This study explores interference coordination for space-air-ground integrated networks under probabilistic line-of-sight (LoS) channel models, where the LoS probability of a wireless channel is statistically modeled based on the elevation angle between an unmanned aerial vehicle (UAV) and a ground node (GN). Unlike conventional approaches that simplify the model by neglecting either LoS or non-LoS (NLoS) channel components, we jointly optimize user scheduling, transmit power, and three-dimensional trajectory while fully accounting for both components. The objective is to maximize the minimum average spectral efficiency (SE) among GNs while ensuring the required SE for earth stations (ESs) served by satellites. Given the nonconvexity of the optimization problem, we decompose it into four subproblems and apply a successive convex approximation to make each subproblem convex with respect to the relevant optimization variable. Subsequently, we propose a low-complexity algorithm based on the block coordinate descent method to iteratively determine the optimal solution for each convex subproblem. Extensive simulations under various scenarios confirm that the UAV optimizes its horizontal and vertical trajectories to increase the LoS probability of the signal channel and the NLoS probability of the interference channel. This allows the UAV to serve GNs with high SE while reducing interference to the ESs. The results also demonstrate that the proposed scheme outperforms baseline schemes in terms of average SE by jointly optimizing the three-dimensional trajectory and communication resources.

In this paper, we explore the rigorous mathematical modeling of an unmanned aerial vehicle (UAV)-enabled parcel delivery to optimize a three-dimensional (3D) trajectory and pickup/drop-off strategy. Taking into account practical considerations including the avoidance of no-fly zones (NFZs) and the weight restrictions of the UAV, our goal is to jointly optimize the pickup and drop-off indicators, lengths of time slots, and horizontal and vertical trajectories, with the objective of minimizing the weighted-sum of completion time and energy consumption. To address the nonconvexity of the formulated problem, which involves mixed-integer nonlinear programming, we first apply a successive convex approximation to transform the nonconvex problem into a convex one for optimization variables. Moreover, we utilize a penalty convex-concave procedure to maintain the binary nature of integer variables. Finally, for the relaxed convex problem, we propose a low-complexity algorithm that derives the suboptimal UAV strategy iteratively. The simulation results demonstrate the effectiveness of the proposed strategy in establishing 3D trajectories for specific objectives and completely avoiding NFZs while maintaining the binary nature of the pickup and drop-off indicators. Furthermore, the comparative study provides insight into the trade-offs between time-minimization and energy-minimization strategies, offering the flexibility to choose the most suitable approach based on the specific service requirements and objectives.

Reconfigurable intelligent surfaces (RIS) are emerging as a promising technology for next-generation wireless communications, capable of mitigating severe propagation attenuation, enhancing spectral efficiency, and expanding signal coverage. This paper focuses on online millimeter-wave (mmWave) beam tracking for multi-RIS-assisted hybrid beamforming systems. We develop two novel beam tracking algorithms based on multi-agent deep reinforcement learning (DRL): a multi-agent deep deterministic policy gradient (MADDPG)-based algorithm for continuous-domain beam angle tracking and a multi-agent deep Q-network (MADQN)-based algorithm for codebook-based discrete-domain beam angle tracking. Both algorithms are designed to maximize the sum rate by jointly optimizing analog beamforming for the base station (BS) and reflection coefficients for multiple RISs in dynamic environments, leveraging historical information and without requiring current user position or channel information. After determining analog beamforming and RIS reflection coefficients, digital beamforming for the BS is constructed by estimating the end-to-end effective channel, which significantly reduces the overhead of channel estimation. Experimental results demonstrate that the proposed algorithms effectively adapt the analog beamformer and RIS reflection coefficients to account for user mobility, significantly outperforming existing benchmark schemes.

