the delays, aliased Doppler shifts, and channel gains of the propagation paths. In the second stage, the received time domain signal is converted into the frequency domain to detect the peaks of all the Doppler shifts using the cosine pilot signal. Then, we present a threshold-based method to pair the estimated actual Doppler shifts with their corresponding delays and channel gains. The complexity of the proposed channel estimation is also discussed. Finally, the performance of the proposed channel estimation is validated in terms of the normalized mean square error (NMSE) and bit error rate (BER) in various scenarios.

This paper studies the coherent capacity of noiselimited satellite communications between a serving satellite from a mega-constellation and a ground user. The satellite megaconstellation is stochastically modelled as a non-homogeneous binomial point process at the time instance when inter-satellite handover occurs, and thereafter the chosen satellite is on a deterministic orbit that persistently serves the ground user until it is no longer visible. The persistent satellite capacity is derived as an integral closed-form for a handover strategy that randomly chooses a visible satellite. Additional handover strategies are studied by estimating their persistent capacities using Monte Carlo simulations. The nearest-satellite handover strategy outperforms the random handover strategy but is improved upon with a handover strategy that chooses the satellite with the maximum capacity over its projected orbit. The gap between the persistent capacity and the non-persistent capacity from the literature is significant, motivating the use of persistent capacity for accurate analysis of satellite mega-constellations.

A general satellite channel model is proposed for communications between a rapidly moving low Earth orbit (LEO) satellite in a mega-constellation and a stationary user on Earth. The channel uses a non-homogeneous binomial point process (NBPP) for modelling the satellite positions, marked with an ascending/descending binary random variable for modelling the satellite directions. Using the marked NBPP, we derive the probability distributions of power gain, propagation delay, and Doppler shift, resulting in a stochastic signal propagation model for the mega-constellation geometry in isolation of other effects. This forms the basis for our proposed channel model as a randomly time-varying channel. The scattering function of this channel is derived to characterise how the received power is spread in the delay-Doppler domain. Global channel parameters such as path loss and channel spread are analysed in terms of the scattering function. The channel statistics and the global channel parameters closely match realistic orbit simulations of the Starlink constellation.

In low latency applications and in general, for overspread channels, channel delay spread is a large percentage of the transmission frame duration. In this paper, we consider OTFS in anoverspreadchannel exhibiting a delay spread that exceeds the block duration in a frame, where traditional channel estimation (CE) fails. We propose a two-stage CE method based on a delay-Doppler (DD) training frame, consisting of a dual chirp converted from time domain and a higher power pilot. The first stage employs a DD domain embedded pilot CE to estimate the aliased delays (due to modulo operation) and Doppler shifts, followed by identifying all the underspread paths not coinciding with any overspread path. The second stage utilizes time domain dual chirp correlation to estimate the actual delays and Doppler shifts of the remaining paths. This stage also resolves ambiguity in estimating delays and Doppler shifts for paths sharing same aliased delay. Furthermore, we present a modified low-complexity maximum ratio combining (MRC) detection algorithm for OTFS in overspread channels. Finally, we evaluate performance of OTFS using the proposed CE and the modified MRC detection in terms of normalized mean square error (NMSE) and bit error rate (BER).

Orthogonal time-frequency space (OTFS) modulation shows superior performance in high-mobility wireless environments compared to orthogonal frequency division multiplexing (OFDM). In this paper, we consider maximal ratio combining (MRC) detection for an OTFS receiver with oversampling for channels with fractional delays and Doppler shifts. Specifically, we first reformulate input-output relations in delay-Doppler and delay-time domains for an oversampled OTFS receiver. Then we present a modified iterative MRC detection in both domains taking advantage of the oversampled received signal to improve error performance. The complexity of our detection method is equivalent to that of standard MRC detection scaled by the oversampling factor, while remaining much lower than message passing (MP) detection. We also develop a noise whitening approach to decorrelate the oversampled noise in time domain and derive the optimal combining weights of the MRC detection. Simulation results show that the proposed detection with receiver oversampling outperforms the MRC detection with Nyquist sampling, and the oversampling MP detection. Finally, we show that adding noise whitening can significantly improve error performance, compared to the MRC detection without noise whitening. This comes at a small additional computational cost, while still remaining much lower than MP detection.

Federated learning (FL) allows predictive model training on the sensed data in a wireless Internet of Things (IoT) network evading data collection cost in terms of energy, time, and privacy. In this article, for an FL setting, we model the learning gain achieved by an IoT device against its participation cost as its utility. The local model quality and the associated cost differ from device to device due to the device heterogeneity, which could be time varying. We identify that this results in utility unfairness because the same global model is shared among the devices. In the vanilla FL setting, the master is unaware of devices’ local model computation and transmission costs, thus, it is unable to address the utility unfairness problem. In addition, a device may exploit this lack of knowledge at the master to intentionally reduce its expenditure and thereby boost its utility. We propose to control the quality of the global model shared with the devices, in each round, based on their contribution and expenditure. This is achieved by employing differential privacy (DP) to curtail global model divulgence based on the learning contribution. Furthermore, we devise adaptive computation and transmission policies for each device to control its expenditure in order to mitigate utility unfairness. Our results show that the proposed scheme reduces the standard deviation of the energy cost of devices by 99% in comparison to the benchmark scheme, while the standard deviation of the training loss of devices varies around 0.103.

