In a space-based automatic identification system (AIS), a satellite has a wide coverage area and thus can receive AIS signals from ships in the high seas. However, wide coverage can cause multiple AIS packets to collide with each other at the satellite receiver. Furthermore, transmitted packets are affected by channel parameters, such as Doppler shifts, channel impulse response, and propagation delay time, which are remarkably different in each packet because these parameters depend on the distance and relative speed between ships and the satellite. Therefore, these parameters should be estimated and used for multiuser detection to detect collided packets separately. Nevertheless, when the received power difference between packets or desired to undesired signal power ratio (DUR) is low, the accuracy of the channel parameter estimation is degraded so severely, such that multiuser detection cannot maintain sufficient bit error rate (BER) performance. To compensate for the reduced accuracy, this paper proposes a highly accurate channel estimation method. In addition to the conventional correlation-based channel estimation, the proposed method applies the quasi-Newton and least-squares methods to estimate Doppler frequency and channel impulse response, respectively. Regarding the propagation delay time, the conventional correlation-based channel estimation is repeated for improvement. Multiuser detection based on the Viterbi algorithm is performed using the estimated channel parameters. Computer simulations were conducted under the conditions of two collision packets and Rician fading, and the results show that the proposed method can significantly improve the accuracy of the channel estimation and BER performance than the conventional method.

In unlicensed spectrum, wireless communications employing carrier sense multiple access with collision avoidance (CSMA/CA) suffer from longer transmission delay time as the number of user terminals (UTs) increases, because packet collisions are more likely to occur. To cope with this problem, this paper proposes a new multiuser detection (MUD) scheme that uses both request-to-send (RTS) and enhanced clear-to-send (eCTS) for high-reliable and low-latency wireless communications. As in conventional MUD scheme, the metric-combining MUD (MC-MUD) calculates log likelihood functions called metrics and accumulates the metrics for the maximum likelihood detection (MLD). To avoid increasing the number of states for MLD, MC-MUD forces the relevant UTs to retransmit their packets until all the collided packets are correctly detected, which requires a kind of central control and reduces the system throughput. To overcome these drawbacks, the proposed scheme, which is referred to as cancelling MC-MUD (CMC-MUD), deletes replicas of some of the collided packets from the received signals, once the packets are correctly detected during the retransmission. This cancellation enables new UTs to transmit their packets and then performs MLD without increasing the number of states, which improves the system throughput without increasing the complexity. In addition, the proposed scheme adopts RTS and eCTS. One UT that suffers from packet collision transmits RTS before the retransmission. Then, the corresponding access point (AP) transmits eCTS including addresses of the other UTs, which have experienced the same packet collision. To reproduce the same packet collision, these other UTs transmit their packets once they receive the eCTS. Computer simulations under one AP conditions evaluate an average carrier-to-interference ratio (CIR) range in which the proposed scheme is effective, and clarify that the transmission delay time of the proposed scheme is shorter than that of the conventional schemes. In two APs environments that can cause the hidden terminal problem, it is demonstrated that the proposed scheme achieves shorter transmission delay times than the conventional scheme with RTS and conventional CTS.

Our previous work proposed a semi-blind single antenna interference cancellation scheme to cope with severe inter-cell interference in heterogeneous networks. This paper extends the scheme to allow multiple-receive-antenna implementation. It does not require knowledge of the training sequences of interfering signals and can cancel multiple interfering signals irrespective of the number of receive antennas. The proposed scheme applies an enhanced version of the quantized channel approach to suboptimal joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals, while reducing the computational complexity of optimum JCESD drastically. Different from the previous work, the proposed scheme applies the quantized channel generation and local search at each individual receive antenna so as to estimate transmitted symbol matrices during the training period. Then, joint estimation is newly introduced in order to estimate a channel matrix from the estimated symbol matrices, which operates in the same manner as the expectation maximization (EM) algorithm and considers signals received at all receive antennas. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) during the data period under the maximum likelihood (ML) criterion in order to cancel the interference. Computer simulations with two receive antennas under two-interfering-stream conditions show that the proposed scheme outperforms interference rejection combining (IRC) with perfect channel state information (CSI) and MUD with channels estimated by a conventional scheme based on the generalized Viterbi algorithm, and can achieve almost the same average bit error rate (BER) performance as MUD with channels estimated from sufficiently long training sequences of both the desired stream(s) and the interfering streams, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

In order to cope with severe interference in heterogeneous networks, this paper proposes a semi-blind interference cancellation scheme, which does not require multiple receive antennas or knowledge about training sequences of the interfering signals. The proposed scheme performs joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals. On the other hand, maximum likelihood detection (MLD), which can be considered the optimum JCESD, must perform channel estimation for all transmitted signal candidates of the interfering signals and must search for the most likely signal candidate. Therefore, MLD incurs a prohibitive amount of computational complexity. To reduce such complexity drastically, the proposed scheme enhances the quantized channel approach, and applies the enhanced version to JCESD. In addition, a recalculation scheme is introduced to avoid inaccurate channel estimates due to local minima. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) of the data sequences in order to cancel the interference. Computer simulations show that the proposed scheme outperforms a conventional scheme based on the Viterbi algorithm, and can achieve almost the same average bit error rate performance as the MUD with channels estimated from sufficiently long training sequences of both the desired signal and the interfering signals, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