This paper studies a cooperative relaying communication scheme that employs a single passive reconfigurable intelligent surface (RIS), utilizing integer forcing (IF) as a multiple-input multiple-output (MIMO) technique. In the case of IF-based transceivers, the transmitter sends independently encoded data streams using the same lattice code, and the receiver decodes integer-linear combinations of codewords instead of decoding each codeword separately. Although the flexible decoding provided by IF improves achievable rates compared to conventional separate decoding, the integer-linear combinations observed at the IF-based receiver must remain unchanged throughout the codeword’s duration, even in the presence of channel variations, to enable the decoding of summed codewords. Motivated by this fact, we introduce a novel strategy tailored for IF that involves adjusting the reflection matrix of the RIS to reduce fluctuations in the resulting end-to-end channel between the transmitter and receiver throughout codeword transmission, which we refer to aschannel stabilization. Furthermore, we develop a novel IF-based transceiver scheme calledsuccessive cancellation IF (SC-IF), which effectively integrates successive IF (S-IF) sum decoding with minimum mean square error-successive interference cancellation (MMSE-SIC) individual decoding within a unified MIMO framework to achieve improved performance. Simulation results demonstrate that when a large number of reflective elements are employed in the RIS, the proposed channel stabilization scheme significantly outperforms benchmark schemes that aim to individually optimize the reflection matrix for each sub-block, and the proposed SC-IF can achieve a rate comparable to the theoretical upper bound represented by the joint maximal likelihood (ML) receiver.

We study a new rate splitting (RS)-based hybrid beamforming scheme for multi-user downlink cellular networks in which the base station having a hybrid beamforming structure serves multiple users each having conventional multiple antennas. To maximize the potential of RS, we propose a general RS-enabled hybrid beamforming framework that can be applied to both fully-connected and sub-array hybrid beamforming structures, allowing for the assignment of a flexible number of streams for each user. Our proposed RS method divides each stream into an arbitrary number of common and private sub-streams, where private sub-streams are only recoverable by a dedicated user, whereas common streams can be recovered by all users. We propose a low-complexity analog and digital beamforming design suitable for the proposed RS and optimize the number of allocated common and private sub-streams for all users through a low-complexity genetic algorithm to maximize the achievable sum rate or minimum rate over multiple users. Numerical results demonstrate that the proposed scheme achieves a near-optimal sum rate close to that of dirty paper coding with low computational complexity and outperforms the benchmark approaches without considering RS.

We consider reconfigurable intelligent surface (RIS) aided sixth-generation (6G) terahertz (THz) communications for indoor environment in which a base station (BS) wishes to send independent messages to its serving users with the help of multiple RISs. For indoor environment, various obstacles such as pillars, walls, and other objects can result in no line-of-sight signal path between the BS and a user, which can significantly degrade performance. To overcome such limitation of indoor THz communication, we firstly optimize the placement of RISs to maximize the coverage area. Under the optimized RIS placement, we propose 3D hybrid beamforming at the BS and phase adjustment at RISs, which are jointly performed at the BS and RISs via codebook-based 3D beam scanning with low complexity. Numerical simulations demonstrate that the proposed scheme significantly improves the average sum rate compared to the cases of no RIS and randomly deployed RISs and also outperforms several benchmark schemes. It is further shown that the proposed codebook-based 3D beam scanning efficiently aligns analog beams between BS–user links or BS–RIS–user links and, as a consequence, achieves the average sum rate close to that of coherent beam alignment requiring global channel state information.

We consider reconfigurable intelligent surface (RIS) aided sixth-generation (6G) terahertz (THz) communications for indoor environment in which a base station (BS) wishes to send independent messages to its serving users with the help of multiple RISs. For indoor environment, various obstacles such as pillars, walls, and other objects can result in no line-of-sight signal path between the BS and a user, which can significantly degrade performance. To overcome such limitation of indoor THz communication, we firstly optimize the placement of RISs to maximize the coverage area. Under the optimized RIS placement, we propose 3D hybrid beamforming at the BS and phase adjustment at RISs, which are jointly performed at the BS and RISs via codebook-based 3D beam scanning with low complexity. Numerical simulations demonstrate that the proposed scheme significantly improves the average sum rate compared to the cases of no RIS and randomly deployed RISs and also achieves the average sum rate close to that of coherent beam alignment requiring global channel state information.