Unmanned aerial vehicles (UAVs) are envisioned to be extensively employed for assisting wireless communications in the Internet of Things (IoT). On the other hand, terahertz (THz)-enabled intelligent reflecting surface (IRS) is expected to be one of the core enabling technologies for forthcoming beyond-5G (B5G) wireless communications that promise a broad range of data-demand applications. In this article, we propose a UAV-mounted IRS (UIRS) communication system over THz bands for confidential data dissemination from an access point (AP) toward multiple ground user equipments (UEs) in IoT networks. Specifically, the AP intends to send data to the scheduled UE, while unscheduled UEs may behave as potential adversaries. To protect information messages from the privacy preservation perspective, we aim to devise an energy-efficient multi-UAV covert communication scheme, where the UIRS is for reliable data transmissions, and an extra UAV is utilized as an aerial cooperative jammer, opportunistically generating artificial noise (AN) to degrade unscheduled UEs detection, leading to communication covertness improvement. This poses a novel max-min optimization problem in terms of minimum average energy efficiency (mAEE), aiming to improve covert throughput and reduce UAVs’ propulsion energy consumption, subject to satisfying some practical constraints such as the covertness requirements for which we obtain analytical expressions. Since the optimization problem is nonconvex, we tackle it via the block successive convex approximation (BSCA) approach to iteratively solve a sequence of approximated convex subproblems, designing the binary user scheduling, AP’s power allocation, maximum AN jamming power, IRS beamforming, and both UAVs’ trajectory and velocity planning. Finally, we present a low-complex overall algorithm for system performance enhancement with complexity and convergence analysis. Numerical results are provided to verify the analysis and demonstrate significant outperformance of our design over other existing benchmark schemes concerning the mAEE performance.

In this paper, we investigate an intelligent reflecting surface (IRS) aided wireless system adopting a finite number of IRS elements with and without a direct path between access point (AP) and the user. Assuming the maximum received power, we present the bit error rate (BER) and average achievable rate (AAR) analysis of IRS-based systems. In particular, we derive a closed-form BER approximation, which enables us to predict the asymptotic performance variation with signal-to-noise ratios (SNRs) and the number of IRS elements. Further, we derive an upper bound on AAR with direct path, then tight upper and lower bounds on AAR without direct path. Simulation results demonstrate that our analysis offers more accurate BERs than the existing works and all bounds are very close to simulated AARs.

Non-binary low-density parity-check (NB-LDPC) codes can offer promising performance advantages but suffer from high decoding complexity. To tackle this challenge, in this paper, we consider NB-LDPC codes over finite fields as codes over subfields as a means of reducing decoding complexity. In particular, our approach is based on a novel method of expanding a non-binary Tanner graph over a finite field into a graph over a subfield. This approach offers several decoding strategies for a single NB-LDPC code, with varying levels of performance-complexity trade-offs. Simulation results demonstrate that in a majority of cases, performance loss is minimal when compared with the complexity gains.

This article considers a dual-hop Internet of Things communications network where sensor nodes transmit data to a gateway either directly or via other nodes using dual-hop communications. Each node employs separate transmission buffers to store its own sensing data and data received from other nodes. End-to-end delay quality-of-service constraints in terms of the maximum acceptable delay-outage probabilities are imposed. We investigate energy-efficient adaptive resource allocation problems (i.e., joint link scheduling, rate, and power allocation) to support minimum data rates of the nodes. A novel approach is proposed exploiting asymptotic delay analysis to first determine the achieved delay exponents of the queue length tail distributions to satisfy the delay-outage constraints. Next, the relation between the delay exponents and resource allocation variables are derived. Last, the solutions to the resulting constrained optimization problems are obtained using the Lagrangian approach and convex optimization. Illustrative examples demonstrate the effects of the rate requirements and delay constraint stringency on the power consumption and routing configuration.

Although the combination of the orthogonal time frequency space (OTFS) modulation and the massive multiple-input multiple-output (MIMO) technology can make communication systems perform better in high-mobility scenarios, there are still many challenges in downlink channel estimation owing to inaccurate modeling and high pilot overhead in practical systems. In this paper, we propose a channel state information (CSI) acquisition scheme for downlink massive MIMO-OTFS in presence of the fractional Doppler, including deterministic pilot design and channel estimation algorithm. First, we analyze the input-output relationship of the single-input single-output (SISO) OTFS based on the orthogonal frequency division multiplexing (OFDM) modem and extend it to massive MIMO-OTFS. Moreover, we formulate an accurate model for the practical system in which the fractional Doppler is considered and the influence of subpaths is revealed. A deterministic pilot design is then proposed based on the model and the structure of the pilot matrix to reduce pilot overhead and save memory consumption. Since channel geometry changes very slowly relative to the communication timescale, we put forward a modified sensing matrix based channel estimation (MSMCE) algorithm to acquire the downlink CSI. Simulation results demonstrate that the proposed downlink CSI acquisition scheme has significant advantages over traditional algorithms.

This paper proposesorthogonal time sequency multiplexing (OTSM), a novel single carrier modulation scheme that places information symbols in the delay-sequency domain followed by a cascade of time-division multiplexing (TDM) and Walsh-Hadamard sequence multiplexing. Thanks to the Walsh Hadamard transform (WHT), the modulation and demodulation do not require complex domain multiplications. For the proposed OTSM, we first derive the input-output relation in the delay-sequency domain and present a low complexity detection method taking advantage of zero-padding. We demonstrate via simulations that OTSM offers high performance gains over orthogonal frequency division multiplexing (OFDM) and similar performance to orthogonal time frequency space (OTFS), but at lower complexity owing to WHT. Then we propose a low complexity time domain channel estimation method. Finally, we show how to include an outer error control code and a turbo decoder to improve error performance of the coded system.

NB-LDPC codes, a class of codes well-known for their exceptional error correcting performance, are not yet used widely in practice due to the high complexity of decoding algorithms. In this paper, we propose a low complexity decoder for these codes by means of a novel graph expansion. We view the finite field over which the code is constructed as the quadratic extension of one of its subfields, and then expand the Tanner graph of the code into a graph over that particular field. Decoding algorithm, which is tailored for this larger graph, presents significant complexity gains while the performance loss is minimal.

Staircase codes, a class of product-like codes, have been demonstrated to perform exceptionally well in optical transmission systems. Although they are predominantly used with BCH component codes and hard decision decoding, soft decision decoding has also been recently attempted, with BCH and polar code based staircase codes. We consider using LDPC codes as the component code of soft decoded staircase codes. Results demonstrate that these codes offer very good performance, with gains in the range of 0.5-1dB over soft decoded BCH-staircase codes, at a BER of 1$0^{-8}$. These can be further improved through the novel bit-flipping scheme we propose.

