This paper proposes a statistical-eigenmode spacedivision multiple-access (SE-SDMA) transmission for a two-user downlink system where two transmit antennas are equipped at the base station and each mobile user has one receive antenna, assuming that only statistical channel state information (CSI) is available at the transmitter. By maximizing a lower bound of the ergodic signal-to-leakage-and-noise ratio, the proposed SE-SDMA approach selects two users with orthogonal principal statistical eigen-directions and transmits to each user along the corresponding eigenmode. We derive an exact expression of the ergodic achievable rate, and compare it with the zero-forcing beamforming (ZFBF) system exploiting instantaneous CSI. It is shown that SE-SDMA can achieve the maximum ergodic sum-rate of the two selected users, and provide significant user selection gain. Analytical and simulation results show that the rate gap between SE-SDMA and ZFBF with perfect CSI at the transmitter can tend to zero in highly correlated channels, which indicates that statistical precoding can be used instead of instantaneous precoding in certain environments.

In practical downlink multiuser MIMO channels, users' channels are non-orthogonal, which results in inter-user interference and in turn degrades system performance. In this paper, a new subspace-domain linear transmit preprocessing technique is proposed in enhancing users' spatial separation and suppressing inter-user interference. We show by simulations that sum rate is significantly improved and its saturation is avoided.

We perform a minimum distance analysis of a class of two-dimensional intersymbol interference (ISI) channels applicable to multitrack magnetic recording and orthogonal frequency division multiplex transmission systems. Exact minimum distance for a wide class of ISI responses is derived. The fundamental analytical technique is to transform the channel into an equivalent minimum phase channel. The results improve upon the prior work of Soljanin and Georghiades.

Single-carrier frequency division multiple access (SC-FDMA) has appeared to be a promising technique for high data rate uplink communications. Aimed at SC-FDMA applications, a cyclic prefixed version of the offset quadrature amplitude modulation based OFDM (OQAM-OFDM) is first proposed in this paper. We show that cyclic prefixed OQAM-OFDM (CP-OQAM-OFDM) can be realized within the framework of the standard OFDM system, and perfect recovery condition in the ideal channel is derived. We then apply CP-OQAM-OFDM to SC-FDMA transmission in frequency selective fading channels. Signal model and joint widely linear minimum mean square error (WLMMSE) equalization using a prior information with low complexity are developed. Compared with the existing DFTS-OFDM based SC-FDMA, the proposed SC-FDMA can significantly reduce envelope fluctuation (EF) of the transmitted signal while maintaining the bandwidth efficiency. The inherent structure of CP-OQAM-OFDM enables low-complexity joint equalization in the frequency domain to combat both the multiple access interference and the intersymbol interference. The joint WLMMSE equalization using a prior information guarantees optimal MMSE performance and supports Turbo receiver for improved bit error rate (BER) perform BER) performance. Simulation results confirm the effectiveness of the proposed SC-FDMA in terms of EF (including peak-to-average power ratio, instantaneous-to-average power ratio and cubic metric) and BER performances.

Zero-IF architecture is a competitive alternative to the conventional super-heterodyne architecture for RF-to-baseband conversion in OFDM systems. Despite its advantages of low cost and high integratability, it suffers from the I/Q imbalance that contributes amplitude and phase mismatches between in-phase and quadrature branches, resulting in signal distortion and performance degradation. In this paper, we revisit the problem in a theoretical viewpoint through a minimum distance analysis. In particular, we aim at proving that when the subcarriers are paired symmetrically to a center frequency and the maximum likelihood decoding is employed, the transmitter I/Q imbalance can provide an additional degree of diversity in frequency selective fading channels.

In this paper we perform a minimum distance analysis of a class of two dimensional intersymbol interference channels. In particular, some important cases of multitrack multihead magnetic recording systems fall into the studied class. Previously, Soljanin and Georghiades have studied the same problem as we do. The results derived in this paper are more conclusive and they improve upon theirs. The fundamental proof technique that we will use is to transform the channel into an equivalent minimum phase channel.

In this paper, a novel time-of-arrival estimation algorithm is proposed for impulse radio-based UWB systems in dense multipath environment. In particular, a dedicated ranging sequence with good cross-correlation property is proposed and a threshold-based search-back unit is introduced, with the purpose of supporting high-precision ranging even at low signal-to-noise ratio. An approximate closed-form expression on the optimal threshold is derived based on the Rayleigh statistical analysis, and its accuracy and tightness are verified by simulations. Results show that the proposed ranging scheme achieves an excellent mean absolute error performance in the order of nanoseconds without introducing too much latency.

We propose a joint set of linear precoder designs for single cell uplink multiuser space-time block coded multiple- input multiple-output systems with multi-packet reception by exploiting outdated channel state information. By deriving the pairwise error probability with respect to both minimum and average codeword distance design metrics, we formulate the design as an optimization problem subject to transmit power constraint for each user. Due to the non-convex nature of the optimization problem, we devise an iterative algorithm to solve for linear precoding structure for general space-time block code. For orthogonal space-time block code, we also propose a simplified distributed algorithm to solve for a closed-form solution. Asymptotic analysis on the effect of quality of the outdated channel state information (CSI) on the precoder structure is also presented. Simulation results are provided to demonstrate the effectiveness of the proposed designs for different space-time block codes at various CSI qualities.

