This paper proposes a new approach for the joint processing of signal detection and channel estimation based on the expectation-maximization (EM) algorithm in orthogonal frequency division multiplexing (OFDM) mobile communications. Conventional schemes based on the EM algorithm estimate a channel impulse response using Kalman filter, and employ the random walk model or the first-order autoregressive (AR) model to derive the process equation for the filter. Since these models assume that the time-variation of the impulse response is white noise without considering any autocorrelation property, the accuracy of the channel estimation deteriorates under fast-fading conditions, resulting in an increased packet error rate (PER). To improve the accuracy of the estimation of fast-fading channels, the proposed scheme employs a differential model that allows the correlated time-variation to be considered by introducing the first- and higher-order time differentials of the channel impulse response. In addition, this paper derives a forward recursive form of the channel estimation along both the frequency and time axes in order to reduce the computational complexity. Computer simulations of channels under fast multipath fading conditions demonstrate that the proposed method is superior in PER to the conventional schemes that employ the random walk model.

This paper proposes a new correction technique for a linear amplification with nonlinear components (LINC) transmitter. The technique, which is based on the minimum mean squared error (MMSE) criterion, estimates the gain and phase imbalance between the two amplifier branches. With information on the estimation, the imbalance is offset by controlling the amplitude and phase of the input signal that is fed into one of the two amplifiers. Computer simulations with a DS-CDMA system demonstrate that this method can compensate for the imbalance and sufficiently suppress the out-of-band distortion spectrum.

This paper proposes an iterative maximum a posteriori probability (MAP) receiver for multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) mobile communications. For exploiting the space, time, and frequency diversity, the low-density parity-check code (LDPC) is used as a channel coding with a built-in interleaver. The receiver employs the expectation maximization (EM) algorithm so as to perform the MAP symbol detection with reasonable computational complexity. The minimum mean square error (MMSE), recursive least squares (RLS), and least mean square (LMS) algorithms are theoretically derived for the channel estimation within this framework. Furthermore, the proposed receiver performs a new scheme called backward symbol detection (BSD), in which the signal detection uses the channel impulse response that is estimated one OFDM symbol later. The advantage of BSD, which is explained from the viewpoint of the message passing algorithm, is that BSD can exploit information on the both precedent and subsequent OFDM symbols, similarly to RLS with smoothing and removing (SR-RLS) [25]. In comparison with SR-RLS, BSD reduces the complexity at the cost of packet error rate (PER) performance. Computer simulations show that the receiver employing RLS for the channel estimation outperforms the ones employing MMSE or LMS, and that BSD can improve the PER performance of the ones employing RLS or LMS.

In communication systems such as mobile telecommunication systems and the Internet, resource sharing among coexisting real-time and non-real-time services is extremely important to provide multimedia services. This paper analytically investigates the performance of the packet data control algorithm proposed in. This algorithm efficiently uses radio resources by utilizing the remaining capacity that is not used by real-time services. The state probability vectors and transition probability matrices of both the real-time and non-real-time services are first derived and then the delay characteristics, the outage probability of voice users, and the outage probability of data users are evaluated. A performance analysis with high bit-rate non-real-time services is also presented.

This paper proposes an iterative maximum a posteriori (MAP) receiver for orthogonal frequency division multiplexing (OFDM) mobile communications under fast-fading conditions. The previous work in [21] developed a MAP receiver based on the expectation-maximization (EM) algorithm employing the differential model, which can allow correlated time-variation of channel impulse responses. In order to make such a MAP receiver more robust against time-variant channels, this paper proposes two new message-passing algorithms derived from factor graphs; subcarrier removal and partial turbo processing. The subcarrier removal estimates the channel frequency response by using all subcarriers other than the targeted subcarrier. Such channel estimate can be efficiently calculated by removing information on the targeted subcarrier from the estimate of the original EM algorithm that uses all the subcarriers. This modification can avoid the repetitive use of incorrectly detected signals for the channel estimation. On the other hand, the partial turbo processing performs symbol-by-symbol channel decoding by using a symbol interleaver. Owing to this process, the current channel estimate, which is more accurate due to the decoding gain, can be used as the initial channel estimate for the next symbol. Computer simulations under fast multipath fading conditions demonstrate that the subcarrier removal and the partial turbo processing can improve the error floor and the convergence speed, respectively, compared to the conventional MAP receiver.