A new multiple-input multiple-output (MIMO) receiver scheme for practical binary codes is proposed that provides consistent gains over conventional linear receivers. We first develop a practical successive integer forcing (IF) scheme based on practical binary codes rather than lattice codes. We then present the successive cancellation integer forcing (SC-IF) scheme, which combines and enhances successive IF and minimum mean squared error successive interference cancellation (MMSE-SIC). In this scheme, the receiver first decides whether individual decoding or IF sum decoding is appropriate for each data stream, and then conducts successive IF sum decoding only for selected streams while decoding the remaining streams using MMSE-SIC. The proposed SC-IF methodology mitigates the performance loss caused by mismatched IF filtering in fading channels, while attenuating the noise amplification caused by MMSE filtering. Extensive link-level simulations demonstrate that the proposed successive IF significantly improves the basic IF, and the SC-IF improves both the successive IF and MMSE-SIC, offering uniform improvements over conventional linear receivers for most channel correlation and variation parameters and modulation orders at comparable computational costs. These results illustrate the viability of SC-IF as a fundamental building block for high-performance MIMO receivers in 5G-Advanced and/or subsequent-generation communication systems.

A new interference management scheme based on integer forcing (IF) receivers is studied for the two-user multiple-input and multiple-output (MIMO) interference channel. The proposed scheme employs a message splitting method that divides each data stream into common and private sub-streams, in which the private stream is recovered by the dedicated receiver only while the common stream is required to be recovered by both receivers. Specifically, to enable IF sum decoding at the receiver side, all streams are encoded using the same lattice code. Additionally, the number of common and private streams of each user is carefully determined by considering the number of antennas at transmitters and receivers, the channel matrices, and the effective signal-to- noise ratio (SNR) at each receiver to maximize the achievable rate. Furthermore, we consider various assumptions of channel state information at the transmitter side (CSIT) and propose low-complexity linear transmit beamforming suitable for each CSIT assumption. The achievable sum rate and rate region are analytically derived and extensively evaluated by simulation for various environments, demonstrating that the proposed interference management scheme strictly outperforms the previous benchmark schemes in a wide range of channel parameters due to the gain from IF sum decoding.

We study cooperative communication with an active reconfigurable intelligent surface (RIS) for the$K$-user rank-deficient multiple-input multiple-output (MIMO) interference channel. Specifically, we assume that transmitters and receivers use$M$antennas each, and the channel matrix between each transmitter and each receiver has rank$L_{2}$whereas the channel matrix between each transmitter or each receiver and the RIS has rank$L_{1}$, where$L_{1}, L_{2}\leq M$. In the absence of the RIS, the multiplexing gain from MIMO is severely limited when$L_{2}$is small. We develop a novel cooperative transmission technique utilizing the RIS to overcome the channel rank deficiency and manage inter-user interference, and the key idea is to neutralize interfering links using signals reflected from the RIS or to reflect incident waves at the RIS to increase the rank of effective channel matrices, depending on the system configuration parameters. We analyze the achievable sum degrees of freedom (DoF) and sum rate, and derive an upper bound on the sum DoF, which is tight under certain conditions. The results show that using an active RIS can significantly improve both the sum rate and sum DoF compared to the network without the RIS, especially when$L_{1}$is small and/or$L_{2}$is large.

This article studies simultaneous wireless information and power transfer (SWIPT) for unmanned aerial vehicle (UAV)-enabled Internet-of-Things (IoT) networks. Specifically, it is assumed that a single UAV wishes to simultaneously send common and private data streams as well as energy to multiple IoT nodes, in which the common stream should be recovered by all nodes while private streams are recovered only by the dedicated nodes. In addition, it is assumed that each node uses a power-splitting method that divides the received signal into two parts for energy harvesting and information decoding. Under this setting, by applying a concave-convex procedure (CCCP) method, we propose a novel algorithm that maximizes the minimum rate of private streams of IoT nodes by properly allocating the transmit power of each stream, adjusting the power-splitting ratios at IoT nodes, and designing the trajectory of the UAV, while the common rate and energy harvesting constraints at each node should also be satisfied. Moreover, to enable multiuser communication, a superposition coding in conjunction with successive interference cancellation (SIC) decoding is considered for SWIPT. The performance of the proposed scheme is evaluated and compared with benchmark schemes in various aspects by numerical simulations.