This paper analyzes bit error rate (BER) and outage probability of singular value decomposition-based multiple-input multiple-output systems with channel estimation error and feedback delay over uncorrelated Ricean fading channels. By utilizing marginal unordered and ordered eigenvalue distributions of complex noncentral Wishart matrices, we derive exact closed-form expressions on the average system performance and high signal- to-interference-plus-noise ratio (SINR) approximations on the individual eigen-subchannels, respectively, under the assumption of equal power allocation. Our expressions apply for various modulation formats and arbitrary numbers of transmit and receive antennas. Our results show that in low-to-moderate SINR regimes, both the BER and the outage probability increase with channel estimation error, feedback delay and the Ricean K-factor at a polynomial rate that is inversely proportional to the difference between the numbers of transmit and receive antennas. We also show that, with channel estimation error and feedback delay, the diversity orders of the BER and outage probability are zero and an irreducible error floor exists at high SINR.

The input-output weight enumerator of a convolutional code characterizes the distance spectrum and allows error probability bounds to be conveniently evaluated. To efficiently compute the weight enumerator, Pimentel recently introduced the so-called state reduction algorithm which has a convenient implementation using existing symbolic mathematical software. In this paper, we propose a dynamic state elimination ordering heuristic to further accelerate the algorithm. As demonstrated by our empirical results, the accelerated state reduction algorithm can achieve impressive complexity savings relative to the original algorithm when applied to compute the weight enumerators and its various truncated versions of convolutional codes with moderate-to-large constraint lengths.

We address the problem of designing a linear precoder for space-time coded multiple-input multiple-output (MIMO) system with imperfect knowledge of channel state information at the transmitter (CSIT), subject to a total transmit power constraint. Assuming an uncorrelated flat-fading channel and using a maximum likelihood decoder at the receiver, we analytically reveal that the derived precoder is a function of the noise variance, the eigenvalues of the estimated channel matrix and the eigenvalues of the codeword distance matrix. Furthermore, the power allocation on the eigenvalues of the precoder is shown to follow the water-pouring policy and hence the proposed precoder allocates more power to the stronger channels.

This paper analyzes the average bit error rate (BER) performance of singular value decomposition-based multiple-input multiple-output systems with channel estimation error and feedback delay over uncorrelated Ricean fading channels. By utilizing marginal unordered eigenvalue distributions of complex noncentral Wishart matrices, we derive exact closed- form BER expression under the assumption of equal power allocation. Our results apply for various modulation formats and arbitrary numbers of transmit and receive antennas. Our results show the average BER increases with channel estimation error, feedback delay and Ricean A'-factor at a polynomial rate that is inversely proportional to the difference between the numbers of transmit and receive antennas. We also show that the achievable BER performance is limited by the presence of an irreducible error floor as the signal-to-interference-plus-noise ratio increases.

Non-linear amplitude distortion may be the key impairment in some practical multiple-input multiple-output (MIMO) communications systems. However, there are only a few past investigations addressing its impact on the system performance. In this paper, we derive an approximate upper bound on the bit error rate for MIMO zero-forcing receivers with M-ary quadrature amplitude modulation (MQAM) in the presence of channel estimation error, which is valid for any order of non-linearity and arbitrary numbers of transmit and receive antennas. In the absence of channel estimation error, the results derived herein give a true BER upper bound. Comparison with Monte Carlo simulations suggest that the theoretical bound is accurate and useful for practical system design.

Motivated by the fact that combining space-time block codes with channel precoding can make the system robust against channel fading while achieving both coding and diversity gains, we propose a joint set of linear precoder designs for uplink multiuser space-time block coded multiple-input multiple-output systems with multipacket reception by exploiting outdated channel state information. In particular, we formulate the design as an optimization problem of minimizing pairwise error probability subject to transmit power constraint for each user. Due to non-convex nature of the optimization problem, we devise an iterative algorithm to solve for linear precoding structure for general space-time block code. For orthogonal space-time block code, we also propose a simplified distributed algorithm to solve for a closed-form solution. Asymptotic analysis of the effect of channel quality on the precoder structure is also presented. Simulation results are provided to demonstrate the effectiveness of the proposed designs for orthogonal and quasi-orthogonal space-time block codes over the conventional beamforming system.

This paper considers a joint design of linear precoders and equalizers for uplink multiuser multiple-input multiple-output communications systems over uncorrelated flat-fading channels with imperfect channel state information at both the transmitters and the receivers. By minimizing the mean square error (MSE) of all users, or equivalently the sum-MSE, under a sum-power constraint, we model the linear transceiver design as an optimization problem. Instead of relying on complex iterative algorithms, the authors propose a low-complexity, non-iterative but close-to-optimal precoder design solution by relaxing the problem into a simpler convex optimization problem. In this way, a closed-form linear transceiver structure can be derived by using the Karush-Kuhn-Tucker (KKT) optimality conditions. Based on the closed-form solution and random matrix theory, the authors obtain a simple asymptotic expression on the average sum-MSE, which can provide useful design insights.

