A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels

In this paper, we establish a general framework on the reduced dimensional channel state information (CSI) estimation and pre-beamformer design for frequency-selective massive multiple-input multiple-output MIMO systems employing single-carrier (SC) modulation in time division duplex (TDD) mode by exploiting the joint angle-delay domain channel sparsity in millimeter (mm) wave frequencies. First, based on a generic subspace projection taking the joint angle-delay power profile and user-grouping into account, the reduced rank minimum mean square error (RR-MMSE) instantaneous CSI estimator is derived for spatially correlated wideband MIMO channels. Second, the statistical pre-beamformer design is considered for frequency-selective SC massive MIMO channels. We examine the dimension reduction problem and subspace (beamspace) construction on which the RR-MMSE estimation can be realized as accurately as possible. Finally, a spatio-temporal domain correlator type reduced rank channel estimator, as an approximation of the RR-MMSE estimate, is obtained by carrying out least square (LS) estimation in a proper reduced dimensional beamspace. It is observed that the proposed techniques show remarkable robustness to the pilot interference (or contamination) with a significant reduction in pilot overhead

Optimal space-time codes for the MIMO amplify-and-forward cooperative channel

In this work, we extend the non-orthogonal amplify-and-forward (NAF) cooperative diversity scheme to the MIMO channel. A family of space-time block codes for a half-duplex MIMO NAF fading cooperative channel with N relays is constructed. The code construction is based on the non-vanishing determinant criterion (NVD) and is shown to achieve the optimal diversity-multiplexing tradeoff (DMT) of the channel. We provide a general explicit algebraic construction, followed by some examples. In particular, in the single relay case, it is proved that the Golden code and the 4x4 Perfect code are optimal for the single-antenna and two-antenna case, respectively. Simulation results reveal that a significant gain (up to 10dB) can be obtained with the proposed codes, especially in the single-antenna case.Comment: submitted to IEEE Transactions on Information Theory, revised versio

Performance improvements in wireless CDMA communications utilizing adaptive antenna arrays

This dissertation studies applications of adaptive antenna arrays and space-time adaptive processing (STAP) in wireless code-division multiple-access (CDMA) communications. The work addresses three aspects of the CDMA communications problems: (I) near-far resistance, (2) reverse link, (3) forward link. In each case, adaptive arrays are applied and their performance is investigated. The near-far effect is a well known problem which affects the reverse link of CDMA communication systems. The near-far resistance of STAP is analyzed for two processing methods: maximal ratio combining and optimum combining. It. is shown that while maximal ratio combining is not near-far resistant, optimum combining is near-far resistant when the number of cochannel interferences is less than the system dimensionality. The near-far effect can be mitigated by accurate power control at the mobile station. With practical limitations, the received signal power at a base station from a power-controlled user is a random variable clue to power control error. The statistical model of signal-to-interference ratio at the antenna array output of a base station is presented, and the outage probability of the CDMA reverse link is analyzed while considering Rayleigh fading, voice activity and power control error. New analytical expressions are obtained and demonstrated by computer simulations. For the application of an adaptive antenna. array at the forward link, a receiver architecture is suggested for the mobile station that utilizes a small two-antenna array For interference suppression. Such a receiver works well only when the channel vector of the desired signal is known. The identifying spreading codes (as in IS-95A for example) are used to provide an adaptive channel vector estimate, and control the beam steering weight, hence improve the receiver performance. Numerical results are presented to illustrate the operation of the proposed receiver model and the improvement in performance and capacity

Digital communications over fading channels

In this report, the probabilities of bit error for the most commonly used digital modulation techniques are analyzed. Analytic solutions are developed for the probability of bit error when the signal is affected by the most commonly encountered impairment to system performance for a wireless channel, the transmission of the signal over a fading channel. In this report, the effect of a slow, flat Ricean fading channel on communications systems performance is examined. Since channel fading significantly degrades the performance of a communication system, the performance of digital communication systems that also use forward error correction channel coding is analyzed for hard decision decoding and, where appropriate, for soft decision decoding. Diversity, another technique to mitigate the effect of fading channels on digital communication systems performance, is also discussed. Also included is a discussion of the effect of narrowband noise interference, both continuous and pulsed, on digital communication systems. We then discuss the analysis of the probability of bit error for the combination of error correction coding and diversity. Following this, we briefly discuss spread spectrum systems. Next, we examine the link budget analysis and various models for channel loss. Finally, we examine in detail the second generation digital wireless standard Global System for Mobile (GSM).Approved for public release; distribution is unlimited