Non-binary low-density parity-check (NB-LDPC) codes are known to offer several advantages over their binary counterparts, but the higher complexity, and the resource-hungry nature of decoding algorithms have so far restricted their practical usage. In this paper, we propose a new decoding algorithm for NB-LDPC codes over finite fields of characteristic 2, based on a novel binary expansion of the Q-ary Tanner graph. While it offers substantial complexity gains, simulation results demonstrate that the performance loss of the new algorithm, in comparison to the best known decoder, is quite small. Furthermore, due to being based on a binary graph, it is particularly attractive for hardware implementations. We also suggest a simplified version of the algorithm, which offers even higher gains in complexity.

This paper presents a majority-logic decoding (MLgD) algorithm for non-binary LDPC codes based on a novel expansion of the Tanner graph. The expansion introduced converts the Q-ary graph into a binary one, which makes the new MLgD algorithm more attractive for hardware implementations. Proposed algorithm performs significantly better than the existing MLgD algorithms in the waterfall region, and it shows a much lower error-floor as well. Algorithm only requires integer additions, comparisons, finite field operations and some binary operations. Thus, it offers an effective trade-off between performance and complexity in decoding non-binary LDPC codes.

Multicasting K independent messages via multipleinput multiple-output channels to multiple users where each user already has a subset of messages as side information is studied. A general framework of constructing layered space-time index coding (LSTIC) from a large class of space-time block codes (STBC), including perfect STBC, is proposed. We analyze the proposed LSTIC and show that it provides minimum determinant gains that are exponential with the amount of information contained in the side information for any possible side information. When constructed over a perfect STBC, the proposed LSTIC is itself a perfect STBC and hence many desired properties are preserved. To illustrate, we construct LSTIC over the following wellknown STBCs: Golden code; 3×3, 4×4, and 6×6 perfect STBCs; and Alamouti code. Simulation results show that the obtained side information gain can be well predicted by our analysis.

Multicasting K independent messages via multiple-input multiple-output (MIMO) channels to multiple users where each user already has a subset of messages as side information is studied. A general framework of constructing layered spacetime index coding (LSTIC) from a large class of space-time block codes (STBCs), including perfect STBCs, is proposed. We analyze the proposed LSTIC technique and show that it provides minimum determinant gains that are exponential in the amount of information contained in the side information for any possible side information at the receivers. When constructed over a perfect STBC, the proposed LSTIC is itself a perfect STBC and hence enjoys many desired properties.

Orthogonal time frequency space (OTFS) modulation was shown to provide significant error performance advantages over orthogonal frequency division multiplexing (OFDM) over delay-Doppler channels. The channel impulse response is needed at the receiver to perform OTFS detection. In this work, we analyze OTFS-based channel estimation using a pilot symbol embedded in the data frame: the pilot symbol with a number of guard zero-symbols is suitably located on the delay-Doppler grid containing the information symbols. Different symbol arrangements are proposed depending on whether the channel has integer or fractional Doppler paths relative to an integer grid. The channel information is first estimated from a group of received symbols using a simple threshold method. The estimated information is then used for data detection within the same frame, via a message passing (MP) algorithm. Numerical results compare the error performance of the proposed schemes and the OTFS scheme with ideal channel estimation under similar spectral and energy efficiency. Moreover, our results show that OTFS with non-ideal channel estimation can still outperform OFDM with ideal channel estimation.

This paper develops novel transmission schemes to support secure dual-hop Alice-Ray-Bob relaying communication in the presence of a passive eavesdropper (Eve). Due to unknown eavesdropper channel conditions, data transmissions from Alice (to Ray) and from Ray (to Bob) are required to satisfy the secrecy constraint in terms of maximum acceptable secrecy outage probability (SOP). The throughput maximization problem is studied for two scenarios: 1) fixed (Alice and Ray) power allocation; and 2) adaptive power allocation. The resulting constrained optimization problems are solved using the Lagrangian approach. In each frame, either Alice or Ray or neither can be scheduled for transmission depending on the instantaneous main channel conditions. Numerical results demonstrate the effectiveness of the proposed schemes over the existing schemes under various secrecy constraint and signal-to-noise power ratio (SNR) regimes.

We elaborate on the recently proposed orthogonal time frequency space (OTFS) modulation technique, which provides significant advantages over orthogonal frequency division multiplexing (OFDM) in Doppler channels. We first derive the input-output relation describing OTFS modulation and demodulation (mod/demod) for delay-Doppler channels with arbitrary number of paths, with given delay and Doppler values. We then propose a low-complexity message passing (MP) detection algorithm, which is suitable for large-scale OTFS taking advantage of the inherent channel sparsity. Since the fractional Doppler paths (i.e., not exactly aligned with the Doppler taps) produce the inter Doppler interference (IDI), we adapt the MP detection algorithm to compensate for the effect of IDI in order to further improve performance. Simulations results illustrate the superior performance gains of OTFS over OFDM under various channel conditions.

Lattices possess elegant mathematical properties which have been previously used in the literature to show that structured codes can be efficient in a variety of communication scenarios, including coding for the additive white Gaussian noise channel, dirty-paper channel, Wyner-Ziv coding, coding for relay networks, and so forth. We consider the family of single-transmitter multiple-receiver Gaussian channels, where the source transmits a set of common messages to all the receivers (multicast scenario), and each receiver has coded side information, i.e., prior information in the form of linear combinations of the messages. This channel model is motivated by applications to multi-terminal networks, where the nodes may have access to coded versions of the messages from previous signal hops or through orthogonal channels. The capacity of this channel is known and follows from the work of Tuncel (2006), which is based on random coding arguments. In this paper, following the approach of Erez and Zamir, we design lattice codes for this family of channels when the source messages are symbols from a finite field Fpof prime size. Our coding scheme utilizes Construction A lattices designed over the same prime field Fp, and uses algebraic binning at the decoders to expurgate the channel code and obtain good lattice subcodes, for every possible set of linear combinations available as side information. The achievable rate of our coding scheme is a function of the size p of underlying prime field, and approaches the capacity as p tends to infinity.

