You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Survey: Non-Orthogonal Multiple Access with Compressed Sensing Multiuser Detection for mMTC 
Chapter Title:  Combination of CS-MUD with other techniques 
1. Abstract of Cited Paper (BIB001):  In this paper, we consider a multiuser detection technique when the signal sparsity is changing over time. The key ingredient of our method is a clever switching between the CS reconstruction algorithm and classical detection depending on the sparsity level of the signals being detected. Since none of these approaches is uniformly better in a situation where the sparsity level is varying, proposed switching algorithm can effectively combine the merits of both. We show that the proposed switching algorithm provides substantial performance gain over individual algorithms in the multiuser detection of CDMA downlink. 
2. Abstract of Cited Paper (BIB002):  We propose a novel distributed random access scheme for wireless networks based on slotted ALOHA, motivated by the analogies between successive interference cancellation and iterative belief-propagation decoding on erasure channels. The proposed scheme assumes that each user independently accesses the wireless link in each slot with a predefined probability, resulting in a distribution of user transmissions over slots. The operation bears analogy with rateless codes, both in terms of probability distributions as well as to the fact that the ALOHA frame becomes fluid and adapted to the current contention process. Our aim is to optimize the slot access probability in order to achieve rateless-like distributions, focusing both on the maximization of the resolution probability of user transmissions and the throughput of the scheme. 
3. Abstract of Cited Paper (BIB003):  The emergence of Machine-to-Machine (M2M) communication requires new Medium Access Control (MAC) schemes and physical (PHY) layer concepts to support a massive number of access requests. The concept of coded random access, introduced recently, greatly outperforms other random access methods and is inherently capable to take advantage of the capture effect from the PHY layer. Furthermore, at the PHY layer, compressive sensing based multi-user detection (CS-MUD) is a novel technique that exploits sparsity in multi-user detection to achieve a joint activity and data detection. In this paper, we combine coded random access with CS-MUD on the PHY layer and show very promising results for the resulting protocol. 
4. Abstract of Cited Paper (BIB004):  Non-orthogonal multiple access (NOMA) has become one of the promising key technologies for future 5G wireless communications to improve spectral efficiency and support massive connectivity. However, in the uplink grant-free NOMA system, the current near-optimal multi-user detection (MUD) based on message passing algorithm (MPA) assumes that the user activity information is exactly known at the receiver, which is impractical yet challenging due to anyone of massive users can randomly enter or leave the system. In this paper, inspired by the observation of user sparsity, we jointly use compressive sensing (CS) and MPA to propose a CS-MPA detector to realize both user activity and data detection for uplink grant-free NOMA. Specifically, the MUD problem is firstly formulated under CS framework by exploiting user sparsity, and then user activity can be detected by sparse signal recovery algorithms in CS. Then, MPA can be performed to reliably detect active users' data. It is shown that the proposed CS-MPA detector with affordable complexity not only outperforms the conventional MPA detector without user activity information, but also achieves very close performance to the genie- knowledge MPA detector with exact knowledge of user activity, especially when the signal-to-noise ratio (SNR) is high. 
5. Abstract of Cited Paper (BIB005):  Conventional spatial modulation (SM) is typically considered for transmission in the downlink of small-scale multiple-input–multiple-output (MIMO) systems, where a single antenna element (AE) of a set of, e.g., $\mbox{2}^p$ AEs is activated for implicitly conveying $p$ bits. By contrast, inspired by the compelling benefits of large-scale MIMO (LS-MIMO) systems, here, we propose an LS-SM-MIMO scheme for the uplink (UL), where each user having multiple AEs but only a single radio frequency (RF) chain invokes SM for increasing the UL throughput. At the same time, by relying on hundreds of AEs and a small number of RF chains, the base station (BS) can simultaneously serve multiple users while reducing the power consumption. Due to the large number of AEs of the UL users and the comparably small number of RF chains at the BS, the UL multiuser signal detection becomes a challenging large-scale underdetermined problem. To solve this problem, we propose a joint SM transmission scheme and a carefully designed structured compressive sensing (SCS)-based multiuser detector (MUD) to be used at the users and the BS, respectively. Additionally, the cyclic-prefix single carrier (CPSC) is used to combat the multipath channels, and a simple receive AE selection is used for the improved performance over correlated Rayleigh-fading MIMO channels. We demonstrate that the aggregate SM signal consisting of multiple UL users' SM signals of a CPSC block exhibits distributed sparsity. Moreover, due to the joint SM transmission scheme, aggregate SM signals in the same transmission group exhibit group sparsity. By exploiting these intrinsically sparse features, the proposed SCS-based MUD can reliably detect the resultant SM signals with low complexity. Simulation results demonstrate that the proposed SCS-based MUD achieves a better signal detection performance than its counterparts even with higher UL throughput. 
