advantages, UM-MIMO increases system complexity and power consumption due to an extensive array of radio frequency (RF) chains that are required and accurate channel state information at the receiver (CSIR) [9; 10]. Spatial modulation (SM) and its variants, such as space shift keying (SSK) and generalized spatial modulation (GSM), offer an elegant trade-off by conveying information using antenna indices, thereby reducing hardware complexity and energy consumption [11; 12]. Recently, generalized quadrature spatial modulation (GQSM) [13; 14] has been introduced, which further improves spectral efficiency by transmitting independent data symbols on the in-phase and quadrature branches using multiple antennas. However, most studies on GQSM have been conducted under ideal conditions, assuming uncorrelated MIMO channels and perfect CSIR, conditions that are rarely encountered in practical systems. In realistic wireless environments, two major factors can severely degrade the performance of spatial modulation schemes: _transmit antenna correlation_ and _imperfect Channel State Information at the Receiver (CSIR)_. Due to space limitations in UM-MIMO systems, transmit antennas are often placed close together, resulting in spatial correlation that reduces the orthogonality of channel paths and complicates detection [15; 16; 17; 18; 19; 20]. Furthermore, CSIR is rarely perfect in real-world deployments due to factors such as estimation errors, quantization, and feedback delays, which lead to residual interference and mismatch in the detection process [21]. Bit error rate (BER) performance frequently suffers as a result, particularly for maximum likelihood (ML) detection techniques [12]. Although several previous studies have examined spatial modulation under Rayleigh or Rician fading and partial CSIR [22; 23; 24], few have addressed the combined effects of _transmit antenna correlation_ and _imperfect CSIR_ in the context of GQSM. Moreover, most analyses are limited to simplified fading models. The Nakagami-\(m\) fading model offers a more general and flexible alternative, able to simulate a variety of fading scenarios by adjusting the shape parameter \(m\). For example, \(m=1\) represents Rayleigh fading typical in urban environments, \(m>1\) captures less severe fading as in Rician environments, and \(m<1\) reflects more severe fading due to shadowing and heavy multipath [15; 16; 25; 26]. Given its applicability to scenarios such as IoT, satellite, and cellular networks, Nakagami-\(m\) fading provides a realistic channel model for 6G systems [27; 28; 29]. Motivation: GQSM has demonstrated promising performance in ideal settings, but its robustness in practical conditions involving correlated antennas and partial CSIR remains largely unexplored. As 6G networks are deployed in dynamic and interference-prone environments, there is a critical need to develop reliable and low-complexity detection schemes that maintain performance despite these impairments. Research Gap and Objectives: There is a lack of comprehensive analysis and robust detection techniques for GQSM under the combined influence of transmit antenna correlation, partial CSIR, and Nakagami-\(m\) fading channel. This paper aims to close this gap by (i) modeling and analyzing GQSM performance under realistic channel impairments, (ii) proposing three QR-based detection techniques that mitigate BER degradation and error floor effects, and (iii) evaluating their performance and complexity against the conventional ML detection method. Core Contributions: This work proposes and evaluates three QR-based detection methods for GQSM over Nakagami-\(m\) fading channels with transmit antenna correlation and partial CSIR. Unlike ML detection, the proposed schemes are shown to be more resilient to estimation errors and significantly decrease the error floor. The simulation results demonstrate that Technique III offers the best BER performance while maintaining a lower computational complexity compared to ML detection, making it more suitable for practical 6G scenarios.