To suppress intercell interference for three-cell half-duplex relay systems, joint interference suppression and multiuser detection (MUD) schemes that estimate weight coefficients by the recursive least-squares (RLS) algorithm have been proposed but show much worse bit error rate (BER) performance than maximum likelihood detection (MLD). To improve the BER performance, this paper proposes a joint interference suppression and MUD scheme that estimates the weight coefficients by eigenvalue decomposition. The proposed scheme carries the same advantages as the conventional RLS based schemes; it does not need channel state information (CSI) feedback while incurring much less amount of computational complexity than MLD. In addition, it needs to know only two out of three preambles used in the system. Computer simulations of orthogonal frequency-division multiplexing (OFDM) transmission under three-cell and frequency selective fading conditions are conducted. It is shown that the eigendecomposition-based scheme overwhelmingly outperforms the conventional RLS-based scheme although requiring higher computational complexity.

This paper presents an adaptive interference-aware receiver for multiuser multiple-input multiple-output (MU-MIMO) downlink systems in wireless local area network (WLAN) systems. The MU-MIMO downlink technique is one of the key techniques that are newly applied to WLAN systems in order to support a very high throughput. However, the simultaneous communication of several users causes inter-user interference (IUI), which adversely affects receivers. Therefore, in order to prevent IUI, a precoding technique is defined at the transmitter based on feedback from the receiver. Unfortunately, however, the receiver still suffers from interference, because the precoding technique is prone to practical errors from the feedback quantization and subcarrier grouping scheme. Whereas ordinary detection schemes are available to mitigate such interference, such schemes are unsuitable because of their low performance or high computational complexity. In this paper, we propose an switching algorithm based on the norm ratio between an effective channel matrix for the desired signal and that of the interfering signals. Simulation results based on the IEEE 802.11ac standard show that the proposed algorithm can achieve near-optimal performance with a 70% reduction in computational complexity.

A coherent combining-based initial ranging scheme is proposed for multiple-input multiple-output and orthogonal frequency division multiple access systems. The proposed algorithm utilizes the correlation properties of the ranging codes to resolve the multipath components, coherently combines the initial ranging signal of resolved path on each receiving antenna to maximize the output signal-to-interference-and-noise ratio, and then collects the power of the multipath signals to detect the states of the ranging codes. Simulation results show that the proposed scheme has much better performance than the available noncoherent combining method, and can accommodate more active ranging users simultaneously in each cell.

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.

In this letter, a generalized sidelobe canceller (GSC) with robustness against carrier frequency offset (CFO) is proposed for the uplink MC-CDMA system. It has been shown that a CFO will cause the spreading code mismatch and desired signal cancellation. By incorporating the corrected quiescent weight of the upper branch and blocking matrix of the lower branch, we create an efficient GSC that offers strongly counters the effect of the CFO. Significant performance improvement of the proposed GSC is demonstrated by simulation results.

In this paper, we propose a simple, yet effective, multiuser detection scheme for a two-hop cooperative CDMAs. In phase 1, the minimum mean square error (MMSE) detector at the destination is used to identify reliable decisions of direct transmissions from the sources and return them to the relays. Then, in phase 2, based on the reliable decisions, the relays and the destination successively utilize the maximum likelihood (ML) detectors to estimate the residual symbols. Due to the destination estimating the symbols separately from direct transmissions and the relaying signals, as a result the destination does not need the information about the relays' decision performance for the construction of the ML detector. Hence, the proposed scheme is more feasible than existing approaches for practical implementation. In addition, due to the ML detectors in phase 2 only estimating the residual symbols, the number of computations performed by the ML detectors can be reduced significantly. The results of simulations and complexity analysis demonstrate the efficiency and effectiveness of the proposed scheme.

This paper proposes a novel blind multiuser detection scheme using CMA (Constant Modulus Algorithm) adaptive array. In the proposed scheme, the received signal is processed in two steps. In the primary step, only one user is captured by the CMA adaptive array, and at the same time, the other users' directions of arrival (DOA) are estimated. In the secondary step, initial weight vectors are set based on the estimated DOAs, and it processes with CMAs again to capture the other users in parallel. Thus, all the users are detected exactly and recovered separately. The Least-squares CMA is applied as an optimization algorithm to improve the performance of the proposed scheme, and the performances using the proposed scheme with linear arrays and circular arrays are discussed in detail. Simulation results are presented to verify the performance of the proposed scheme.

It is well known that the performance of CDMA systems may degrade in the presence of spreading code mismatch. The diagonal loading multiple constrained minimum variance (DL-MCMV) approaches have been proposed to deal with the mismatch problem. However, they still cannot improve the robust capability efficiently due to the spreading code mismatch. In this letter, a detector based on the variable DL technique is presented that offers more robust capabilities than the MCMV and DL-MCMV detectors. Computer simulation results are provided that illustrate the effectiveness of the proposed detector.

