We study the problem of managing handoffs (HOs) in user-centric cell-free massive MIMO (UC-mMIMO) networks. Motivated by the importance of controlling the number of HOs and by the correlation between efficient HO decisions and the temporal evolution of the channel conditions, we formulate a partially observable Markov decision process (POMDP) with the state space representing the discrete versions of the large-scale fading and the action space representing the association decisions of the user with the access points (APs). We develop a novel algorithm that employs this model to derive a HO policy for a mobile user based on current and future rewards. To alleviate the high complexity of our POMDP, we follow a divide-and-conquer approach by breaking down the POMDP formulation into sub-problems, each solved separately. Then, the policy and the candidate pool of APs for the sub-problem that produced the best total expected reward are used to perform HOs within a specific time horizon. We then introduce modifications to our algorithm to decrease the number of HOs. The results show that half of the number of HOs in the UC-mMIMO networks can be eliminated. Namely, our novel solution can control the number of HOs while maintaining a rate guarantee, where a 47%-70% reduction of the cumulative number of HOs is observed in networks with a density of 125 APs per km2. Most importantly, our results show that a POMDP-based HO scheme is promising to control HOs.

We propose to control handoffs (HOs) in user- centric cell-free massive MIM 0 networks through a partially observable Markov decision process (POMDP) with the state space representing the discrete versions of the large-scale fading (LSF) and the action space representing the association decisions of the user with the access points. Our proposed formulation accounts for the temporal evolution and the partial observability of the channel states. This allows us to consider future rewards when performing HO decisions, and hence obtain a robust HO policy. To alleviate the high complexity of solving our POMDP, we follow a divide-and-conquer approach by breaking down the POMDP formulation into sub-problems, each solved individually. Then, the policy and the candidate cluster of access points for the best solved sub-problem is used to perform HOs within a specific time horizon. We control the number of HOs by determining when to use the HO policy. Our simulation results show that our proposed solution reduces HOs by 47% compared to time- triggered LSF-based HOs and by 70% compared to data rate threshold-triggered LSF-based HOs. This amount can be further reduced through increasing the time horizon of the POMDP.

In this paper, we optimize user scheduling, power allocation and beamforming in distributed multiple-input multiple-output (MIMO) networks implementing user-centric clustering. We study both the coherent and non-coherent transmission modes, formulating a weighted sum rate maximization problem for each; finding the optimal solution to these problems is known to be NP-hard. We use tools from fractional programming, block coordinate descent, and compressive sensing to construct an algorithm that optimizes the beamforming weights and user scheduling and converges in a smooth non-decreasing pattern. Channel state information (CSI) being crucial for optimization, we highlight the importance of employing a low-overhead pilot assignment policy for scheduling problems. In this regard, we use a variant of hierarchical agglomerative clustering, which provides a suboptimal, but feasible, pilot assignment scheme; for our cell-free case, we formulate anarea-basedpilot reuse factor. Our results show that our scheme provides large gains in the long-term network sum spectral efficiency compared to benchmark schemes such as zero-forcing and conjugate beamforming (with round-robin scheduling) respectively. Furthermore, the results show the superiority of coherent transmission compared to the non-coherent mode under ideal and imperfect CSI for the area-based pilot-reuse factors we consider.

We develop two distributed downlink resource allocation algorithms for user-centric, cell-free, spatially-distributed, multiple-input multiple-output (MIMO) networks. In such networks, each user is served by a subset of nearby transmitters that we call distributed units or DUs. The operation of the DUs in a region is controlled by a central unit (CU). Our first scheme is implemented at the DUs, while the second is implemented at the CUs controlling these DUs. We define a hybrid quality of service metric that enables distributed optimization of system resources in a proportional fair manner. Specifically, each of our algorithms performs user scheduling, beamforming, and power control while accounting for channel estimation errors. Importantly, our algorithm does not require information exchange amongst DUs (CUs) for the DU-distributed (CU-distributed) system, while also smoothly converging. Our results show that our CU-distributed system provides 1.3- to 1.8-fold network throughput compared to the DU-distributed system, with minor increases in complexity and front-haul load - and substantial gains over benchmark schemes like local zero-forcing. We also analyze the trade-offs provided by the CU-distributed system, hence highlighting the significance of deploying multiple CUs in user-centric cell-free networks.

