Bayesian Channel Estimation Techniques for AF MIMO Relaying Systems

In this paper, we consider the fundamental problem of channel estimation in multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying systems operating over random channels. Using the Bayesian framework, linear minimum mean square error (LMMSE) and expectation-maximization (EM) based maximum a posteriori (MAP) channel estimation algorithms are developed, that provide the destination with full knowledge of all channel parameters involved in the transmission. The performance of the proposed algorithms is evaluated in terms of the mean square error (MSE) as a function of the signal-to-noise ratio (SNR) during the training interval. Our simulation results show that the incorporation of prior knowledge into the channel estimation algorithm offers improved performance, especially in the low SNR regime

Exploiting Diversity in Broadband Wireless Relay Networks

Fading is one of the most fundamental impairments to wireless communications. The standard approach to combating fading is by adding redundancy - or diversity - to help increase coverage and transmission speed. Motivated by the results in multiple-input multiple-output technologies, which are usually used at base stations or access points, cooperation commutation has been proposed to improve the performance of wireless networks which consist of low-cost single antenna devices. While the majority of the research in cooperative communication focuses on flat fading for its simplicity and easy analysis, in practice the underlying channels in broadband wireless communication systems such as cellular systems (UMTS/LTE) are more likely to exhibit frequency selective fading. In this dissertation, we consider a frequency selective fading channel model and explore distributed diversity techniques in broadband wireless relay networks, with consideration to practical issues such as channel estimation and complexity-performance tradeoffs. We first study a system model with one source, one destination and multiple decode-and-forward (DF) relays which share a single channel orthogonal to the source. We derive the diversity-multiplexing tradeoff (DMT) for several relaying strategies: best relay selection, random relay selection, and the case when all decoding relays participate. The best relay selection method selects the relay in the decoding set with the largest sum-squared relay-to-destination channel coefficients. This scheme can achieve the optimal DMT of the system at the expense of higher complexity, compared to the other two relaying strategies which do not always exploit the spatial diversity offered by the relays. Different from flat fading, we find special cases when the three relaying strategies have the same DMT. We further present a transceiver design and prove it can achieve the optimal DMT asymptotically. Monte Carlo simulations are presented to corroborate the theoretical analysis. We provide a detailed performance comparison of the three relaying strategies in channels encountered in practice. The work has been extended to systems with multiple amplify-and-forward relays. We propose two relay selection schemes with maximum likelihood sequential estimator and linear zero- forcing equalization at the destination respectively and both schemes can asymptotically achieve the optimal DMT. We next extend the results in the two-hop network, as previously studied, to multi-hop networks. In particular, we consider the routing problem in clustered multi-hop DF relay networks since clustered multi-hop wireless networks have attracted significant attention for their robustness to fading, hierarchical structure, and ability to exploit the broadcast nature of the wireless channel. We propose an opportunistic routing (or relay selection) algorithm for such networks. In contrast to the majority of existing approaches to routing in clustered networks, our algorithm only requires channel state information in the final hop, which is shown to be essential for reaping the diversity offered by the channel. In addition to exploiting the available diversity, our simple cross-layer algorithm has the flexibility to satisfy an additional routing objective such as maximization of network lifetime. We demonstrate through analysis and simulation that our proposed routing algorithm attains full diversity under certain conditions on the cluster sizes, and its diversity is equal to the diversity of more complicated approaches that require full channel state information. The final part of this dissertation considers channel estimation in relay networks. Channel state information is vital for exploiting diversity in cooperative networks. The existing literature on cooperative channel estimation assumes that block lengths are long and that channel estimation takes place within a fading block. However, if the forwarding delay needs to be reduced, short block lengths are preferred, and adaptive estimation through multiple blocks is required. In particular, we consider estimating the relay-to-destination channel in DF relay systems for which the presence of forwarded information is probabilistic since it is unknown whether the relay participates in the forwarding phase. A detector is used so that the update of the least mean square channel estimate is made only when the detector decides the presence of training data. We use the generalized likelihood ratio test and focus on the detector threshold for deciding whether the training sequence is present. We also propose a heuristic objective function which leads to a proper threshold to improve the convergence speed and reduce the estimation error. Extensive numerical results show the superior performance of using this threshold as opposed to fixed thresholds

Cooperative diversity for the cellular uplink: Sharing strategies, performance analysis, and receiver design