An Internet-of-Things (IoT) cellular network is considered in which IoT devices communicate with an IoT base station using IoT sub-bands placed between long-term evolution (LTE) bands. Due to spectral leakage, inter-band interference exists among IoT sub-bands and also between LTE and IoT bands. It is assumed that the IoT cellular network is responsible for reducing its interference to the LTE network to a certain threshold level. Under such interference regulation to LTE bands, we establish a joint sub-band assignment and power allocation optimization in order to maximize the sum rate of the IoT cellular network. A novel two-stage suboptimal algorithm that sequentially performs sub-band assignment and power control is proposed, reflecting the impact of spectral leakage in its optimization procedure. Simulation results demonstrate that the proposed algorithm considering the impact of spectral leakage outperforms the conventional optimization algorithms without considering spectral leakage. It is further shown that it provides almost the same sum rate achievable for a stand-alone network as if there were no LTE networks.

A new practical multiple-input multiple-output (MIMO) transceiver technique calledspatially modulated integer-forcing(SM-IF) is proposed for hybrid beamforming array systems, which combines generalized spatial modulation (GSM) with integer-forcing (IF) MIMO multiplexing transmission to achieve improved spectral efficiency with low system complexity. In the proposed scheme, the transmitter first activates a subset of antennas using analog beamforming and delivers an SM information stream via the index of the activated antenna group. Then MIMO digital multiplexing is applied to send multiple MIMO information streams via multilevel coding (MLC) with binary channel codes through the activated antennas. At the receiver side, the receiver first estimates the index of the activated antenna group to recover the SM stream and then recovers the MIMO streams by IF sum decoding in conjunction with multi-stage decoding. The proposed scheme provides a unified coding framework to achieve a synergistic gain by integrating off-the-shelf practical binary codes and low complexity IF decoding into hybrid beamforming array systems. By extensive link-level numerical simulations, the proposed scheme is shown to outperform both the conventional plain IF MIMO and plain SM approaches. The results demonstrate that the proposed SM-IF can be a promising transceiver technique implementable in practical hybrid beamforming array systems.

An internet of things (IoT) cellular network is considered in which IoT devices communicate with an IoT base station using IoT sub-bands placed between long-term evolution (LTE) bands. Due to spectral leakage, inter-band interference exists among IoT subbands and also between LTE and IoT bands. It is assumed that the IoT cellular network is responsible for reducing its interference to the LTE network to a certain threshold level. Under such interference regulation to LTE bands, we establish a joint sub-band assignment and power allocation optimization in order to maximize the sum rate of the IoT cellular network. A novel two-stage suboptimal algorithm that sequentially performs sub-band assignment and power control is proposed, reflecting the impact of spectral leakage in its optimization procedure. Simulation results demonstrate that the proposed algorithm considering the impact of spectral leakage outperforms the conventional algorithms without considering spectral leakage.

We study a simultaneous wireless information and power transfer (SWIPT) setup for the K-user multiple-input single-output (MISO) interference channel. Each transmitter can either send a private or a common message, and each receiver uses a power splitting method that divides the received signal into two parts for information decoding and energy harvesting. The private message is recovered by the destination receiver only while the common message is recovered by all the receivers. While satisfying individual rate and energy harvesting constraints, our goal is to minimize the total transmit power by properly selecting the message types, designing the beamforming vectors at transmitters, and adjusting the power splitting parameters at receivers. To optimize the parameters of our proposed scheme, we first formulate the problem in terms of a semidefinite programming (SDP) and further relax the formulation to propose low complexity algorithms for numerical optimization. In numerical results, it is shown that the required transmit power of the proposed scheme is much lower than that of the conventional scheme based on transmitting private messages only, especially when the required harvesting energy is high or the channel gains of the cross-links are strong.

In this paper, we study simultaneous wireless information and power transfer (SWIPT) for Internet of Things (IoT) sensor networks. The transmitters (e.g., access point) employ hybrid beamforming and each IoT receiver adopts a power splitting (PS) method that divides the received signal into two parts for information recovery and energy harvesting. We propose a novel strategy for SWIPT in which the transmitters have the option to either send a private or a common message. The private message is recovered only by a designated IoT receiver while common messages are recovered by all the receivers. While requiring the receivers to recover a common message results in additional rate constraints, the overall system performance benefits by mitigating interference. We propose SWIPT schemes that minimize the total transmit power by properly selecting message configurations, designing hybrid beamforming vectors, and adjusting the PS ratio at the receivers to satisfy the individual rate and energy harvesting constraints. In particular, we develop tractable and efficient twostage algorithms that, in the first stage determine the message configurations and in the second stage find the beamforming vectors (for both analog and digital components). Numerical simulations demonstrate that the proposed schemes significantly outperform conventional schemes that transmit private messages only using digital beamforming.