Processing and Transmission of Information

Contains research objectives and reports on three research projects.National Aeronautics and Space Administration (Grant NsG-334)Joint Services Electronics Programs (U. S. Army, U.S. Navy, and U.S. Air Force) under Contract DA 28-043-AMC-02536(E

Optimising Cooperative Spectrum Sensing in Cognitive Radio Networks Using Interference Alignment and Space-Time Coding

In this thesis, the process of optimizing Cooperative Spectrum Sensing in Cognitive Radio has been investigated in fast-fading environments where simulation results have shown that its performance is limited by the Probability of Reporting Errors. By proposing a transmit diversity scheme using Differential space-time block codes (D-STBC) where channel state information (CSI) is not required and regarding multiple pairs of Cognitive Radios (CR’s) with single antennas as a virtual MIMO antenna arrays in multiple clusters, Differential space-time coding is applied for the purpose of decision reporting over Rayleigh channels. Both Hard and Soft combination schemes were investigated at the fusion center to reveal performance advantages for Hard combination schemes due to their minimal bandwidth requirements and simplistic implementation. The simulations results show that this optimization process achieves full transmit diversity, albeit with slight performance degradation in terms of power with improvements in performance when compared to conventional Cooperative Spectrum Sensing over non-ideal reporting channels. Further research carried out in this thesis shows performance deficits of Cooperative Spectrum Sensing due to interference on sensing channels of Cognitive Radio. Interference Alignment (IA) being a revolutionary wireless transmission strategy that reduces the impact of interference seems well suited as a strategy that can be used to optimize the performance of Cooperative Spectrum Sensing. The idea of IA is to coordinate multiple transmitters so that their mutual interference aligns at their receivers, facilitating simple interference cancellation techniques. Since its inception, research efforts have primarily been focused on verifying IA’s ability to achieve the maximum degrees of freedom (an approximation of sum capacity), developing algorithms for determining alignment solutions and designing transmission strategies that relax the need for perfect alignment but yield better performance. With the increased deployment of wireless services, CR’s ability to opportunistically sense and access the unused licensed frequency spectrum, without causing harmful interference to the licensed users becomes increasingly diminished, making the concept of introducing IA in CR a very attractive proposition. For a multiuser multiple-input–multiple-output (MIMO) overlay CR network, a space-time opportunistic IA (ST-OIA) technique has been proposed that allows spectrum sharing between a single primary user (PU) and multiple secondary users (SU) while ensuring zero interference to the PUs. With local CSI available at both the transmitters and receivers of SUs, the PU employs a space-time WF (STWF) algorithm to optimize its transmission and in the process, frees up unused eigenmodes that can be exploited by the SU. STWF achieves higher performance than other WF algorithms at low to moderate signal-to-noise ratio (SNR) regimes, which makes it ideal for implementation in CR networks. The SUs align their transmitted signals in such a way their interference impairs only the PU’s unused eigenmodes. For the multiple SUs to further exploit the benefits of Cooperative Spectrum Sensing, it was shown in this thesis that IA would only work when a set of conditions were met. The first condition ensures that the SUs satisfy a zero interference constraint at the PU’s receiver by designing their post-processing matrices such that they are orthogonal to the received signal from the PU link. The second condition ensures a zero interference constraint at both the PU and SUs receivers i.e. the constraint ensures that no interference from the SU transmitters is present at the output of the post-processing matrices of its unintended receivers. The third condition caters for the multiple SUs scenario to ensure interference from multiple SUs are aligned along unused eigenmodes. The SU system is assumed to employ a time division multiple access (TDMA) system such that the Principle of Reciprocity is employed towards optimizing the SUs transmission rates. Since aligning multiple SU transmissions at the PU is always limited by availability of spatial dimensions as well as typical user loads, the third condition proposes a user selection algorithm by the fusion centre (FC), where the SUs are grouped into clusters based on their numbers (i.e. two SUs per cluster) and their proximity to the FC, so that they can be aligned at each PU-Rx. This converts the cognitive IA problem into an unconstrained standard IA problem for a general cognitive system. Given the fact that the optimal power allocation algorithms used to optimize the SUs transmission rates turns out to be an optimal beamformer with multiple eigenbeams, this work initially proposes combining the diversity gain property of STBC, the zero-forcing function of IA and beamforming to optimize the SUs transmission rates. However, this solution requires availability of CSI, and to eliminate the need for this, this work then combines the D-STBC scheme with optimal IA precoders (consisting of beamforming and zero-forcing) to maximize the SUs data rates