A reconfigurable hybrid beamforming (HBF) system is proposed to flexibly exploit the channel diversities and antenna array directivity in millimeter wave channels. Sub-arrays of antennas can be reconfigured in the proposed HBF system to adjust the spatial and polarization diversities and the array gains according to the channel environments and the relative locations between the transmitter and the receiver. Based on the reconfigurable HBF system, a training procedure is also proposed for the transmitter and the receiver to learn the best operating mode according to channel quality and characteristics. Compared to a fixed HBF system, the reconfigurable HBF system has 3 to 10 dB power gains in channel capacity in various simulated channel conditions.

The existing subspace-based channel estimation approach for orthogonal frequency division multiplexing (OFDM) systems with an expanding factor, called the repetition index, suffers from the problem of low probability of full row rank of the signal matrix with few OFDM blocks, which may fail to estimate the channel impulse response (CIR). In this paper, a subspace-based channel estimation algorithm with a two-step signal matrix construction method is proposed. The probability of full row rank of the proposed signal matrix is very close to one even if few OFDM blocks are available. The proposed approach can also be applied to both cyclic prefix (CP)-based and non-CP-based OFDM systems whereas the conventional approach is only suitable for CP-based systems. Simulation results show that the proposed method outperforms related blind channel estimation approaches in terms of normalized mean square error (NMSE).

Subspace-based blind channel estimation for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with repetition index has been proposed in the literature. However, the full-row-rank probability of the signal matrix using the MIMO-based repetition index method is extremely low, especially when low-order modulation or few received OFDM symbols are used. In this paper, the MIMO-based repetition index method with a new signal permutation method is proposed. The proposed method solves the problem of previous MIMO-based repetition index method. Additionally, the proposed method performs well even if low-order modulation or few revived OFDM symbols are applied. Simulation results show that proposed method not only has high full-row-rank probability, but also outperforms conventional blind channel estimation approaches in terms of normalized mean-square error (NMSE).

A subspace-based blind channel estimation algorithm for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed in this paper. The proposed algorithm for MIMO-OFDM systems generalizes the conventional repetition index approach, which is only suitable for single-input single-output (SISO)-OFDM systems. Additionally, the necessary conditions of the proposed algorithm to be full row rank are discussed. Simulation results show that the probability of full row rank of the proposed signal matrix is close to one for different constellation schemes. The proposed generalized approach also outperforms the conventional approach with virtual carriers (VCs) in terms of normalized mean-squared error (NMSE) under static channel environments even if the number of OFDM symbols is small.

Subspace algorithms are commonly used for blind channel estimation in orthogonal frequency-division multiplexing (OFDM) systems as they can establish the relation between the channel impulse response and singular vectors of the noise subspace. However, they are not workable under the conventional cyclic prefix-free OFDM signal model as the corresponding necessary condition of subspace algorithms is not satisfied. To solve this problem, this study proposes two subspace-based blind channel estimation approaches using the real and periodic symbols of time-domain transmitted OFDM blocks. From the simulation results, we can obtain the proposed approaches outperform conventional ones in terms of normalised mean-squared error and bit error rate under time-invariant channel environments.

Orthogonal frequency division multiplexing (OFDM) is a technique widely used for wireless communication applications. All the subcarriers are orthogonal to each other in OFDM systems. However, carrier frequency offset (CFO) may distort the orthogonality of the subcarriers and it must be estimated and compensated to maintain the system performance. A blind carrier frequency offset estimator based on the phase probability density function (pdf) is proposed in this paper. The proposed CFO estimator can operate under additive white Gaussian noise (AWGN) and multipath channels without known training signal, virtual carrier, and redundant guard interval. When compared with subspace-based blind estimators, the proposed estimator can provide better mean-squared-error performance.