In this paper, we develop novel transmission schemes for secure dual-hop Alice-Ray-Bob relaying communication over fading channels in the presence of a passive eavesdropper (Eve). To control the risk of secrecy outage under unknown eavesdropper channel conditions, we impose secrecy constraint in terms of maximum allowable secrecy outage probability. We study the throughput-optimal buffer-aided adaptive relaying problem for two scenarios: 1) fixed (Alice and Ray) power allocation and 2) adaptive power allocation. The resulting constrained optimization problems are solved using Lagrangian approach and convex optimization. In each frame, either Alice or Ray or neither is scheduled for transmission depending on the main (Alice-Ray and Ray-Bob) channel conditions. Since the transmission schemes can result in unboundedly large (queuing) delay at Ray's buffer, we next study the transmission schemes guaranteeing the bounded average delay. The optimal transmission problem is formulated as an infinite horizon average reward constrained Markov decision process. Subsequently, by relying on a novel state value function approach, we show that in each frame, the solution can be obtained by solving a concave maximization problem, taking into account both the main channel conditions and the buffer state. An online transmission algorithm is developed to iteratively update the state value function, which converges to the optimal solution without requiring a-priori statistical information on the fading channels. The simulation results demonstrate the effectiveness of the proposed schemes over benchmark schemes under various secrecy constraints and signal-to-noise power ratio regimes.

The recently proposed orthogonal time-frequency-space (OTFS) modulation technique was shown to provide significant error performance advantages over orthogonal frequency division multiplexing (OFDM) over delay-Doppler channels. In this paper, we first derive the explicit input-output relation describing OTFS modulation and demodulation (mod/demod). We then analyze the cases of: 1) ideal pulse-shaping waveforms that satisfy the bi-orthogonality conditions and 2) rectangular waveforms which do not. We show that while only inter-Doppler interference (IDI) is present in the former case, additional inter-carrier interference (ICI) and inter-symbol interference (ISI) occur in the latter case. We next characterize the interferences and develop a novel low-complexity yet efficient message passing (MP) algorithm for joint interference cancellation (IC) and symbol detection. While ICI and ISI are eliminated through appropriate phase shifting, IDI can be mitigated by adapting the MP algorithm to account for only the largest interference terms. The MP algorithm can effectively compensate for a wide range of channel Doppler spreads. Our results indicate that OTFS using practical rectangular waveforms can achieve the performance of OTFS using ideal but non-realizable pulse-shaping waveforms. Finally, simulation results demonstrate the superior error performance gains of the proposed uncoded OTFS schemes over OFDM under various channel conditions.

We study the problem of constructing good spacetime codes for broadcasting K independent messages over a MIMO network to L users, where each user demands all the messages and already has a subset of messages as side information. As a first attempt, we consider the 2 × 2 case and propose golden-coded index coding by partitioning the golden codes into K subcodes, one for each message. The proposed scheme is shown to have the property that for any side information configuration, the minimum determinant of the code increases exponentially with the amount of information contained in the side information.

Lattices possess elegant mathematical properties which have been previously used in the literature to show that structured codes can be efficient in a variety of communication scenarios. We consider the family of single-transmitter multiple-receiver Gaussian channels where the source transmits a set of common messages to all the receivers (multicast scenario), and each receiver has coded side information, i.e., prior information in the form of linear combinations of the messages. This channel model is motivated by applications to multi-terminal networks where the nodes may have access to coded versions of the messages from previous signal hops or through orthogonal channels. The capacity of this channel is known and follows from the work of Tuncel (2006), which is based on random coding arguments. In this paper, following the approach introduced by Erez and Zamir, we show that lattice codes are capacity-optimal for this family of channels. The structured coding scheme proposed in this paper is derived from Construction A lattices designed over prime fields, and utilizes algebraic binning at the decoders to expurgate the channel code and obtain good lattice subcodes, for every possible set of linear combinations available as side information.

In multiple-input multiple-output (MIMO) channels with discrete input alphabets, at high signal-to-noise ratio (SNR), maximizing the minimum Euclidean distance (dmin) between all possible received constellation points is known to be the optimal precoding strategy. However, finding the optimal precoder has been proved to be NP-hard. For large MIMO, a promising practical approach is to transform the channel into parallel 2 × 2 MIMO subchannels and then precode each of them separately. However, existing methods are mostly based on heuristic subchannel pairing schemes and require numerical search/optimization in the design phase. In this work, we propose a novel real-valued precoder, named as XY-precoder, which enjoys an explicit construction, a provable dmin, a provably optimal subchannel pairing scheme, and low ML-decoding complexity. We prove that the XY-precoder achieves the same diversity order as the best known precoder, but with a much lower decoding complexity. Simulation results confirm that the error performance of XY-precoder is almost the same as that of the best known precoders.

Self-coherent orthogonal frequency division multiplexing (OFDM) was introduced to wireless communications as a promising physical layer technique due to its complete immunity against phase noise, simple radio frequency (RF) front-end receiver, and good spectral efficiency achievability. In this paper, we propose an Alamouti coded multiple-input multiple-output (MIMO) self-coherent OFDM and analyze its performance in terms of diversity order. We prove theoretically that the system exhibits a diversity loss due to a doubly fading effect experienced by both the RF carrier and OFDM subcarriers. To compensate this loss, we exploit the smart carrier positioning (SCP) technique in conjunction with the proposed system. We present a novel diversity analysis, which proves the system with SCP approaches full diversity. Finally, we show by simulations that the system with SCP outperforms the other known non-coherent OFDM schemes as well as the conventional MIMO-OFDM, when phase noise presents.