This paper applies iterative multiuser detection employing a new channel estimation scheme to multicarrier interleave-division multiple access (MC-IDMA), called OFDM-IDMA, which is expected to offer improved spectral efficiency in mobile communications. The MC-IDMA transmitter uses both a low-rate channel code and an individual chip interleaver for each user. The MC-IDMA receiver, which this paper focuses upon, repeats the iterative multiuser detection and soft decision-directed channel estimation (SDCE) by exploiting log-likelihood ratios (LLRs) of the coded bits which the maximum a posteriori (MAP)-based channel decoders for all users provide. SDCE estimates channel impulse responses of all users by the least-mean-square (LMS) algorithm, which aims to minimize the mean squared error between the received signal and its replica. This paper investigates the performance of MC-IDMA employing SDCE and compares it with those of three MC-CDMA techniques. Computer simulations demonstrate that MC-IDMA employing SDCE outperforms time-spread MC-CDMA and frequency-spread MC-CDMA, and that it can achieve almost the same bit error rate performance as chip-interleaved MC-CDMA while requiring lower complexity.

This paper proposes a MIMO-OFDM precoder that can minimize a BER upper bound of the maximum likelihood detector (MLD) under a non-cooperative downlink multicell co-channel interference (CCI) environment. Since there is no cooperation among base stations (BSs), it is assumed that information on the interference can be estimated at a mobile station (MS) and then fed back to the desired BS for the precoder. The proposed scheme controls its precoding parameters under a transmit power constraint so as to minimize the BER upper bound, which is derived from the pairwise error probability (PEP) averaged with respect to CCI plus noise. Computer simulations demonstrate that the proposed precoder can effectively improve BER performance of cell edge users and is superior in terms of BER to the eigenmode and the minimum mean squared error (MMSE) precoded transmissions which aim to maximize the channel capacity and to minimize MSE, respectively.

This paper proposes a multipacket-per-slot reservation-based random access protocol with multiuser detection (MD) and automatic repeat request (ARQ), called MPRMD, and analyzes its performance by computer simulations. In MPRMD, before data packet (DP) transmission, a user terminal (UT) transmits a small access request packet (AP) that is composed of an orthogonal preamble sequence and a UT identifier (UT-ID) in a randomly selected minislot during a short dedicated period. Even when several APs collide, a base station (BS) distinguishes them by matched filtering against the preamble part and then extracts the UT-IDs after separating each AP by MD. If the APs are not successfully detected, a small number of minislots are additionally arranged to retransmit them. Thus, by using MD under AP crowded conditions, BS can maximally detect the access requests in a short period, which results in reducing the overhead. Furthermore, in the assignment of a slot, BS intentionally assigns one slot to multiple UTs in order to enhance the efficiency and separates UT's DPs by MD. Since MPRMD can detect a multitude of access requests by utilizing MD in the short period and efficiently assign the slot to separable DPs by MD, it can enhance the system throughput. Computer simulations are conducted to demonstrate the effectiveness of MPRMD. It is shown that the maximum throughputs of MPRMD with the average SNR of 30dB reach 1.4 and 1.7 packets/slot when a data packet is 10 times and 50 times as long as a control packet, respectively.

Joint signal detection and channel estimation based on the expectation-maximization (EM) algorithm has been investigated for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) mobile communications over fast-fading channels. The previous work in [20] developed a channel estimation method suitable for the EM-based iterative receiver. However, it remained possible for unreliable received signals to be repetitively used during the iterative process. In order to improve the EM-based iterative receiver further, this paper proposes spatial removal from the perspective of a message-passing algorithm on factor graphs. The spatial removal performs the channel estimation of a targeted antenna by using detected signals that are obtained from the received signals of all antennas other than the targeted antenna. It can avoid the repetitive use of unreliable received signals for consecutive signal detection and channel estimation. Appropriate applications of the spatial removal are also discussed to exploit both the removal effect and the spatial diversity. Computer simulations under fast-fading conditions demonstrate that the appropriate applications of the spatial removal can improve the packet error rate (PER) of the EM-based receiver thanks to both the removal effect and the spatial diversity.

This paper proposes a new parameter estimation method for the MIMO-OFDM MAP receiver with spatial-temporal filters. The proposed method employs eigenvalue decomposition (EVD) so as to attain precise estimates especially under interference-limited conditions in MIMO-OFDM mobile communications. Recursive EVD is introduced to reduce the computational complexity compared to the nonrecursive EVD. The spatial-temporal prewhitening is placed prior to FFT because this arrangement is superior to that of conventional prewhitening posterior to FFT in accuracy of the parameter estimation. In order to improve tracking capability to fast fading, the proposed scheme applies a decision-directed algorithm to the parameter estimation by using log-likelihood ratios of coded bits. Computer simulations demonstrate that the proposed scheme can track fast fading and reduce the complexity to 18 percents of the conventional one, and that the spatial-temporal filtering prior to FFT outperforms the conventional one posterior to FFT.

