This study introduces and investigates the integration of a cell-free architecture with bistatic backscatter communication (BiBC), referred to as cell-free BiBC or distributed access point (AP)-assisted BiBC, which can enable potential applications in future (EH)-based Internet-of-Things (IoT) networks. To that purpose, we first present a pilot-based channel estimation scheme for estimating the direct, cascaded, and forward channels. Next, we utilize the channel estimates to design the optimal beamforming weights at the APs, reflection coefficients at the tags, and reception filters at the reader to maximize the tag sum rate while meeting the tags’ minimum energy requirements. Because the proposed maximization problem is non-convex, we propose a solution based on alternative optimization, fractional programming, and Rayleigh quotient techniques. We also quantify the computational complexity of the developed algorithms. Finally, we present extensive numerical results to validate the proposed channel estimation scheme and optimization framework, as well as the performance of the integration of these two technologies. Our algorithm yields impressive gains compared to the random beamforming/combining benchmark. For example, it achieves ~ 64.8% and ~ 253.5% gains in harvested power and tag sum rate, respectively, for 10dBm with 36 APs and 3 tags.

Current backscatter channel estimators employ an inefficient silent pilot transmission protocol, where tags alternate between silent and active states. To enhance performance, we propose a novel approach where tags remain active simultaneously throughout the entire training phase. This enables a one-shot estimation of both the direct and cascaded channels and accommodates various backscatter network configurations. We derive the conditions for optimal pilot sequences and also establish that the minimum variance unbiased (MVU) estimator attains the Cramér-Rao lower bound. Next, we propose new pilot designs to avoid pilot contamination. We then present several linear estimation methods, including least square (LS), scaled LS, and linear minimum mean square error (MMSE), to evaluate the performance of our proposed scheme. We also derive the analytical MMSE estimator using our proposed pilot designs. Furthermore, we adapt our method for cellular-based passive Internet-of-Things (IoT) networks with multiple tags and cellular users. Extensive numerical and simulation results are provided to validate the effectiveness of our approach. Notably, at least 10dBm and 12dBm power savings compared to the prior art are achieved when estimating the direct and cascaded channels. These findings underscore the practical benefits and superiority of our proposed approach.

The era of ubiquitous, affordable wireless connectivity has opened doors to countless practical applications. In this context, ambient backscatter communication (AmBC) stands out, utilizing passive tags to establish connections with readers by harnessing reflected ambient radio frequency (RF) signals. However, conventional data detectors face limitations due to their inadequate knowledge of channel and RF-source parameters. To address this challenge, we propose an innovative approach using a deep neural network (DNN) for channel state information (CSI) estimation and signal detection within AmBC systems. Unlike traditional methods that separate CSI estimation and data detection, our approach leverages a DNN to implicitly estimate CSI and simultaneously detect data. The DNN model, trained offline using simulated data derived from channel statistics, excels in online data recovery, ensuring robust performance in practical scenarios. Comprehensive evaluations validate the superiority of our proposed DNN method over traditional detectors, particularly in terms of bit error rate (BER). In high signal-to-noise ratio (SNR) conditions, our method exhibits an impressive approximately 20% improvement in BER performance compared to the maximum likelihood (ML) approach. These results underscore the effectiveness of our developed approach for AmBC channel estimation and signal detection. In summary, our method outperforms traditional detectors, bolstering the reliability and efficiency of AmBC systems, even in challenging channel conditions.

Ambient internet-of-things networks are just emerging to support sixth-generation wireless goals. We thus investigate a symbiotic radio (SR) system for a single-user primary network and a backscatter communication network that supports non-orthogonal multiple access. The primary base station (BS) concurrently supports the primary user and multiple tags, which modulate and reflect their data using the primary BS signal. The user decodes its data and the tags’ data using the successive interference cancellation technique. We propose a novel optimization framework to accommodate the requirements of both the primary user and the tags while also improving SR network performance. By constructing the beamforming vectors to support both primary and backscatter networks, we develop a BS transmit power minimization problem. The problem formulation ensures the various quality-of-service demands of the user and the tags and the tag energy harvesting requirements. Because of the non-convexity of the problem, we employ semi-definite relaxation techniques to obtain a sub-optimal solution. We evaluate the computational complexity of the proposed algorithm. Finally, we present extensive numerical results and simulations that establish the validity and performance gains of the proposed optimization scheme without modifying the fundamental passive tag architecture.

Optimal beamforming design is developed for a nonorthogonal multiple access (NOMA)-aided symbiotic radio (SR) system where a base station (BS) simultaneously serves multiple NOMA users and a secondary ambient tag. The nearest user of the tag decodes its own data and the tag data using the successive interference cancellation (SIC) technique. We design optimal transmit beamforming and power allocation at the BS to maximize the weighted sum rate of NOMA users and the tag, under the minimum rate requirements while satisfying the tag’s minimum energy requirement. Because the problem is nonconvex, we propose algorithms using alternative optimization and fractional programming techniques. Our results reveal that significant performance gains can be achieved while keeping the tag design intact. For example, the proposed beamforming can increase harvested power and data rate by 2.16×103% and 314.5% compared to random beamforming.