In this thesis, we propose data sharing schemes for the cooperative diversity in a cellular uplink to exploit diversity and enhance throughput performance of the system. Particularly, we consider new two and three-or-more user decode and forward (DF) protocols using space time block codes. We discuss two-user and three-user amplify and forward (AF) protocols and evaluate the performance of the above mentioned data sharing protocols in terms of the bit error rate and the throughput in an asynchronous code division multiple access (CDMA) cellular uplink. We develop a linear receiver for joint space-time decoding and multiuser detection that provides full diversity and near maximum-likelihood performance.;We also focus on a practical situation where inter-user channel is noisy and cooperating users can not successfully estimate other user\u27s data. We further design our system model such that, users decide not to forward anything in case of symbol errors. Channel estimation plays an important role here, since cooperating users make random estimation errors and the base station can not have the knowledge of the errors or the inter-user channels. We consider a training-based approach for channel estimation. We provide an information outage probability analysis for the proposed multi-user sharing schemes. (Abstract shortened by UMI.)

Optimal Training Design for Channel Estimation in Decode-and-Forward Relay Networks With Individual and Total Power Constraints

In this paper, we study the channel estimation and the optimal training design for relay networks that operate under the decode-and-forward (DF) strategy with the knowledge of the interference covariance. In addition to the total power constraint on all the relays, we introduce individual power constraint for each relay, which reflects the practical scenario where all relays are separated from one another. Considering the individual power constraint for the relay networks is the major difference from that in the traditional point-to-point communication systems where only a total power constraint exists for all colocated antennas. Two types of channel estimation are involved: maximum likelihood (ML) and minimum mean square error (MMSE). For ML channel estimation, the channels are assumed as deterministic and the optimal training results from an efficient multilevel waterfilling type solution that is derived from the majorization theory. For MMSE channel estimation, however, the second-order statistics of the channels are assumed known and the general optimization problem turns out to be nonconvex. We instead consider three special yet reasonable scenarios. The problem in the first scenario is convex and could be efficiently solved by state-of-the-art optimization tools. Closed-form waterfilling type solutions are found in the remaining two scenarios, of which the first one has an interesting physical interpretation as pouring water into caves

Multipair Massive MIMO Relaying Systems with One-Bit ADCs and DACs

This paper considers a multipair amplify-and-forward massive MIMO relaying system with one-bit ADCs and one-bit DACs at the relay. The channel state information is estimated via pilot training, and then utilized by the relay to perform simple maximum-ratio combining/maximum-ratio transmission processing. Leveraging on the Bussgang decomposition, an exact achievable rate is derived for the system with correlated quantization noise. Based on this, a closed-form asymptotic approximation for the achievable rate is presented, thereby enabling efficient evaluation of the impact of key parameters on the system performance. Furthermore, power scaling laws are characterized to study the potential energy efficiency associated with deploying massive one-bit antenna arrays at the relay. In addition, a power allocation strategy is designed to compensate for the rate degradation caused by the coarse quantization. Our results suggest that the quality of the channel estimates depends on the specific orthogonal pilot sequences that are used, contrary to unquantized systems where any set of orthogonal pilot sequences gives the same result. Moreover, the sum rate gap between the double-quantized relay system and an ideal non-quantized system is a moderate factor of $4/\pi^2$ in the low power regime.Comment: 14 pages, 10 figures, submitted to IEEE Trans. Signal Processin

Hybrid Processing Design for Multipair Massive MIMO Relaying with Channel Spatial Correlation

Massive multiple-input multiple-output (MIMO) avails of simple transceiver design which can tackle many drawbacks of relay systems in terms of complicated signal processing, latency, and noise amplification. However, the cost and circuit complexity of having one radio frequency (RF) chain dedicated to each antenna element are prohibitive in practice. In this paper, we address this critical issue in amplify-and-forward (AF) relay systems using a hybrid analog and digital (A/D) transceiver structure. More specifically, leveraging the channel long-term properties, we design the analog beamformer which aims to minimize the channel estimation error and remain invariant over a long timescale. Then, the beamforming is completed by simple digital signal processing, i.e., maximum ratio combining/maximum ratio transmission (MRC/MRT) or zero-forcing (ZF) in the baseband domain. We present analytical bounds on the achievable spectral efficiency taking into account the spatial correlation and imperfect channel state information at the relay station. Our analytical results reveal that the hybrid A/D structure with ZF digital processor exploits spatial correlation and offers a higher spectral efficiency compared to the hybrid A/D structure with MRC/MRT scheme. Our numerical results showcase that the hybrid A/D beamforming design captures nearly 95% of the spectral efficiency of a fully digital AF relaying topology even by removing half of the RF chains. It is also shown that the hybrid A/D structure is robust to coarse quantization, and even with 2-bit resolution, the system can achieve more than 93% of the spectral efficiency offered by the same hybrid A/D topology with infinite resolution phase shifters.Comment: 17 pages, 13 figures, to appear in IEEE Transactions on Communication