In this paper, we study a three-dimensional (3D) massive multiple-input-multiple-output (MIMO) system where a horizontal planar antenna array hovers in the sky, serving multiple single-antenna users in a cell on the ground. We consider the uplink where the users transmit to the antenna array utilising perfect uplink power control. Assuming pure line-of-sight (LoS) propagation conditions, the planar array performs receiver maximum-ratio-combining (MRC). We adopt a 3D freespace propagation channel model, which enables us to exploit both the azimuth and elevation dimensions of the space. Under such a setting, we analyse the intra-cell uplink interference. The effective single-user interference and total interference can then be modelled by Beta and Beta-mixture distributions, respectively. In particular, we point out that the height of the hovering antenna can be adjusted to minimise the interference in the system, and thus optimise all the signal-to-interference ratio (SIR) related performance metrics such as coverage and average throughput.

We construct error correcting codes for jointly transmitting a finite set of independent messages to an informed receiver which has prior knowledge of the values of some subset of the messages as side information. The transmitter is oblivious to the message subset already known to the receiver and performs encoding in such a way that any possible side information can be used efficiently at the decoder. We construct and identify several families of algebraic error correcting codes for this problem using cyclic and maximum distance separable (MDS) codes. The proposed codes are of short block length, many of them provide optimum or near-optimum error correction capabilities and guarantee larger minimum distances than known codes of similar parameters for informed receivers. The constructed codes are also useful as error correcting codes for index coding when the transmitter does not know the side information available at the receivers.

In this paper, we provide a solution to the open problem of computing the Fourier transform of a binary function defined over n-bit vectors taking m-bit vector values. In particular, we introduce the two-modular Fourier transform (TMFT) of a binary function f : G → ℜ, where G = (F2n, +) is the group of n bit vectors with bitwise modulo two addition +, and ℜ is a finite commutative ring of characteristic 2. Using the specific group structure of G and a sequence of nested subgroups of G, we define the fast TMFT and its inverse. Since the image ℜ of the binary functions is a ring, we can define the convolution between two functions f : G → ℜ. We then provide the TMFT properties, including the convolution theorem, which can be used to efficiently compute convolutions. Finally, we derive the complexity of the fast TMFT and the inverse fast TMFT.

In this paper, we introduce self-coherent orthogonal frequency-division multiplexing (OFDM), a well-known non-coherent technique in optical communications, for wireless radio frequency communications. Self-coherent OFDM provides complete immunity against phase noise (PN) using a non-coherent receiver and a significantly higher spectral efficiency than self-heterodyne (self-het) OFDM, which utilizes at most 50% of the available spectrum for communications. We present the performance analysis of self-coherent OFDM over additive white Gaussian noise and frequency selective fading channels, and show by simulations that self-coherent OFDM provides both higher spectral efficiency and better bit error rate performance than self-het OFDM. Considering that filter realization in high-frequency bands is challenging, we adopt the undersampling downconversion technique in conjunction with self-coherent OFDM. We show that with the self-coherent demodulation, the additional PN introduced by undersampling downconversion can be significantly reduced. We compare analytically the system performance of self-coherent OFDM using undersampling downconversion with two other conventional OFDM systems: one with super-heterodyne receiver and the other with undersampling downconversion. We show theoretically and by simulations that both in AWGN and frequency selective fading channels, self-coherent OFDM with undersampling downconversion outperforms the two conventional OFDM systems even when intercarrier interference compensation schemes are applied.

In this paper, we present self-coherent OFDM, a well-known non-coherent technique in optical communications, for wireless RF communications. Self-coherent OFDM is known to have complete immunity against phase noise using a simple RF front-end receiver and to provide a significantly higher spectral efficiency than self-het OFDM, which uses at most 50% of the available spectrum for communications. We present the performance analysis of self-coherent OFDM over additive white Gaussian noise (AWGN) and frequency selective fading channels. We show by simulations that self-coherent OFDM provides not only a higher spectral efficiency but also a better bit error rate (BER) performance than self-het OFDM. Finally, we discuss the impact on the system performance of the filters design parameters used in the self-coherent OFDM receiver.

The Unshared Secret Key Cryptography (USK), recently proposed by the authors, guarantees Shannon's ideal secrecy and perfect secrecy for MIMO wiretap channels, without requiring secret key exchange. However, the requirement of infinite constellation inputs limits its applicability to practical systems. In this paper, we propose a practical USK scheme using finite constellation inputs. The new scheme is based on a cooperative jamming technique, and is valid even if the eavesdropper has more antennas than the transmitter. We show that Shannon's ideal secrecy can be achieved with an arbitrarily small outage probability.

We consider the special case of index coding over the Gaussian broadcast channel where each receiver has prior knowledge of a subset of messages at the transmitter and demands all the messages from the source. We propose a concatenated coding scheme for this problem, using an index code for the Gaussian channel as an inner code/modulation to exploit side information at the receivers, and an outer code to attain coding gain against the channel noise. We derive the capacity region of this scheme by viewing the resulting channel as a multiple-access channel with many receivers, and relate it to the side information gain - which is a measure of the advantage of a code in utilizing receiver side information - of the inner index code/modulation. We demonstrate the utility of the proposed architecture by simulating the performance of an index code/modulation concatenated with an off-the-shelf convolutional code through bit-interleaved coded-modulation.

In this paper we introduce the two-modular Fourier transform of a binary function f : R → R defined over a finite commutative ring R = F2[X]/ϕ(X), where F2[X] is the ring of polynomials with binary coefficients and ϕ(X) is a polynomial of degree n, which is not a multiple of X. We also introduce the corresponding inverse Fourier transform. We then prove the corresponding convolution theorem.

The index coding problem involves a sender with K messages to be transmitted across a broadcast channel, and a set of receivers each of which demands a subset of the K messages while having prior knowledge of a different subset as side information. We consider the specific instance of noisy index coding where the broadcast channel is Gaussian and every receiver demands all the messages from the source. We construct lattice index codes for this channel by encoding the K messages individually using K modulo lattice constellations and transmitting their sum modulo a shaping lattice. We introduce a design metric called side information gain that measures the advantage of a code in utilizing the side information at the receivers, and hence its quality as an index code. Based on the Chinese remainder theorem, we then construct lattice index codes for the Gaussian broadcast channel. Among all lattice index codes constructed using any densest lattice of a given dimension, our codes achieve the maximum side information gain.