A subspace-based blind channel estimation algorithm for OFDM systems with the conjugate-symmetric property is proposed in this paper. In subspace-based algorithms, construction of the signal or noise subspace is an important issue. Different to other subspace-based approaches exploiting the signal or noise subspace from cyclic prefix, virtual subcarriers, or oversampling techniques, we develop a blind channel estimation algorithm by establishing noise subspace from time-domain real symbols, which can be obtained by using the conjugate-symmetric property of OFDM symbols in frequency-domain. Simulation results demonstrate that the proposed algorithm outperforms conventional subspace-based channel estimation algorithms in mean-squared error.

A subspace-based blind channel estimation algorithm with cyclic prefix is proposed in this paper. A systematic approach is used to construct a new signal matrix in the proposed algorithm. Compared with conventional blind channel estimation algorithm, the proposed algorithm has lower computational complexity and higher probability of full row rank for the corresponding signal matrix. In addition, fewer OFDM symbols can be used to satisfy the necessary condition for achieving a full-row-rank signal matrix. Simulation results show that the proposed algorithm outperforms conventional methods in mean-squared error and bit error rate under static channel. Even with a smaller number of received OFDM symbols, the proposed algorithm can perform well.

A modified subspace-based blind channel estimation algorithm for OFDM systems is proposed in this paper. A systematic approach is used to construct the signal matrix in the proposed algorithm. Compared with conventional subspace- based blind channel estimation algorithm, the proposed algorithm has lower computational complexity and higher probability of full row rank for the corresponding signal matrix. In addition, fewer OFDM symbols can be used to satisfy the necessary condition for achieving a full-row-rank signal matrix. Simulation results show that the proposed algorithm outperforms conventional method in mean-squared error and bit error rate under static channel. Even with a smaller number of received OFDM symbols, the proposed algorithm can perform well.

Carrier frequency offset estimation is an important technique in receiver design of wireless communications. In many applications, sampled single frequency tone is selected as training symbols/sequence for frequency synchronization. Under this assumption, frequency offset estimation can be regarded as the problem of single frequency estimation. In this paper, an approximate maximum likelihood frequency estimator is proposed. This estimator is an efficient one at moderate and high SNR's. When compared with other estimators, the proposed estimator also has lower variance threshold effect and feasibly computational complexity. The proposed estimator is suitable for high carrier frequency offset cases and coarse/fine frequency synchronization applications.

Most existing contention access schemes are inherently unstable resulting in exponentially deteriorating throughput under increased traffic loads. In this paper, we propose a wide-sense stable (WSS) efficient hexanary-feedback contention access (HFCA) scheme, capable of providing signaling traffic high performance while retaining maximal throughput for wireless access networks. HFCA performs incremental contention resolution, managing a small subset of users at a time via a two-phase process. In the first phase, a group of users is probabilistically admitted, with a negligible probability of the group size greater than five. In the second phase, all users in the group are efficiently resolved. The two-phase process is augmented with hexanary feedback control facilitated by a probability density function (pdf)-based multiuser estimator (PMER) implemented at the physical layer. Basically, PMER measures the exact number of transmitting users (zero to five) in a contention slot by matching the envelope-phase pdf's histograms of received signals to a preconstructed pdf's library. To formally justify the performance of HFCA, we present throughput and stability analysis in which HFCA is shown WSS and the strict-sense stability condition is derived. Finally, analytic and simulation results delineate that, HFCA is highly robust against estimation discrepancy. Significantly, HFCA achieves high performance with respect to maximum stable and saturated throughputs, access delay, and blocking probability.

Most existing contention access schemes are inherently unstable resulting in exponentially deteriorating throughput under increased traffic loads. In this paper, we propose a wide-sense stable, efficient hexanary-feedback contention access (HFCA) scheme, capable of providing signaling traffic high performance while retaining maximal throughput for wireless access networks. HFCA performs incremental contention resolution via a two-phase process. The two-phase process is augmented with hexanary feedback control facilitated by a pdf-based multiuser estimator (PMER) implemented at the physical layer. We present throughput and stability analyses in which HFCA is shown wide-sense stable, and the strict-sense stability condition is derived. Finally, analytic and simulation results delineate that, HFCA achieves high performance with respect to maximum stable and saturated throughputs, access delay, and blocking probability.