Collaborative modulation multiple access for single hop and multihop networks

While the bandwidth available for wireless networks is limited, the world has seen an unprecedented growth in the number of mobile subscribers and an ever increasing demand for high data rates. Therefore efficient utilisation of bandwidth to maximise link spectral efficiency and number of users that can be served simultaneously are primary goals in the design of wireless systems. To achieve these goals, in this thesis, a new non-orthogonal uplink multiple access scheme which combines the functionalities of adaptive modulation and multiple access called collaborative modulation multiple access (CMMA) is proposed. CMMA enables multiple users to access the network simultaneously and share the same bandwidth even when only a single receive antenna is available and in the presence of high channel correlation. Instead of competing for resources, users in CMMA share resources collaboratively by employing unique modulation sets (UMS) that differ in phase, power, and/or mapping structure. These UMS are designed to insure that the received signal formed from the superposition of all users’ signals belongs to a composite QAM constellation (CC) with a rate equal to the sum rate of all users. The CC and its constituent UMSs are designed centrally at the BS to remove ambiguity, maximize the minimum Euclidian distance (dmin) of the CC and insure a minimum BER performance is maintained. Users collaboratively precode their transmitted signal by performing truncated channel inversion and phase rotation using channel state information (CSI ) obtained from a periodic common pilot to insure that their combined signal at the BS belongs to the CC known at the BS which in turn performs a simple joint maximum likelihood detection without the need for CSI. The coherent addition of users’ power enables CMMA to achieve high link spectral efficiency at any time without extra power or bandwidth but on the expense of graceful degradation in BER performance. To improve the BER performance of CMMA while preserving its precoding and detection structure and without the need for pilot-aided channel estimation, a new selective diversity combining scheme called SC-CMMA is proposed. SC-CMMA optimises the overall group performance providing fairness and diversity gain for various users with different transmit powers and channel conditions by selecting a single antenna out of a group of L available antennas that minimises the total transmit power required for precoding at any one time. A detailed study of capacity and BER performance of CMMA and SC-CMMA is carried out under different level of channel correlations which shows that both offer high capacity gain and resilience to channel correlation. SC-CMMA capacity even increase with high channel correlation between users’ channels. CMMA provides a practical solution for implementing the multiple access adder channel (MAAC) in fading environments hence a hybrid approach combining both collaborative coding and modulation referred to as H-CMMA is investigated. H-CMMA divides users into a number of subgroups where users within a subgroup are assigned the same modulation set and different multiple access codes. H-CMMA adjusts the dmin of the received CC by varying the number of subgroups which in turn varies the number of unique constellation points for the same number of users and average total power. Therefore H-CMMA can accommodate many users with different rates while flexibly managing the complexity, rate and BER performance depending on the SNR. Next a new scheme combining CMMA with opportunistic scheduling using only partial CSI at the receiver called CMMA-OS is proposed to combine both the power gain of CMMA and the multiuser diversity gain that arises from users’ channel independence. To avoid the complexity and excessive feedback associated with the dynamic update of the CC, the BS takes into account the independence of users’ channels in the design of the CC and its constituent UMSs but both remain unchanged thereafter. However UMS are no longer associated with users, instead channel gain’s probability density function is divided into regions with identical probability and each UMS is associated with a specific region. This will simplify scheduling as users can initially chose their UMS based on their CSI and the BS will only need to resolve any collision when the channels of two or more users are located at the same region. Finally a high rate cooperative communication scheme, called cooperative modulation (CM) is proposed for cooperative multiuser systems. CM combines the reliability of the cooperative diversity with the high spectral efficiency and multiple access capabilities of CMMA. CM maintains low feedback and high spectral efficiency by restricting relaying to a single route with the best overall channel. Two possible variations of CM are proposed depending on whether CSI available only at the users or just at the BS and the selected relay. The first is referred to Precode, Amplify, and Forward (PAF) while the second one is called Decode, Remap, and Forward (DMF). A new route selection algorithm for DMF based on maximising dmin of random CC is also proposed using a novel fast low-complexity multi-stage sphere based algorithm to calculate the dmin at the relay of random CC that is used for both relay selection and detection