The artificial noise (AN) scheme, proposed by Goel and Negi, is being considered as one of the key enabling technology for secure communications over multiple-output multiple-input wiretap channels. However, the decrease in secrecy rate due to the increase in the number of Eve's antennas is not well understood. In this paper, we develop an analytical framework to characterize the secrecy rate of the AN scheme as a function of Eve's SNR, Bob's SNR, the number of antennas in each terminal, and the power allocation scheme. We first derive a closed-form expression for the average secrecy rate. We then derive a closed-form expression for the asymptotic instantaneous secrecy rate with large number of antennas at all terminals. Finally, we derive simple lower and upper bounds on the average/instantaneous secrecy rate that provide a tool for the system design.

The index coding problem involves a sender with K messages to be transmitted across a broadcast channel, and a set of receivers each of which demands a subset of the K messages while having a prior knowledge of a different subset as side information. We consider the specific case of noisy index coding where the broadcast channel is Gaussian and every receiver demands all the messages from the source. Instances of this communication problem arise in wireless relay networks, sensor networks, and retransmissions in broadcast channels. We construct lattice index codes for this channel by encoding the K messages individually using K modulo lattice constellations and transmitting their sum modulo a coarse lattice. We introduce a design metric called side information gain that measures the advantage of a code in utilizing the side information at the receivers, and hence, its goodness as an index code. Based on the Chinese remainder theorem, we then construct lattice index codes with large side information gains using lattices over the following principal ideal domains: 1) rational integers; 2) Gaussian integers; 3) Eisenstein integers; and 4) Hurwitz quaternions. Among all lattice index codes constructed using any densest lattice of a given dimension, our codes achieve the maximum side information gain. Finally, using an example, we illustrate how the proposed lattice index codes can benefit Gaussian broadcast channels with more general message demands.

While the impact of finite-rate feedback on the capacity of fading channels has been extensively studied in the literature, not much attention has been paid to this problem under secrecy constraint. In this work, we study the ergodic secret capacity of a multiple-input multiple-output multiple-antenna-eavesdropper (MIMOME) wiretap channel with quantized channel state information (CSI) at the transmitter and perfect CSI at the legitimate receiver, under the assumption that only the statistics of eavesdropper CSI is known at the transmitter. We refine the analysis of Lin et al.'s random vector quantization (RVQ) based artificial noise (AN) scheme, where a heuristic upper bound on the secrecy rate loss (compared to the perfect CSI case) was given. We propose a lower bound on the ergodic secrecy capacity. We show that the lower bound and the secrecy capacity with perfect CSI coincide asymptotically as the number of feedback bits and the AN power go to infinity. For practical applications, we propose a very efficient quantization codebook construction method for the two transmit antennas case.

In this paper, we study an uplink Poisson cellular network model, where the BSs and mobiles are located according to two independent Poisson processes with different densities. A Voronoi tessellation is formed based on the locations of BSs, dividing the network plane into cells. Each mobile communicates with the closest BS. Assuming an orthogonal channelised multiple access technique and a random channel reuse scheme, a BS randomly assigns its available channels to the users within its cell in a one-to-one manner. Under this setting, uplink coverage probability in a channel is studied. In addition, we introduce the concept of user spatial blocking, which occurs when a user has no access to any channel due to limited number of channels available in each cell. Approximate expressions for user spatial blocking probability and uplink coverage probability are derived in this paper.

In this work, we propose phase precoding for the compute-and-forward (CoF) protocol. We derive the phase precoded computation rate and show that it is greater than the original computation rate of CoF protocol without precoder. To maximize the phase precoded computation rate, we need to `jointly' find the optimum phase precoding matrix and the corresponding network equation coefficients. This is a mixed integer programming problem where the optimum precoders should be obtained at the transmitters and the network equation coefficients have to be computed at the relays. To solve this problem, we introduce phase precoded CoF with partial feedback. It is a quantized precoding system where the relay jointly computes both a quasi-optimal precoder from a finite codebook and the corresponding network equations. The index of the obtained phase precoder within the codebook will then be fedback to the transmitters. A “deep hole phase precoder” is presented as an example of such a scheme. We further simulate our scheme with a lattice code carved out of the Gosset lattice and show that significant coding gains can be obtained in terms of equation error performance.

While information-theoretic security is stronger than computational security, it has long been considered impractical. In this work, we provide new insights into the design of practical information-theoretic cryptosystems. Firstly, from a theoretical point of view, we give a brief introduction into the existing information theoretic security criteria, such as the notions of Shannon's perfect/ideal secrecy in cryptography, and the concept of strong secrecy in coding theory. Secondly, from a practical point of view, we propose the concept of ideal secrecy outage and define a outage probability. Finally, we show how such probability can be made arbitrarily small in a practical cryptosystem.

In cryptography, a shared secret key is normally mandatory to encrypt the confidential message. In this work, we propose the unshared secret key (USK) cryptosystem. Inspired by the artificial noise (AN) technique, we align a one-time pad (OTP) secret key within the null space of a multiple-output multiple-input (MIMO) channel between transmitter and legitimate receiver, so that the OTP is not needed by the legitimate receiver to decipher, while it is fully affecting the eavesdropper's ability to decipher the confidential message. We show that the USK cryptosystem guarantees Shannon's ideal secrecy and perfect secrecy, if an infinite lattice input alphabet is used.