We study the problem of user-scheduling and resource allocation in distributed multi-user, multiple-input multiple-output (MIMO) networks implementing user-centric clustering and non-coherent transmission. We formulate a weighted sum-rate maximization problem which can provide user proportional fairness. As in this setup, users can be served by many transmitters, user scheduling is particularly difficult. To solve this issue, we use block coordinate descent, fractional programming, and compressive sensing to construct an algorithm that performs user-scheduling and beamforming. Our results show that the proposed framework provides an 8- to 10-fold gain in the long-term user spectral efficiency compared to benchmark schemes such as round-robin scheduling. Furthermore, we quantify the performance loss due to imperfect channel state information and pilot training overhead using a defined area-based pilot-reuse factor.

Power line communication (PLC) is an emerging field of communication that makes use of the existing power line infrastructure for the transmission of data and power. However, the presence of additive and multiplicative power line noises deteriorate the performance of a PLC system. Background and impulsive noises are the two main categories of additive noise, whereas channel gain accounts for the multiplicative noise. In this study, the authors propose coordinate interleaving (CI) technique and investigate its performance for a PLC system under the combined effect of Nakagami‐ m additive background noise and Rayleigh channel gain. They assume perfect channel state information at the transmitter and receiver of the PLC link. By interleaving the coordinates of the symbols sent over different channel realisations, CI results in significant improvement in the performance of a PLC system. Both the simulated and analytical results shown in this study reveal the effectiveness of the proposed technique in achieving better performance.

Generalized Frequency Division Multiplexing (GFDM) is a recently proposed multicarrier modulation technique. Due to its flexibility and many desired features compared to the orthogonal frequency division multiplexing (OFDM), GFDM is considered as a potential airinterface technique for the next generation wireless networks. However, GFDM suffers from self interference due to the non-orthogonality of its subcarriers. In this paper, we propose two novel precoding techniques to achieve better bit error rate (BER) performance in GFDM systems with linear receivers. The two-stage precoding that we present here achieves higher diversity gain with a reduced complexity linear MMSE receiver, when compared with GFDM system with no precoding and conventional MMSE receiver. Assuming full channel state information at both ends of the communication link, we propose another precoding method based on Singular Value Decomposition (SVD) and Coordinate Interleaving (CI), which we refer to as SVD-CI. By interleaving the coordinates of the symbols sent over different eigen-subchannels of the channel matrix, SVD-CI achieves significant improvement in the BER performance, compared to the SVD precoding proposed earlier. We present the BER performance of the proposed precoding schemes, obtained through Monte Carlo simulations, to validate our claims.

In femtocell networks, large numbers of femtocell access points (FAPs) are deployed and integrated into a cellular network. In this paper, a novel architecture for femtocell networks is proposed, known as fractional cooperation. Using this method, connections from mobile users to multiple FAPs are permitted. This architecture is analogous to fractional cooperation in wireless relay networks. Analytical and simulation results are presented, which indicate that large gains are possible over conventional cellular-style architectures.

In molecular communication, messages are conveyed in patterns of particles (e.g., arranged in time), which propagate from transmitter to receiver by means of Brownian motion. If there is drift from transmitter to receiver, the first arrival time of the particles has the Inverse Gaussian distribution, leading to the additive inverse Gaussian noise channel. In this paper, we give a closed-form upper bound on capacity for this channel when the maximum waiting time is constrained, building on previous work in which only the mean waiting time was constrained.

In this paper, we consider molecular communication, with information conveyed in the time of release of molecules. These molecules propagate to the transmitter through a fluid medium, propelled by a positive drift velocity and Brownian motion. The main contribution of this paper is the development of a theoretical foundation for such a communication system; specifically, the additive inverse Gaussian noise (AIGN) channel model. In such a channel, the information is corrupted by noise that follows an IG distribution. We show that such a channel model is appropriate for molecular communication in fluid media. Taking advantage of the available literature on the IG distribution, upper and lower bounds on channel capacity are developed, and a maximum likelihood receiver is derived. Results are presented which suggest that this channel does not have a single quality measure analogous to signal-to-noise ratio in the additive white Gaussian noise channel. It is also shown that the use of multiple molecules leads to reduced error rate in a manner akin to diversity order in wireless communications. Finally, some open problems are discussed that arise from the IG channel model.