This paper conceives a novel sparse code multiple access (SCMA) codebook design which is motivated by the strong need for providing ultra-low decoding complexity and good error performance in downlink Internet-of-things (IoT) networks, in which a massive number of low-end and low-cost IoT communication devices are served. By focusing on the typical Rician fading channels, we analyze the pair-wise error probability of superimposed SCMA codewords and then deduce the design metrics for multi-dimensional constellation construction and sparse codebook optimization. For significant reduction of the decoding complexity, we advocate the key idea of projecting the multi-dimensional constellation elements to a few overlapped complex numbers in each dimension, called low projection (LP). An emerging modulation scheme, called golden angle modulation (GAM), is considered for multi-stage LP optimization, where the resultant multi-dimensional constellation is called LP-GAM. Our analysis and simulation results show the superiority of the proposed LP codebooks (LPCBs) including one-shot decoding convergence and excellent error rate performance. In particular, the proposed LPCBs lead to decoding complexity reduction by at least 97% compared to that of the conventional codebooks, whilst owning large minimum Euclidean distance. Some examples of the proposed LPCBs are available athttps://github.com/ethanlq/SCMA-codebook.

In this paper, we investigate the throughput performance of single-packet and multi-packet hybrid-automatic repeat request (HARQ) with blanking for downlink non-orthogonal multiple access (NOMA) systems. While conventional single-packet HARQ achieves high throughput at the expense of high latency, multi-packet HARQ, where several data packets are sent in the same channel block, can achieve high throughput with low latency. Previous works have shown that multi-packet HARQ outperforms single-packet HARQ in orthogonal multiple access (OMA) systems, especially in the moderate to high signal-to-noise ratio regime. This work amalgamates multi-packet HARQ with NOMA to achieve higher throughput than the conventional single-packet HARQ and OMA, which has been adopted in the legacy mobile networks. We conduct theoretical analysis for the throughput per user and also investigate the optimization of the power and rate allocations of the packets, in order to maximize the weighted-sum throughput. It is demonstrated that the gain of multi-packet HARQ over the single-packet HARQ in NOMA systems is reduced compared to that obtained in OMA systems due to inter-user interference. It is also shown that NOMA-HARQ cannot achieve any throughput gain with respect to OMA-HARQ when the error propagation rate of the NOMA detector is above a certain threshold.

In this paper, we leverage multi-antenna transmit beamforming techniques in order to enable spatial reuse for coexisting LTE and Wi-Fi systems in unlicensed spectrum. For the cellular small cell base stations equipped with multiple transmit antennas and operating in the unlicensed spectrum, some spatial degrees of freedom (DoF)s are dedicated to serving small cell user terminals (SUEs) and others are employed to mitigate interference to the co-existing co-channel Wi-Fi users by applying a linear multi-user precoding technique, such as zero-forcing transmit beamforming (ZFBF). Through careful allocation of spatial DoFs, enhanced spatial reuse of unlicensed spectrum resources can be achieved, thereby improving spectrum efficiency on unlicensed bands. However, due to inherent channel state information (CSI) estimation and feedback errors, ZFBF cannot completely alleviate detrimental co-channel interference effects. After analysing the so-called intra radio technology (intra-RAT) interference among SUEs, i.e., the residual interference caused by imperfect CSI used in ZFBF, and the inter-RAT interference experienced by the Wi-Fi users, we derive the throughput of the co-existing LTE and Wi-Fi systems, respectively. Based on the derived throughput, spatial DoF and power can be optimally allocated to balance the throughput between the small cell and Wi-Fi systems in different scenarios. Our theoretical analysis and proposed schemes are further confirmed with exhaustive numerical simulation results.

In this paper, we study how to reuse the unlicensed spectrum in LTE-U systems while guaranteeing harmonious coexistence between the LTE-U and Wi-Fi systems. For a small cell with multiple antennas at the base station (SBS), some spatial degrees of freedom (DoFs) are used to serve small cell users (SUEs) while the rest are employed to mitigate the interference to the Wi-Fi users by applying zero-forcing beamforming (ZFBF). As a result, the LTE-U and Wi-Fi throughput can be balanced by carefully allocating the spatial DoFs. Due to the channel state information (CSI) estimation and feedback errors, ZFBF cannot eliminate the interference completely. We first analyze the residual interference among SUEs, called intra-RAT interference, and the interference to the Wi-Fi users, called inter-RAT interference after ZFBF, due to imperfect CSI. Based on the analysis, we derive the throughputs of the small cell and the Wi-Fi systems, respectively. Accordingly, a spatial DoF allocation scheme is proposed to balance the throughput between the small cell and the Wi-Fi systems. Our theoretical analysis and the proposed scheme are verified by simulation results.