A cooperative cognitive radio for satellite networks is considered, in which the primary network is a satellite network and the secondary network is a cellular network. Due to the lack of multipath in a satellite environment, the channel matrices of the satellite network are assumed to be rank-deficient, which implies that the capacity cannot be increased in proportion to the number of antennas. To overcome the rank deficiency, we propose a novel cooperative transmission strategy where the base station or mobile users in the cellular network both help the communication of the satellite network and transmit and receive their own streams. Not only does the secondary network carefully adjust the number of transmitted streams to avoid causing interference to the primary network beyond a certain threshold; it also provides alternative signal paths for the primary network, thereby effectively increasing the channel ranks of the primary network. We obtain both the achievable sum degrees of freedom (DoFs) and the sum rate under the proposed scheme, and we also derive upper bounds on the sum DoF. Using the analytical and numerical analysis, we show that our scheme significantly improves the overall system throughput compared with the satellite network alone, without cognitive access.

We study Please be advised that per instructions from the Communications Society this proof was formatted in Times Roman font and therefore some of the fonts will appear different from the fonts in your originally submitted manuscript. For instance, the math calligraphy font may appear different due to usage of the usepackage[mathcal]euscript. The Communications Society has decided not to use Computer Modern fonts in their publications. the degrees of freedom (DoF) of cellular networks in which a full duplex (FD) base station (BS) equipped with multiple transmit and receive antennas communicates with multiple mobile users. We consider two different scenarios. In the first scenario, we study the case when half duplex (HD) users, partitioned to either the uplink (UL) set or the downlink (DL) set, simultaneously communicate with the FD BS. In the second scenario, we study the case when FD users simultaneously communicate UL and DL data with the FD BS. Unlike conventional HD only systems, inter-user interference (within the cell) may severely limit the DoF, and must be carefully taken into account. With the goal of providing theoretical guidelines for designing such FD systems, we completely characterize the sum DoFs for both FD cellular networks. The key idea of the proposed scheme is to carefully allocate UL and DL streams using interference alignment and beam forming techniques. By comparing the DoFs of the FD systems with those of the conventional HD systems, we show that the DoF can approach the two-fold gain over the HD systems, when the number of users becomes large enough compared with the number of antennas at the BS.

A new practical coding scheme for integer- forcing (IF) multiple-input multiple-output (MIMO)systems is proposed. In order to utilize practical binary codes for IF, the proposed scheme is based on multilevel coding, in which multilevel encoding composed of binary linear codes is employed at the transmitter and multistage decoding suitably adapted to the IF operation is employed at the receiver. The performance of the proposed scheme is evaluated both analytically and numerically, showing that the gain of IF over conventional receivers is indeed achievable with practical binary codes. Specifically, it is shown that the proposed IF receiver can significantly outperform conventional linear receivers especially when the channel correlation is severe and/or target spectral efficiency is high.

It was recently shown that full-duplex (FD) operation at a base station (BS) can provide up to twice as many degrees of freedom (DoF) as a conventional half-duplex (HD) cellular network in the absence of self-interference. In practice, however, self-interference in an FD BS may not be eliminated completely due to imperfect cancellation, and it is not yet known whether FD operation can improve the sum DoF of cellular networks in the presence of residual self-interference. In this paper, we provide a complete characterization of the sum DoF in an FD-BS cellular network with self-interference, where the rank of the self-interference matrix is arbitrary. Specifically, we propose a self-interference cancellation scheme that maximizes the sum DoF, and we prove its optimality by deriving the matching upper bound. Our results show that even in the presence of residual self-interference, an FD-BS network can still outperform a conventional HD-BS network, and furthermore, the sum DoF coincides with that of an FD-BS network with no self-interference under certain conditions. We also derive an achievable sum rate under ergodic phase fading, showing that not only a sum-DoF gain but also a sum-rate gain can be obtained over the entire signal-to-noise ratio range even if residual self-interference exists.