Link adaptation allows the transmitter to adapt to changing channel conditions. Critical to the design of link adaptation is the accuracy of channel state information at the transmitter. In this paper, we investigate the effect of imperfect channel state information and feedback delay on the performance of a multiple-input multiple-output zero-forcing receiver with adaptive power allocation. A closed-form approximate upper bound on bit error rate is derived for M-ary phase shift keying and M-ary quadrature amplitude modulation and it is valid for arbitrary numbers of transmit and. receive antennas. Comparison with Monte Carlo simulations is also provided, showing that the results derived from this analytical bound are useful for system design.

By employing spatial multiplexing, multiple-input multiple-output (MIMO) wireless antenna systems provide increases in capacity without the need for additional spectrum or power. Zero-forcing (ZF) detection is a simple and effective technique for retrieving multiple transmitted data streams at the receiver. However the detection requires knowledge of the channel state information (CSI) and in practice accurate CSI may not be available. In this letter, we investigate the effect of channel estimation error on the performance of MIMO ZF receivers in uncorrelated Rayleigh flat fading channels. By modeling the estimation error as independent complex Gaussian random variables, tight approximations for both the post-processing SNR distribution and bit error rate (BER) for MIMO ZF receivers with M-QAM and M-PSK modulated signals are derived in closed-form. Numerical results demonstrate the tightness of our analysis

Few works have addressed the effect of CFO (carrier frequency offset) on channel estimation performance. In this paper, compact analytical expressions on the mean square error of channel estimation in the presence of CFO are derived for OFDM (orthogonal frequency division multiplexing) systems employing single and multiple antennas. Concise upper bounds are also derived for SISO-OFDM systems. It is revealed that channel estimation MSE (mean square error) increases at the rate of approximately the square of the CFO and increasing the number of pilots does not contribute to better suppression of the MSE caused by CFO. In addition, it is observed that LMMSE (linear minimum mean square error) channel estimation is more resistant to CFO compared to LS (least square) in terms of channel estimation MSE. Furthermore, from the results derived herein, a clue for the pilot design of OFDM systems with CFO can be obtained

We derive exact closed-form expressions on the bit error rate (BER) for the singular value decomposition (SVD)-based multiple-input multiple-output (MIMO) systems using Mary phase-shift keying (MPSK) and M-ary quadrature amplitude modulation (MQAM), respectively, with optimal detection under the assumptions of equal power allocation and Gaussian distributed cochannel interference. From the expressions derived herein, we investigated the effect of imperfect channel state information (CSI) on the average BER. It can be concluded from our theoretical analysis that the channel estimation error always induces an irreducible error floor and may severely deteriorate the BER performance.

We address the problem of designing a linear precoder for space-time coded multiple-input multiple-output (MIMO) system with partial knowledge of channel state information at the transmitter (CSIT), subject to a total transmit power constraint. Assuming an uncorrelated flat-fading channel and using a maximum-likelihood detector at the receiver, we show that the derived precoder is a function of the noise variance, the eigenvalues of the estimated channel matrix and the eigenvalues of the codeword error matrix. From the results derived herein, it is observed that the power allocation on the eigenvalues of the precoder follows the water-pouring policy. Simulation results are provided to illustrate the significant performance gain achieved by using the proposed precoder even at moderate to large CSIT errors.

In this paper, we first investigate the performance of optimum multi-head multi-track detection systems for the two-dimensional recording channels and compare their performance for various intertrack interference levels in terms of minimum-distance parameters. Then we propose a low-complexity multi-head data detection algorithm for multi-track partial response and two-dimensional recording channels based on the ordered successive interference algorithm but it is different in the way that the detection order is pre-defined according to channel conditions and the data at successive time instants are simultaneously estimated by using group receivers. Compared with the optimal MLSD approach based on the multi-dimensional Viterbi algorithm, the complexity of the proposed algorithm is only linearly proportional to the number of tracks at an expense of small performance degradation

The weight enumerator of a convolutional code is an important function that characterizes the codeword distance distribution and allows the error probability bounds of the code to be conveniently computed. An efficient state reduction algorithm to compute weight enumerators by iteratively modifying the symbolic adjacency matrix associated with the code was recently introduced. In this paper, we propose a dynamic elimination ordering technique that exploits the state diagram structure of the convolutional encoder for improving the efficiency of the state reduction algorithm.

A current-mode binary-search sensing scheme for a 4-state one-transistor one-magnetic tunnel junction (1T1MTJ) magneto-resistive random access memory (MRAM) is proposed. By using the switched-current technique, it is able to read data non-destructively with a magneto-resistive (MR) ratio of as low as 5%. The circuit is designed using a 0.18mm CMOS process and the performance is verified by HSPICE. Compared to the parallel sensing approach, the proposed sensing scheme consumes less power and chip area and requires fewer comparison steps. Compared to the serial sensing approach, it allows a shorter read access time while requiring the same number of comparisons.