The random access channel (RACH) incurs a collision if more than one user make signaling requests over the same time slot, spreading code, or antenna element, in TDMA, CDMA, or SDMA wireless networks, respectively. We propose a hexanary-feedback collision resolution paradigm (HFCRP), capable of leveraging access efficiency of the RACH for all above wireless networks. HFCRP performs incremental contention resolution, managing a small subset of users at a time via a two-phase process. In the first phase, a group of users is probabilistically admitted, with a negligible probability of the group size greater than five. In the second phase, all users in the group are efficiently resolved. The two-phase process is augmented with hexanary feedback control facilitated by an envelope-PDF-based multi-user estimator (MR) implemented at the physical layer. Significantly, the MR measures the exact number of transmitting users (zero to five) in a contention slot by matching the envelope PDFs histograms of received signals to a library of pre-constructed PDFs. These six outcomes comprise the hexanary feedback being broadcast to users during the real-time operation of the two-phase process. Analytic and simulation results delineate that, performing in conjunction with the MR, HFCRP achieves high performance with respect to maximum stable throughput, saturated throughput, access delay, and blocking probability.

Existing TDM-based contention access schemes exhibit the unstable or load-susceptible problem in which throughput exponentially deteriorates as the traffic offered load increases or fluctuates. In this paper, we propose a persistently stable, efficient hexanary-feedback-based contention access (HFCA) scheme, aiming to provide QoS guarantee while retaining stable and maximal network throughput. Unlike existing schemes that consider all contending mobile terminals as a whole, HFCA incrementally resolves a small group of terminals each time via a two-phase selection/resolution process. The incremental resolution repeats until the minimum non-blocking probability (QoS for signaling traffic) is satisfied. To accelerate resolution within the process, the number of simultaneously transmitting terminals is estimated based on an envelope-pdf-based estimator (EPER), by matching the corresponding normalized envelope histogram of the receiving signal with the priori envelope-pdf library. Facilitated with incremental resolution and the EPER, HFCA achieves the highest maximum throughput (0.574) and saturated throughput (0.52) reported to date irrespective of traffic increase and variation.

Cochannel interference is often the predominant factor that limits the capacity of a cellular mobile radio system. Power control is thus needed so that carrier-to-cochannel interference ratio (CIR) can be maintained within a tolerable bound. Many power control algorithms that require real-time CIR measurement have been proposed but there is very few mentioning the measurement method. This paper presents viable solutions for real-time CIR estimations under various channel conditions. These solutions are based on either the method of moments or the histogram matching concept. We provide numerical results to demonstrate the usefulness and to compare the performance of the proposed algorithms. It is found that the histogram matching method with a properly-designed nonuniform quantizer offers excellent CIR estimation.

The spectral efficiency of a cellular mobile radio system is enhanced through the reuse of the available spectrum. The resulting co-channel interference, however, also limits the system capacity. Power control is needed so that co-channel interference can be maintained within a tolerable bound. Therefore, co-channel carrier to interference ratio (CIR) is often used as a quality indicator for received signals. Various power control algorithms assume perfect CIR measurement have been proposed but there is no mentioning of the measurement method. This paper presents viable solutions for real-time CIR estimations under either additive white Gaussian noise (AWGN) or Rayleigh fading condition. A new algorithm that uses the concept of probability density function matching is also proposed to measure CIR in the presence of multiple interferers. Numerical results are provided to demonstrate the usefulness of the proposed algorithms.

This paper studies the coded performance of multichannel MFSK and DPSK signalings in mobile satellite environments characterized by various kinds of multipath fading. Rician, Rician/lognormal, and a convex combination of Rician and Rician/lognormal or Rayleigh/lognormal distributions are used to model these communication channels. We investigate the minimum average signal-energy-to-noise ratio required to yield a cutoff rate that is greater than or equal to a given code rate. Also examined are system design issues such as the effect of quantization and metric conversion, the choice between binary codes and M-ary symbol codes, the optimization of the diversity order and the signal size, and the order of deinterleaving and diversity combining. Numerical examples are given to answer concerns raised by these issues.>