Multicarrier code division multiple access (MC-CDMA) systems are well suited for high data rate wireless multimedia services, due to their ability to convert frequency-selective fading channels to distinct flat fading channels with low complexity fast Fourier transform (FFT) devices. However, when multiple users are present, the performance of MC-CDMA systems is degraded by the multiuser interference (MUI) when the channel is frequency-selective. In order to mitigate MUI, we present a joint algorithm that combines transmit power control, antenna array processing and multiuser detection at the receiver. Interestingly, the frequency-selectivity that entails the MUI also provides multipath diversity which can help suppress the MUI. Performance of the algorithm in a number of MC-CDMA system models is evaluated in terms of the average transmit power to achieve the target signal to interference plus noise ratio (SINR). Simulations confirm the outstanding performance of this algorithm compared with the existing ones in MC-CDMA systems.

In this paper, we propose a novel multiuser detection (MUD) method that is robust against timing offset between wireless terminals (WTs) for the multiuser multiple-input multiple-output (MU-MIMO) orthogonal frequency division multiplexing (OFDM) uplink. In the proposed method, MUD is carried out in the frequency-domain using overlapping fast Fourier transform (FFT) windows. After the inverse FFT (IFFT) operation, the samples obtained at both ends of each FFT window are discarded to suppress the effect of inter-block interference (IBI). Thus, it realizes an MUD regardless of the arrival timing differences of the signals from the WTs. The achievable bit error rate (BER) performance of the proposed MUD method is evaluated by computer simulations in a frequency selective fading channel.

Due to the computational complexity of the optimum maximum likelihood detector (OMD) growing exponentially with the number of users, suboptimum techniques have received significant attention. We have proposed the particle swarm optimization (PSO) for the multiuser detection (MUD) in asynchronous multicarrier code division multiple access (MC-CDMA) system. The performance of PSO based MUD is near optimum, while its computational complexity is far less than OMD. Performance of PSO-MUD has also been shown to be better than that of genetic algorithm based MUD (GA-MUD) at practical SNR.

The computation involved in multiuser detection (MUD) for multicarrier CDMA (MC-CDMA) based on maximum likelihood (ML) principle grows exponentially with the number of users. Particle swarm optimization (PSO) with soft decisions has been proposed to mitigate this problem. The computational complexity of PSO, is comparable with genetic algorithm (GA), but is much less than the optimal ML detector and yet its performance is much better than GA.

Ultra fast switching speed of superconducting digital circuits enable realization of Digital Signal Processors with performance unattainable by any other technology. Based on rapid-single-flux technology (RSFQ) logic, these integrated circuits are capable of delivering high computation capacity up to 30 GOPS on a single processor and very short latency of 0.1 ns. There are two main applications of such hardware for practical telecommunication systems: filters for superconducting ADCs operating with digital RF data and recursive filters at baseband. The later of these allows functions such as multiuser detection for 3G WCDMA, equalization and channel precoding for 4G OFDM MIMO, and general blind detection. The performance gain is an increase in the cell capacity, quality of service, and transmitted data rate. The current status of the development of the RSFQ baseband DSP is discussed. Major components with operating speed of 30 GHz have been developed. Designs, test results, and future development of the complete systems including cryopackaging and CMOS interface are reviewed.

The computational complexity of the optimum maximum likelihood detector (OMLD) does not allow its utility for multi-user detection (MUD) in code division multiple access (CDMA) systems. As proposed in this letter, particle swarm optimization (PSO) with soft decision offers a much more efficient option with few parameters to be adjusted, flexibility to implement, that gives a much faster convergence compared to OMLD. It outperforms the conventional detector, the genetic algorithm approach and the standard suboptimal detectors considered in the literature.

This letter deals with multiuser detection under imprecise knowledge of the received signature codes of all active users for multicarrier code division multiple access (MC-CDMA) systems. The weight vector of the modified multiple constrained minimum variance (MMCMV) is found by projecting the multiple constrained minimum variance (MCMV) weight vector onto a vector subspace constructed from the eigenstructure of the correlation matrix. However, MMCMV still cannot handle the large code-mismatch. Shaping the noise subspace with all estimated active spreading codes, we present an effective approach to achieve more robust capabilities than the MMCMV. Computer simulations show the effectiveness of the proposed detector.

We propose a robust iterative multiuser receiver for decoding convolutional coded code-division multiple access (CDMA) signals in both Gaussian and non-Gaussian channel noise. The receiver is derived from a modified maximum a-posteriori (MAP) algorithm called the max-log-MAP algorithm for robustness against erroneous channel variance estimation. Furthermore, the effect of destructive outliers arising from impulsive noise is mitigated in the proposed receiver by incorporating the robust Huber penalty function into the multiuser detector. The proposed receiver is shown to perform satisfactorily over Gaussian and non-Gaussian impulsive channels. In every iteration, cumulative improvement in the quality of the a-posteriori probabilities is also demonstrated.