An integer-forcing (IF) linear multiple-input multiple-output (MIMO) receiver has recently been proposed, which is theoretically shown to achieve near capacity with almost the same complexity as that of conventional linear receivers. The key idea is that the receiver attempts to directly decode integer-linear combinations of codewords. To ensure that this sum-decoding operation is feasible, in previous works, lattice codes over$\mathbb {Z}_{q}$were employed. Although those codes can attain good theoretical performance, however, its implementation complexity can be considerably high in practice, especially when$q$is large to support high-order modulations. In this paper, we propose a practical multilevel coding scheme for IF MIMO, in which multilevel encoding composed of binary linear codes$(q = 2)$in conjunction with the natural mapping is employed on the transmitter side and multistage decoding adapted to the IF operation is employed on the receiver side. The performance of the proposed scheme is extensively evaluated both analytically and numerically, showing that the gain of IF over conventional receivers is indeed achievable in practical settings with almost the same complexity. Our results imply that the proposed IF MIMO can be an attractive solution for the 5G communications due to its ability of supporting high spectral efficiency with low complexity.

This paper studies the degrees of freedom (DoFs) of full-duplex (FD) multicell networks that share the spectrum among multiple cells. In the considered network, we assume that FD base stations (BSs) with multiple transmit and receive antennas communicate with multiple single-antenna uplink (UL) and downlink (DL) mobile users. By spectrum sharing among multiple cells, and with FD radio, the network can utilize the spectrum more efficiently. However, since spectrum sharing and FD induce additional inter-cell and intra-cell interferences, interference management is crucial to take advantage of these features. In this paper, we propose novel interference management strategies which take into account the new sources of interferences caused by spectrum sharing and FD to establish a general achievability result on the sum DoFs. The key ideas in our proposed scheme are to minimize the dimension of UL inter-cell and user-to-user interferences using interference alignment at the UL users. On the BS side, we propose an interference management strategy to align or null out DL intra-cell and inter-cell interferences, and BS-to-BS interferences. We further establish an upper bound on the sum DoFs and show that our lower and upper bounds match under certain conditions. Several numerical evaluations are shown which demonstrate that spectrum sharing and FD can significantly improve the throughput over conventional cellular networks, especially for a network with large number of users and/or cells.

We study the sum degrees of freedom (DoF) of interference channels with hybrid beamforming in which each transmitter i uses M'iantennas and MiRF chains and each receiver i uses N'iantennas and NiRF chains, where Mi≤ M'iand Ni≤ N'i, ∀i = 1, 2,..., K, and hybrid beamforming composed of analog and digital precoders is employed at each node. For the two-user case, we completely characterize the sum DoF for an arbitrary number of antennas and RF chains by developing an achievable scheme optimized for the hybrid beamforming structure and deriving its matching upper bound. For a general K-user case, we focus on a symmetric case where Mi= M, Ni= N, M'i= M , and N'i= N', ∀i = 1, 2, . . ., K, and obtain lower and upper bounds on the sum DoF, which are tight when max{M',N'}/min{M',N'} is an integer. The results show that with a fixed number of RF chains, employing more antennas can increase the sum DoF of interference channel under certain conditions while this cannot improve the sum DoFs of point-to-point channel, multiple access channel, and broadcast channel.

We study the degrees of freedom (DoF) of cellular networks in which a full duplex (FD) base station (BS) equipped with multiple transmit and receive antennas communicates with multiple mobile users. We consider two different scenarios. In the first scenario, we study the case when half duplex (HD) users, partitioned to either the uplink (UL) set or the downlink (DL) set, simultaneously communicate with the FD BS. In the second scenario, we study the case when FD users simultaneously communicate UL and DL data with the FD BS. For both network models, we completely characterize the sum DoFs by developing achievable schemes and obtaining matching upper bounds. The key idea of the proposed scheme is to carefully allocate UL and DL information streams using interference alignment and beamforming techniques. As a consequence of the result, we show that the DoF can approach the two-fold gain over the HD systems when the number of users becomes large enough as compared to the number of antennas at the BS.