6. Abstract of Cited Paper (BIB006):  Non-Orthogonal Multiple Access (NOMA) has been considered to be one of the promising key technologies for future wireless communications and broadcasting return channels due to its high spectral efficiency under massive connectivity. The major challenge of NOMA is to realize interference cancellation and detect the optimal transmitted signals among multiple users. The message passing algorithm (MPA) based multi-user detection (MUD) has been developed to approximate optimal signals from multiple users. However, the conventional MPA always suppose that the user-activity is exactly known at the receiver, which is impractical in real systems. Thus, precise user-activity detection is significant in realizing MPA based NOMA system. In this paper, we propose a compressive sensing based time-frequency joint NOMA scheme in the uplink grant-free low density signature orthogonal frequency division multiplexing (LDS-OFDM) systems, where the priori information obtained from the timedomain m-sequence and the frequency-domain training sequence are utilized for user-activity detection under the framework of CS, while the MPA is performed for the successive user-data detection. The proposed method has a superior performance and less complexity compared to the conventional MPA detector in numerical stimulation. 
7. Abstract of Cited Paper (BIB007):  Massive Machine Communication (MMC) in the next generation of mobile communication (5G) systems requires new Medium Access Control (MAC) and physical (PHY) layer concepts to handle massive access with low overhead. The recently developed concept coded random access is capable of resolving collisions in massive access at MAC layer. Furthermore, Compressive Sensing Multi-User Detection (CS-MUD) achieves joint activity and data detection from the PHY layer perspective by exploiting sparsity in sporadic multi-user detection. In [1], a joint design of these two concepts was semi-analytically evaluated combining CS-MUD with coded random access under certain assumptions, which showed a promising performance for supporting MMC. In this work, a full link-level analysis of the joint protocol will be presented to verify the previous results and provide deep insights on the link-level performance. Although the joint approach on the link-level shows a small throughput loss compared to the semi-analytical evaluation, high system flexibility can be achieved by tuning MAC and PHY resources dynamically based on the numerical analysis which can be referred to in the joint MAC-/PHY-layer design.

Literature Review:
The method of CS-MUD was combined with other different techniques to enhance the overall performance of the machine type communication system. The non-orthogonal low density signature based orthogonal frequency division multiplexing and CDMA (LDS-OFDM/CDMA) scheme exploits the sparse signatures, which allows the use of a relatively low complexity message passing algorithm (MPA) to approximate the MAP detection. However, the basic assumption in MPA is that the activity is known at the receiver, which require a higher control signaling overhead. In BIB005 , CS-MUD is combined with MPA receiver and CS-MPA receiver is proposed to optimize the activity and data detection. An active node transmits a dedicated dense spreading sequence before transmitting the actual symbols spread over the sparse LDS signatures. The multiplexed data frame of all active nodes constitutes y 1 and y 2 . y 1 represents the superimposed dense signatures from all active nodes while y 2 is the superimposed sparse LDS signatures over which the data symbols are spread. At the receiver the CS-MUD takes y 1 as input and uses compressive sensing algorithm to detect the active users prior to the MPA detector. The support obtained by the CS-MUD and the y 2 are fed into the MPA to efficiently estimate the data. The detection process is depicted in Figure 12 . When the activity is not known, the MPA has to search for all the possible combinations of data colliding at a subcarrier, which increases the complexity as well as degrades the performance. In the CS-MPA receiver when the support is fed into the MPA detector, the possible combinations for data estimation are reduced which enhances the data estimation accuracy as well as reduces the complexity. The CS-MPA is optimized in BIB007 by incorporating a two stage CS based activity detection. At the first stage a correlation based activity detection is carried out. The approximated support obtained at the first stage is fed into the second stage which executes compressive sampling matching pursuit (CoSaMp) BIB001 algorithm. The CoSaMP uses the y 1 and the estimated support in the first stage as prior information and detect the activity more accurately. The LDS based non-orthogonal schemes are capable of accommodating more users on less physical resources when all users are active while the nonorthogonal CDMA with CS-MUD only works if a small number of the users are active. For example for 6 users sharing 4 physical resources, using the LDS based NOMA, when all 6 users are active, the MPA algorithm is capable of separating the data of all users. On the other hand the CS-MUD cannot separate users when the number of active users is greater than half of the number of physical resources. However, in mMTC where only small number of users are active, the LDS based NOMA requires control signaling overhead for medium access while non-orthogonal CDMA with CS-MUD does not need any control signaling. Considering the variations in the sparsity level of the multiuser signal, in BIB002 a switching mechanism between the CS-MUD and the classical multiuser data detection is proposed. A threshold for the sparsity level based on the OMP algorithm is derived. The multiuser detector uses the OMP algorithm if the sparsity is high and is switched to the classical linear minimum mean square error estimator when the sparsity is lower than the threshold. To efficiently handle the massive connectivity, the MAC layer coded slotted ALOHA BIB003 and the PHY layer CS-MUD are combined in BIB004 BIB008 . The CS-MUD exploits the sparsity at physical layer to jointly detect the activity and data while the coded slotted ALOHA is capable of resolving the collisions by exploiting the successive interference cancellation. The joint activity and data detection at physical layer facilitates the efficient collision resolution and increases the user density at MAC layer. In BIB006 , a large-scale spatial modulation multiple-input-multiple-output system is proposed to reduce the radio frequency chains and hence reduce the hardware cost and power consumption. Each user selects one antenna element out of all the antenna elements used for data transmission. The MUD at the base station is posed as underdetermined signal detection problem and CS-MUD is used for MUD.