The maximum multiplexing gain of orthogonal relaying protocols has, so far, been limited to 1/2. We propose a new orthogonal decode-and-forward protocol that employs rotated n-dimensional constellations. With a single relay, the proposed protocol achieves a linear diversity-multiplexing tradeoff (DMT) connecting the points (0,2) and (n/n+1,0), where n+1 is the frame length. With NRrelays, our proposed protocol achieves a linear DMT connecting (0, NR+1) and (n/n+NR,0).

Performance of spatial multiplexing multiple-input multiple-output (MIMO) wireless systems can be improved with channel state information (CSI) at both ends of the link. This paper proposes a new linear diagonal MIMO transceiver, referred to as co-ordinate interleaved spatial multiplexing (CISM). With CSI at transmitter and receiver, CISM diagonalizes the MIMO channel and interleaves the co-ordinates of the input symbols (from rotated QAM constellations) transmitted over different eigenmodes. The analytical and simulation results show that with co-ordinate interleaving across two eigenmodes, the diversity gain of the data stream transmitted over the weaker eigenmode becomes equal to that of the data transmitted on the stronger eigenmode, resulting in a significant improvement in the overall diversity. The diversity-multiplexing tradeoff (DMT) is analyzed for CISM and is shown that it achieves higher diversity gain at all positive multiplexing gains compared to existing diagonal transceivers. Over rank n MIMO channels, with input symbols from rotated n-dimensional constellations, the DMT of CISM is a straight line connecting the endpoints (0,NtNr) and (min{Nt,Nr}, 0), where Nt, and Nrare the number of transmit and receive antennas, respectively.

Vertical layering with successive interference cancellation (SIC) at the receiver (e.g. V-BLAST) is a popular spatial multiplexing scheme that achieves high data rates over multi-antenna wireless channels. However, SIC suffers from low diversity gains and recently, with limited feedback, a diversity optimal SIC receiver has been proposed based on greedy QR decomposition (GQR-SIC). But the low diversity gain of the first decoded layer degrades the overall diversity gain. In this paper, we present a new diagonally layered spatial multiplexing scheme that employs GQR-SIC receiver but achieves significantly higher diversity gains. In the proposed scheme, the diversity gain of a weak layer is improved through interleaving the co-ordinates of the symbols transmitted over the weak layer and a strong layer. In this work, we focus on spatial multiplexing with only two layers and analyze the diversity multiplexing tradeoff to show that the proposed scheme achieves maximum diversity gain. When compared with other diagonally layered schemes, the proposed scheme has low decoding complexity.

When channel state information is available at the transmitter, we can diagonalize a MIMO channel with SVD transceivers. However, outage of the weaker eigenchannels limits the performance of such a transceiver. In the current work, we propose and analytically characterize co-ordinate interleaving of multi-dimensional symbols over sets of eigenchannels. We show that in our method, the diversity multiplexing trade-off (DMT) is determined by the strongest eigenchannel in each set. We also calculate the optimal (DMT) for different possible sets and constellation dimensions with rate allocation among the sets.

Spatial multiplexing over multiple-input multiple-output (MIMO) channels significantly improves the data rates over wireless channels. With channel knowledge at both ends of the link, many spatial multiplexing schemes have been proposed in literature, showing improved performance with respect to some performance measure. Co-ordinate interleaved spatial multiplexing (CISM) (Srinivas et al., 2006) is one such scheme that has been shown to achieve improved error rate performance. In this paper, we analyze CISM from diversity-multiplexing gain tradeoff (DMT) perspective. We focus on CISM over MIMO channels having only two degrees of freedom and show that the DMT of CISM is a straight line connecting the two extreme points (0, 2 m) and (2, 0) where m = max{Nt, Nr}. This result shows that CISM outperforms many other schemes that require same amount of feedback.

Spatial multiplexing (SM) over multiple-input multiple-output wireless channels provides significant capacity gains. In a SM scheme, the eigenmode having the least signal-to-noise ratio (SNR), degrades the overall error rate performance. In this paper, we propose co-ordinate interleaved spatial multiplexing that maximizes the minimum SNR over all eigenmodes. This linearly decodable SM scheme needs the knowledge of the right singular vectors of the channel at the transmitter, and the singular values and left singular vectors at the receiver. We derive the SNR expressions for the proposed scheme and compare its performance with other closed-loop schemes using computer simulations