This paper proposes a novel MIMO system that introduces a heterogeneous stream (HTS) scheme and a blind signal detection method for mobile radio communications. The HTS scheme utilizes different modulation or coding methods for different MIMO streams, and the blind detection method requires no training sequences for signal separation, detection, and channel estimation. The HTS scheme can remove the ambiguity in identifying separated streams without unique words that are necessary in conventional MIMO blind detection. More specifically, two examples of HTS are considered: modulation type HTS (MHTS) and timing-offset type HTS (THTS). MHTS, which utilizes different modulation constellations with the same bandwidth for different streams, has been previously investigated. This paper proposes THTS which utilizes different transmission timing with the same modulation. THTS can make the blind detection more robust and effective with fractional sampling. The blind joint processing of detection and channel estimation performs adaptive blind MIMO-MLSE and is derived from an adaptive blind MLSE equalizer that employs the recursive channel estimation with the Moore-Penrose generalized inverse. Computer simulations show that the proposed system can achieve superior BER performance with Eb/N0 degradation of 1 dB in THTS and 2.5 dB in MHTS compared with the ideal maximum likelihood detection.

Non-orthogonal multiple access (NOMA) is a promising multiple access scheme for further improving the spectrum efficiency compared to orthogonal multiple access (OMA) in the 5th Generation (5G) mobile communication systems. As inter-user interference cancellers for NOMA, two kinds of receiver structures are considered. One is the reduced complexity-maximum likelihood receiver (R-ML) and the other is the codeword level interference canceller (CWIC). In this paper, we show that the R-ML is superior to the CWIC in terms of scheduling flexibility. In addition, we propose a link to system (L2S) mapping scheme for the R-ML to conduct a system level evaluation, and show that the proposed scheme accurately predicts the block error rate (BLER) performance of the R-ML. The proposed L2S mapping scheme also demonstrates that the system level throughput performance of the R-ML is higher than that for the CWIC thanks to the scheduling flexibility.

OFDM transmission performance in mobile communications suffers severe degradation caused by multipath delay difference greater than the Guard Interval (GI). This is because the excess delay results in considerable Inter-Symbol Interference (ISI) between temporally adjacent symbols and Inter-Carrier Interference (ICI) among subcarriers in the same symbol. This paper proposes a robust OFDM receiver for the scattered pilot OFDM signal that can effectively suppress both ISI and ICI by using two types of equalization and a smoothed FFT-window. In order to verify the performance of the proposed receiver, computer simulations are conducted in accordance with the scattered pilot OFDM signal format of the Digital Terrestrial Television Broadcasting (DTTB). The simulation results demonstrate that the proposed receiver shows much better performance than the conventional receiver in multipath fading environments with the delay difference greater than GI duration.

This paper proposes a new blind adaptive MLSE equalizer for frequency selective mobile radio channels. The proposed equalizer performs channel estimation for each survivor path of the Viterbi algorithm (VA), and restricts the number of symbol candidates for the channel estimation in order to reduce prohibitive complexity. In such channel estimation, autocorrelation matrices of the symbol candidates are likely to become singular, which increases the estimation error. To cope with the singularity, the proposed equalizer employs a recursive channel estimation algorithm using the Moore-Penrose generalized inverse of the autocorrelation matrix. As another problem, the blind channel estimation can yield plural optimal estimates of a channel impulse response, and the ambiguity of the estimates degrades the BER performance. To avoid this ambiguity, the proposed equalizer is enhanced so that it can take advantage of the fractional sampling. The enhanced equalizer performs symbol-spaced channel estimation for each fractional sampling phase. This equalizer combines separate channel estimation errors, and provides the sum to the VA processor as the branch metric, which tremendously reduces the probability that a correct estimate turns into a false one. Computer simulation demonstrates the effectiveness of the proposed equalizers in the frequency selective fading channels.

This paper proposes an OFDM mobile radio packet system that employs a new protocol of automatic repeat request (ARQ) for nonlinear multiuser detection (MUD) with log likelihood ratio combining (LC) on the appropriate bits. The conventional metric combining (MC) MUD separates collided packets by using nonlinear MUD, accumulates the Euclidian distance metrics of the received subcarrier symbols in the packets, and then achieves throughput improvement. However, when MC-MUD detects a packet error, it makes user terminals retransmit the same packets so as to reproduce the collision of the same packets. The proposed LC-MUD scheme simplifies the ARQ protocol and requires no reproduction of the same packet collision. The computer simulations demonstrate the superior throughput of LC-MUD to that of MC-MUD, and further improvement due to adaptive modulation and coding (AMC) optimized for the nonlinear MUD in LC-MUD.