We study the sum degrees of freedom (DoFs) of the K-user rank-deficient interference channel with feedback. For the two-user case, we characterize the sum DoF by developing an achievable scheme and deriving a matching upper bound. For the three-user case, we develop a new achievable scheme which employs interference alignment to efficiently utilize the dimension of the received signal space. In addition, we derive an upper bound for the general K-user case and show the tightness of the bound when the number of antennas at each node is sufficiently large. As a consequence of these results, we show that feedback can increase the DoF when the number of antennas at each node is large enough as compared with the ranks of channel matrices. This finding is in contrast to the full-rank interference channel where feedback provides no DoF gain. The gain comes from using feedback to provide alternative signal paths, thereby effectively increasing the ranks of desired channel matrices.

In this paper, we study the degrees of freedom (DoF) of cellular networks in which a base station with full-duplex operation simultaneously communicates to multiple half-duplex mobile stations. The half-duplex mobile stations are assumed to either communicate with the base station in the uplink or downlink. For such networks, inter-terminal interference needs to be taken into account to achieve the potential gain that doubles the throughput of conventional half-duplex cellular networks. We provide an achievable total DoF for such networks and show that having full-duplex operation at the base station only can indeed double the DoF when the number of mobile stations is sufficiently greater than the number of antennas at the base station. The key idea is to utilize the full DoF for the uplink transmission, while minimizing the inter-terminal interference via interference alignment. The downlink communication rate is then carefully chosen to occupy the remaining DoF at the receiving mobile stations.

We characterize the total degrees of freedom (DoF) of the two-user rank-deficient interference channel with feedback, in which transmitter i and receiver j use Miand Njantennas, respectively, and the rank of the channel matrix between transmitter i and receiver j is given by Dji≤ min(Mi, Nj) ∀i, j = 1,2. One consequence of this result is that feedback can increase the DoF when the number of antennas at each node is large enough as compared to the ranks of channel matrices. This finding is in contrast to the full-rank interference channel where feedback provides no DoF gain. The gain comes from using feedback to provide alternative signal paths, thereby effectively increasing the ranks of desired channel matrices.

We consider a class of K-user line-of-sight interference channels without channel state information at transmitters (CSIT). All transmitters are fixed while receiver i has high mobility if i∈{1,2,⋯,K1} and has low mobility otherwise, where K-1≤ K1≤ K, and the channel coherence times for high- and low-mobility receivers are given by one and T, respectively. In addition, we assume that both transmitter i and receiver i use M≥ T antennas if i∈{1,2,⋯K1} and use only one antenna otherwise. In this paper, we propose an interference alignment (IA) scheme for these channels. The key idea is to group receivers with different mobility to have different coherence time. The results show that IA can improve the degrees of freedom even in the absence of CSIT under certain conditions.

We analyze the achievable degrees of freedom (DoF) of the time-varying K-user rank deficient (M, N, D) interference channel (IC) in which each transmitter and receiver uses M and N antennas, respectively, and the rank of each channel matrix is equal to D ≤ min (M, N). The proposed achievable schemes are based on zero forcing and interference alignment. We see that the total DoF of min (DK, max(M+N-D,(DL/L+1)K)) is achievable, where L=(max(M,N/D)) and (x) denotes the integer part of x. The result shows that the achievable total DoF of the K-user (M, N, D) IC has similar tendency to that of the full rank IC.

We analyze achievable multiplexing gains (MUXGs) of fully connected K-user line-of-sight (LOS) interference channels (ICs). An array of polarimetric antennas, each composed of three orthogonal electric dipoles and three orthogonal magnetic dipoles in which all six elements are co-located, is used throughout this paper. For a K-user LOS IC with single polarization, the maximum achievable MUXG is only K, regardless of the number of transmit and receive antennas at each node due to the key-hole effect. If polarimetric antennas are used at each node, a trivial upper bound on the MUXG is now 2K. In this paper, we consider zero-forcing (ZF) and interference alignment (IA) schemes to achieve this upper bound. We show the optimal MUXG of 2K is achievable if M ≥ ((K+1)/6) polarimetric antennas are used at each node for any K. In addition, using the proposed ZF scheme, we obtain minimal dipole configurations at each node that achieve this upper bound for K <; 5. Furthermore, we analyze achievable MUXGs using the distributed interference alignment (DIA) algorithm. Although IA can generally provide a higher MUXG than ZF for LOS ICs, we observe that the number of required dipole elements to achieve the optimal MUXG of 2K under a ZF scheme is the same as that required under IA for all cases we consider.