We consider a new variant of successive cancellation decoder (SCD) for polar codes based on the concept of folding, which was proposed in [1], [2] as technique to reduce the decoding latency at the cost of a higher computational complexity. In this paper, we first formally define the multiple folding operation (iterated κ times), which decomposes the original encoding graph into a number of smaller polar encoding graphs. More specifically, we show that the multiple folding gives rise to a two stage interpretation of the graph representing the polar encoder and the SCD. Based on this, we propose the improved multiple folded successive cancellation decoder (IMFSCD), which combines SCD in one stage and maximum-likelihood decoding in the other. This decoder exhibits a latency gain by a factor of 2κ, still retaining a complexity close to the classic SCD. The small increase in complexity is due to a short maximum likelihood decoder (MLD) used in place of a SCD in the last decoding stage within the IMFSCD. Moreover, we observe by simulation that the decoder performance is exactly the same as that of an SCD at all rates.

Current security techniques can be implemented with either secret key exchange or physical-layer wiretap codes. In this paper, we investigate an alternative solution for MIMO wiretap channels. Inspired by the artificial noise (AN) technique, we propose the unshared secret key (USK) cryptosystem, where the AN is redesigned as a one-time pad secret key aligned within the null space between a transmitter and a legitimate receiver. The proposed USK cryptosystem is a new physical-layer cryptographic scheme, which was obtained by combining traditional network-layer cryptography and physical-layer security. Unlike previously studied AN techniques, rather than ensuring nonzero secrecy capacity, the USK is valid for an infinite lattice input alphabet and guarantees Shannon's ideal secrecy and perfect secrecy without the need for secret key exchange. We then show how ideal secrecy can be obtained for finite lattice constellations with an arbitrarily small outage.

In this paper, we present a subcarrier pairing scheme to improve the overall error performance of self-heterodyne (self-het) OFDM communications. The proposed pairing scheme exploits the average signal-to-interference-to noise ratios (SINRs) imbalance experienced among self-het OFDM subcarriers. At the transmitter, two simple operations, symbol constellation rotation and component interleaving, are performed before pairing the good and the bad OFDM subcarriers, and maximum likelihood detection is used at the receiver to decode the information. The simulation results show that the proposed pairing scheme improves the system performance by 2.5 dB and 0.6 dB for Rayleigh fading and AWGN channels at bit error rate (BER) of 10-3, respectively, without any coding overhead. In addition, we show that, in the presence of phase noise, self-het OFDM using the proposed pairing scheme outperforms the conventional OFDM schemes with superheterodyne receiver structures.

Self-heterodyne OFDM (self-het OFDM) is known to provide complete immunity against frequency-offset and phase noise, with a much lower RF frontend complexity, when compared to conventional OFDM techniques. Self-het OFDM is considered to be a promising physical layer technology for millimeter-wave RF communications, where the implementation of low complexity stable oscillators is technically difficult. Although self-het OFDM has great potential, it has only been studied for additive white Gaussian noise and two-ray channel models. In this paper, we analyze the performance of self-het OFDM for general frequency selective channels and show that the standard self-het OFDM undergoes an outage if the RF carrier is affected by deep fading. In order to avoid this, we introduce a new technique called smart carrier positioning. We show both analytically and by simulation that the smart carrier positioning can improve the diversity order and the performance of standard self-het OFDM by approximately 4dB at bit error rate of 10^{-2}. In addition, we investigate the optimum power allocation between the carrier and the OFDM subcarriers under frequency selective conditions.

Unipolar communications systems can transmit information using only real and positive signals. This includes a variety of physical channels ranging from optical (fiber or free-space), to RF wireless using amplitude modulation with non-coherent reception, to baseband single wire communications. Unipolar OFDM techniques can efficiently compensate frequency selective channel distortion in unipolar communication systems. One of the leading example of unipolar OFDM is asymmetric clipped optical OFDM (ACO-OFDM) originally proposed for optical communications. Flip-OFDM is an alternative approach that was proposed in a patent, but its performance and full potentials have never been investigated in the literature. In this paper, we first compare Flip-OFDM and ACO-OFDM, and show that both techniques have the same performance but different complexities. In particular, Flip-OFDM offers 50% saving in hardware complexity at the receiver over ACO-OFDM. We then propose a new detection scheme, which enables to reduce the noise at the Flip-OFDM receiver by almost 3dB. The analytical performance of the noise filtering schemes is supported by the simulation results.

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 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.

We consider two uniploar OFDM techniques for optical wireless communications: asymmetric clipped optical OFDM (ACO-OFDM) and Flip-OFDM. Both techniques can be used to compensate multipath distortion effects in optical wireless channels. However, ACO-OFDM has been widely studied in the literature, while the performance of Flip-OFDM has never been investigated. In this paper, we conduct the performance analysis of Flip-OFDM and propose additional modification to the original scheme in order to compare the performance of both techniques. Finally, it is shown by simulation that both techniques have the same performance but different hardware complexities. In particular, for slow fading channels, Flip-OFDM offers 50% saving in hardware complexity over ACO-OFDM at the receiver.

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.

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.

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.

We focus on full-rate, fast-decodable space-time block codes (STBCs) for 2 times 2 and 4times2 multiple-input multiple-output (MIMO) transmission. We first derive conditions and design criteria for reduced-complexity maximum-likelihood (ML) decodable 2times2 STBCs, and we apply them to two families of codes that were recently discovered. Next, we derive a novel reduced-complexity 4times2 STBC, and show that it outperforms all previously known codes with certain constellations.

The Golden space-time trellis coded modulation (GST-TCM) scheme was proposed for a high rate 2 times 2 multiple-input multiple-output (MIMO) system over slow fading channels. In this letter, we present the performance analysis of GST-TCM over block fading channels, where the channel matrix is constant over a fraction of the codeword length and varies from one fraction to another, independently. In practice, it is not useful to design such codes for specific block fading channel parameters and a robust solution is preferable. We then show both analytically and by simulation that the GST-TCM designed for slow fading channels are indeed robust to all block fading channel conditions.