This paper proposes a new blind algorithm effective for multiuser detection with an adaptive array antenna. The conventional blind algorithm, known as the Constant Modulus Algorithm (CMA), has two major drawbacks: (i) the convergence speed is not sufficiently fast for usual applications in mobile communications, and (ii) the algorithm is very likely to lock on the path with the largest received power, which means the signal with the second largest power can hardly be extracted. This paper introduces the Recursive Least Squares algorithm for CMA (RLS-CMA) in order to speed the convergence up, and additionally introduces the concept of the orthogonal projection into CMA so as to extract signals with weak power. The proposed CMA with Orthogonal Projection (CMA-OP) sequentially calculates the weight vector of each user under a constraint that the weight vector should be orthogonal to the estimated array response vectors of previously extracted users. Computer simulations demonstrate that the proposed scheme can operate properly in the Rayleigh fading channels under the two-user condition.

This paper proposes a precoding scheme for downlink multiuser MIMO-OFDM systems. The proposed precoding employs the minimum average bit error rate (MABER) criterion, and obtains precoding matrices by the steepest descent algorithm in order to minimize average BER of mobile stations. As the cost function of the proposed scheme, an upper bound of the average BER is derived from the pairwise error probability (PEP) and is averaged with respect to channel state information (CSI) errors. Thus, the MABER scheme is robust against imperfect CSI. Computer simulations under a frequency-selective fading condition demonstrate that the proposed precoder is more robust against the CSI errors than both the zero-forcing (ZF) precoder and a robust sum mean square error (SMSE) precoder, and that it is superior in BER to the conventional schemes.

In a network with dense deployment of multiple-input multiple-output (MIMO) small cells, coverage overlap between the small cells produces intercell-interference, which degrades system capacity. This paper proposes an intercell-interference management (IIM) scheme that aims to maximize system capacity by using both power control for intercell-interference coordination (ICIC) on the transmitter side and interference cancellation (IC) on the receiver side. The power control determines transmit power levels at the base stations (BSs) by employing a neural network (NN) algorithm over the backhaul. To further improve the signal to interference plus noise ratio (SINR), every user terminal (UT) employs a multiuser detector (MUD) as IC. The MUD detects not only the desired signals, but also some interfering signals to be cancelled from received signals. The receiver structure consists of branch metric generators (BMGs) and MUD. BMGs suppress residual interference and noise in the received signals by whitening matched filters (WMFs), and then generate metrices by using the WMFs' outputs and symbol candidates that the MUD provides. On the basis of the metrices, the MUD detects both the selected interfering signals and the desired signals. In addition, the MUD determines which interfering signals are detected by an SINR based replica selection algorithm. Computer simulations demonstrate that the SINR based replica selection algorithm, which is combined with channel encoders and packet interleavers, can significantly improve the system bit error rate (BER) and that combining IC at the receiver with NN power control at the transmitter can considerably increase the system capacity. Furthermore, it is shown that choosing the detected interfering signals by the replica selection algorithm can obtain system capacity with comparable loss and less computational complexity compared to the conventional greedy algorithm.

This paper proposes low-complexity blind detection for orthogonal frequency division multiplexing (OFDM) systems with the differential space-time block code (DSTBC) under time-varying frequency-selective Rayleigh fading. The detector employs the maximum likelihood sequence estimation (MLSE) in cooperation with the blind linear prediction (BLP), of which prediction coefficients are determined by the method of Lagrange multipliers. Interpolation of channel frequency responses is also applied to the detector in order to reduce the complexity. A complexity analysis and computer simulations demonstrate that the proposed detector can reduce the complexity to about a half, and that the complexity reduction causes only a loss of 1 dB in average Eb/N0 at BER of 10-3 when the prediction order and the degree of polynomial approximation are 2 and 1, respectively.

This paper proposes a low-complexity signal detection algorithm for spatially correlated multiple-input multiple-output (MIMO) channels. The proposed algorithm sets a minimum mean-square error (MMSE) detection result to the starting point, and searches for signal candidates in multi-dimensions of the noise enhancement from which the MMSE detection suffers. The multi-dimensional search is needed because the number of dominant directions of the noise enhancement is likely to be more than one over the correlated MIMO channels. To reduce the computational complexity of the multi-dimensional search, the proposed algorithm limits the number of signal candidates to O(NT) where NT is the number of transmit antennas and O( ) is big O notation. Specifically, the signal candidates, which are unquantized, are obtained as the solution of a minimization problem under a constraint that a stream of the candidates should be equal to a constellation point. Finally, the detected signal is selected from hard decisions of both the MMSE detection result and unquantized signal candidates on the basis of the log likelihood function. For reducing the complexity of this process, the proposed algorithm decreases the number of calculations of the log likelihood functions for the quantized signal candidates. Computer simulations under a correlated MIMO channel condition demonstrate that the proposed scheme provides an excellent trade-off between BER performance and complexity, and that it is superior to conventional one-dimensional search algorithms in BER performance while requiring less complexity than the conventional algorithms.