Jagyasi Deepa Gurmukhdas received her doctorate in Electronics and Communication Engineering  (ECE). Her research work was supervised by Dr. Ubaidulla. Here’s a summary of  Jagyasi Deepa Gurmukhdas’s thesis,  Low-Complexity Millimeter Wave Communication System Designs:

Millimeter Wave (mmWave) communication is considered as one of the important frontiers in the suite of technologies for next generation wireless communication, as it offers huge unlicensed spectrum (3 GHz-300 GHz). The spectrum available at mmWave frequencies is approximately 200 times more than that of currently exploited sub-6 GHz spectrum for wireless communication. It can hence accommodate a lot more users as compared to currently utilized cellular bands. Also, due to shorter wavelengths at high frequencies, mmWaves enable multi-giga-bit-per-second (Gbps) data rates, a major expectations from next generation networks. However, these potential benefits are accompanied by many challenges that include path loss, loss due to blockages, limited coverage, and, absorption and penetration losses. Highly directional beamforming, enabled by large antenna arrays and advanced beamforming techniques, is considered as one of the potential ways to overcome these losses. The two well-studied beamforming techniques used in various wireless communication scenarios are analog beamforming and digital beamforming. In analog beamforming, the same signal is fed into each antenna and then analog phase-shifters are used to steer the signal emitted by the array. Only one pre-processing radio-frequency (RF) chain feeds the same signal to all the antennas in an array. On the other hand, in digital beamforming, a different signal is fed into each antenna, thus requiring an equivalent number of RF chains as the total number of antennas. This allows for greater flexibility since one can assign different powers and phases to different antennas and also to different parts of the frequency bands making digital beamforming particularly desirable for spatial multiplexing. Multi-input-multi-output (MIMO) is hence a key technique in mmWave communication. The small wavelength of mmWaves allows packing of large number of antenna elements in small volumes, thus enabling MIMO implementation and resulting in large beamforming gains from MIMO. Here, we focus on the design of mmWave communication systems to overcome some of the key challenges encountered while exploiting the benefits of MIMO. However, the high cost and power consumption of mixed signal components at mmWave frequencies make practical implementation of fully digital MIMO beamformers difficult. Hybrid beamforming, which offers a trade-off between analog and fully-digital beamforming, is a potential technique to overcome this challenge. In hybrid beamforming, the complete processing happens in two-stages that is digital baseband and analog RF beamforming and the number of RF chains required is less than the number of antenna elements. In this thesis, low-complexity hybrid RF/baseband beamforming architecture is adopted in all the proposed mmWave communication system designs in order to achieve practical feasibility. In particular, to address the underlying challenges, we propose the design of hybrid transceivers for MIMO equipped mmWave systems in different communication scenarios: (i) multi-user MIMO downlink communication, (ii) multi-user MIMO interference channel-based communication, and (iii) MIMO amplify-forward (AF) relay-assisted cooperative communication. For all the considered communication scenarios, we propose low-complexity hybrid transceiver designs. To obtain these, first the fully-digital filters are derived by solving specifically designed optimization problem, which are then decomposed into RF/baseband hybrid filters using sparse approximation techniques. Specifically, in this thesis, we utilize the Orthogonal Matching Pursuit (OMP)-based sparse approximation technique to obtain hybrid filters. In the OMP algorithm, the RF filter matrices are obtained by precisely selecting the vectors from predefined practically realizable RF dictionaries. Once the vectors of RF matrix are selected, the baseband filter is further obtained by minimizing the least square problem in a greedy manner. This OMP-based greedy approach results the optimal hybrid filters by minimizing the residue between the optimal fully-digital filter and decomposed hybrid RF/baseband equivalents at each successive iteration. The distinguishing factor among the three considered scenarios is the difference in the optimization problem formulated to address related communication challenges. The first scenario considers that the base-station (BS) is simultaneously communicating with multiple user-equipments (UEs) over a MIMO downlink channel. A sum-mean-square-error (SMSE) minimization problem is formulated under a constraint on the total transmit power. This is a non-convex problem and a closed-form solution is hard to achieve. We propose a joint iterative algorithm for reliable solution towards this problem. The second scenario, which is a multi-user MIMO interference channel-based scenario, considers a complex network, wherein several mmWave transmitters are simultaneously communicating with their intended receivers. The signal from all remaining transmitters act as co-channel interference at each intended receiver. Three different designs are obtained for this scenario. First, an overall SMSE is minimized under total transmit power constraint for all the transceiver pairs to obtain the low-complexity mmWave system design. Later, its dual problem, i.e., minimization of transmit power at the transmitting units while achieving the desired quality-of-service (QoS) criterion (in terms of SMSE), is addressed. The solution to both the SMSE minimization and its dual problem is derived by an iterative algorithm. At last, the maximization of signal-to-leakage-plus-noise-ratio (SLNR) under a constraint on the transmit power is considered. The proposed leakage-based problem results in a set of decoupled sub-problems and hence admits a closed-form solution. This leads to reduction in computation complexity as compared to the first two iterative solutions obtained for this scenario. The third scenario considers a MIMO AF relay-assisted communication system design in which two UEs are communicating with each other via an AF relay. This case addresses the short-range and non-line-of-sight (NLoS) communication challenges of mmWaves. Again, an SMSE minimization problem is considered with a constraint on the total relay transmit power. Two design solutions are obtained based on the operating mode viz., half-duplex (HD) mode and in-band full-duplex (FD) mode, of all the communicating nodes. First, a transceiver and relay-filter design is proposed considering the HD AF relay and HD UEs. Further, this design is extended to in-band FD mode where all the nodes operate in FD mode and utilize the same frequency resources. In in-band FD communication, due to simultaneous transmission and 2 reception, the problem of loopback-self-interference (LSI) prevails. The LSI can be mitigated using the existing cancellation techniques. However these do not provide perfect cancellation and hence some residual LSI still remains. This residual LSI accumulates over time and hugely affects the overall system performance. In the proposed in-band FD mmWave design, the low-complexity filters are obtained while mitigating the effect of the residual LSI at all the nodes. Channel state information (CSI) is a critical factor in the overall system performance. The availability of perfect CSI is not guaranteed due to the presence of various errors such as pilot contamination, estimation errors, quantization errors, etc., that corrupt the CSI. Hence, in this thesis, the perfect CSI-based proposed designs are also extended towards robust designs for almost all the communication scenarios while making them resilient to the CSI errors. The efficacy of the proposed designs is validated through various performance metrics such as SMSE, sum-rate, bit-error-rate (BER), and hardware and computational complexities. The asymptotic analysis is also performed in order to study the upper bounds on the performance of the system. The numerical results demonstrate that the proposed solutions with reduced hardware complexity achieve comparable performance to the full-complexity digital solutions. Furthermore, the results also demonstrate the resilience of the robust design in the presence of CSI errors as compared to design assuming perfect CSI knowledge.