In this paper, we first present a modified code-spread code-division multiple-access (CS-CDMA) scheme, named phase-scrambling CDMA (PS-CDMA), for a Gaussian multiple access channel (MAC). In PS-CDMA, we realize the code-spreading using a low-rate serially concatenated code consisting of a convolutional code and a repetition code. Then, we use complex user-specific algebraic-phase scrambling sequences to distinguish users. The receiver is based on the iterative multiuser decoding suggested in [5,8]. Next, we design complex algebraic phase scrambling sequences to mitigate multiple access interferences for overloaded PS-CDMA, i.e., the number of users is greater than the spreading factor. By analyzing extrinsic information transfer (EXIT) curves and the trajectories, we demonstrate that PS-CDMA using the proposed scrambling sequences has faster iterative decoding convergency and better system performance, when compared to the PS-CDMA using random-phase scrambling sequences and some previously known multiple access schemes.

In this paper, we consider multiuser space-time block codes (STBCs) for 2times2 multiple-input multiple-output (MIMO) uplink transmissions. Using a truncated union-bound (UB) approximation, we propose design criteria of multiuser STBCs for quasi-static fading MIMO multiple access channels (MACs). Next, we demonstrate how, by combining the structure of algebraic perfect STBCs in [10], a family of multiuser STBCs can be constructed to fulfill the design criteria, and show that the proposed STBC outperforms all previously known codes over quasi-static fading MIMO MACs.

Golden space-time trellis coded modulation (GST-TCM) scheme was proposed in [1] for a high rate 2times2 multiple- input multiple-output (MIMO) system over slow fading channels. In this paper, we present the design criteria of GST-TCM over general block fading channels, where the channel matrix is constant over a fraction of the codeword length and varies from one fraction to another independently. However, the code construction and optimization can be difficult to implement. We therefore analyze the performance of GST-TCM for slow fading over block fading channels. The impact of the block fading channel on the code performance is analyzed using a truncated Union Bound technique. We finally show both analytically and by simulation that the GST-TCM designed for slow fading channels are indeed robust to various channel conditions. This feature is particularly useful for transmission over multipath channels using multicarrier modulation such as OFDM.

In this paper, we present a multidimensional trellis coded modulation scheme for a high rate 2times2 multiple-input multiple-output (MIMO) system over slow fading channels. Set partitioning of the Golden code is designed specifically to increase the minimum determinant. The branches of the outer trellis code are labeled with these partitions and Viterbi algorithm is applied for trellis decoding. In order to compute the branch metrics, a sphere decoder is used. The general framework for code design and optimization is given. Performance of the proposed scheme is evaluated by simulation and it is shown that it achieves significant performance gains over the uncoded Golden code

In this paper, we consider the downlink of a space time block coded multiuser multiple-input multiple-output (MIMO) system. We propose a transmission scheme to support highest possible data rate and full diversity for multiuser MIMO systems. For this, threaded algebraic space-time block codes and perfect space-time block codes are employed. Different spreading matrices are used to separate the data streams of multiple users. After despreading the signal sequence at the receiver of each user, the maximum likelihood decoding is obtained by a lattice decoder. Performance of the multiuser MIMO system in the presence of multiple access interference is evaluated by simulations in terms of block error rate

New space-time trellis codes with 4-PSK and 8-PSK for two transmit antennas in slow fading channels are proposed in this paper. The codes are designed specifically to minimize the frame error probability. The performance of the proposed codes with various memory orders and receive antennas is evaluated by simulation. It is shown that the proposed codes outperform previously known codes1.

For coded multiple-input multiple-output spatial multiplexing (MIMO-SM) systems, the iterative receiver consisting of the MIMO detector and decoding can provide near optimal performance. While the sphere detection (SD) technique can be employed to implement the MIMO maximum likelihood (ML) detection with a lower complexity, some modifications of the SD have been proposed to provide a soft-decision for iterative receivers. In the paper, we propose an alternative approach that is based on a quadratic cost function to find the maximum a-posteriori (MAP) solution for the MIMO detection. Using the proposed approach, the MAP detection with the soft-decision can be straightforwardly implemented by the SD technique. Compared to the existing approach, in the new scheme, the soft-decision is well defined and it avoids a numerical instability in computing a soft-decision (which is an approximation of the log likelihood ratio (LLR)). Through simulation results, it is shown that the performance of the proposed scheme is comparable to that of the existing approach.

This paper proposes an approach for the soft-decision in the coded multiple-input multiple-output (MIMO) iterative receiver. A quadratic cost function approximation for the maximum a-posteriori (MAP) detection is considered to apply the computationally efficient sphere decoding (SD) method and a numerically stable approach for the soft-decision is proposed.

We derive the performance union bound of space-time trellis codes in orthogonal frequency division multiplexing system (STTC-OFDM) over quasistatic frequency selective fading channels based on the distance spectrum technique. The distance spectrum is the enumeration of the codeword difference measures and their multiplicities by exhausted searching through all the possible error event paths. Exhaustive search approach can be used for low memory order STTC with small frame size. However with moderate memory order STTC and moderate frame size the computational cost of exhaustive search increases exponentially, and may become impractical for high memory order STTCs. This requires advanced computational techniques such as genetic algorithms (GAs). A GA with sharing function method is used to locate the multiple solutions of the distance spectrum for high memory order STTCs. Simulation evaluates the performance union bound and the complexity comparison of nonGA aided and GA aided distance spectrum techniques. It shows that the union bound give a close performance measure at high signal-to-noise ratio (SNR). It also shows that GA sharing function method based distance spectrum technique requires much less computational time as compared with exhaustive search approach but with satisfactory accuracy.

This paper proposes the code design criteria for robust space-time trellis codes (STTCs) in orthogonal frequency division multiplexing (OFDM) systems over quasi-static frequency selective fading channels. The code design criteria consider the channels with multiple uncorrelated taps and various channel delay distributions such that the robust code performance over various channel conditions can be guaranteed. Based on the code design criteria, new 4, 8, and 16-state 4-PSK STTCs are constructed. Simulation shows that the new codes achieve the robust code performance over various quasi-static frequency selective fading channels.