Small cell base stations (SBSs) have been deployed in heterogeneous networks to improve the spectrum efficiency on licensed channels by reusing the spectrum resource of the macro base station (MBS). To relief the shortage on the licensed spectrum resources, licensed-assisted access (LAA) has been introduced to LTE small cell systems to share the unlicensed channel with the Wi-Fi users. In this paper, we investigate the fundamental tradeoff between the collision probability (CP) to the Wi-Fi users and the co-channel interference (CI) power to the MBS in such a heterogeneous LAA system. A multi-objective resource allocation problem is first formulated while guaranteeing the quality-of-service (QoS) of small cell users (SUEs). Then, the double waterfilling-line power allocation on the licensed and unlicensed channels is developed to analyze the CI-CP tradeoff and the weighted Tchebycheff method is applied to convert the multi-objective optimization problem into a single objective optimization problem. To find the complete set of Pareto optimal solutions to the tradeoff problem, a novel feasibility method is proposed. Based on the simulation results, the proposed joint resource allocation algorithm can achieve a flexible CI-CP tradeoff according to the QoS of SUEs in LAA systems.

The employment of Long-Term Evolution (LTE) in unlicensed spectrum, known as LTE-U, can alleviate the spectrum scarcity problem in the 5G networks. With this new technique, the traditional mobile data offloading schemes, which generally offload LTE users to the WiFi network, should be revisited. In this paper, we propose to transfer WiFi users to the LTE-U network and simultaneously allocate some unlicensed spectrum to LTE-U. In this way, a win-win situation could be generated since LTE can achieve better spectrum efficiency than WiFi in the unlicensed spectrum. To facilitate it, three important challenges are addressed in the paper: which WiFi users should be transferred; how many WiFi users need to be transferred; and how much unlicensed resource should be allocated to the LTE network. We utilize the Nash bargaining solution to design fair unlicensed spectrum allocation between WiFi and LTE-U and thereby a win-win strategy is developed, whose performance is demonstrated by numerical simulation.

Acquiring more spectral resources is a key enabler for the envisioned high data rates of next generation mobile networks. Licensed-assisted access (LAA) to the vast and free-of-charge unlicensed spectrum has been therefore receiving tremendous interest, especially with the advancements in small cells and carrier aggregation. We propose a novel 5G MAC solution for fair and efficient coexistence with WLAN and other 5G operator networks in unlicensed spectrum (5G-U). A UE-centric joint association and channel selection algorithm maximizes the achievable long-term rates. Neighboring LPNs of the same 5G-U network opportunistically form per-channel disjoint radio access clusters (RACs). During an active sensing phase, RACs discover their potential interferers and `contend-to-coordinate' their self-allocation of the unlicensed channel. A self-allocated RAC dynamically optimizes its coexistence frames with WLAN to achieve the estimated soft airtime share over the coordination frame. We generalize the simple sequential inhibition model, which has been shown to accurately model the carrier sense multiple access, to capture the impact of longer LAA bursts as well as the priority access mode in the downlink simulations. Results with single-LPN RACs show substantial coexistence throughput gains compared to two different models of LTE-LAA. Additional gains are realized with multi-LPN RACs in dense deployment and high channel occupancy scenarios.

To improve system capacity, licensed-assisted access (LAA) has been proposed for long-term evolution (LTE) systems to use unlicensed bands. However, the energy efficiency (EE) of the LTE system may be degraded by LAA since unlicensed bands are generally less energy-efficient than licensed bands. In this paper, we investigate the EE optimization of LAA systems. We first develop a criterion to determine whether unlicensed bands can be leveraged to improve the EE of LAA systems. We prove that unlicensed bands can be used to improve the EE only when the allocated licensed resource blocks (RBs) are not enough. We then investigate joint licensed and unlicensed RB allocation to maximize the EE of each small cell base station (SBS) in a multi-SBS scenario, taking into account fair resource sharing between LTE and WiFi networks. The complete Pareto optimal EE set can be obtained by the weighted Tchebycheff method. We also develop an algorithm to provide fair EE among different SBSs based on the Nash bargaining solution. Numerical results are presented to confirm our analysis and to demonstrate the effectiveness of the proposed algorithms.

In this paper, we study cooperative precoder design in two-tier networks, consisting of a macro-cell (MC) and several small-cells (SCs). By exploiting multiuser Vandermonde-subspace frequency division multiplexing (VFDM) transmission, an MC downlink can co-exist with cognitive SCs. In this paper, we first propose a cooperative cross-tier precoder (CTP) among the transmitters in the SCs to increase the transmitted dimension. The cooperative CTP allows us to use more efficient intra-tier precoder (ITP) in SCs to handle intracell interference and improve the throughput of the cognitive system. And then, three ITPs, a block-diagonal zero-forcing (BD-ZF) ITP, a capacity-achieving (CA) ITP, and a generalized MMSE channel inversion (GMI) ITP, are developed. Complexities of all CTPs and ITPs are discussed and compared. The overhead of channel state information (CSI) exchange is analyzed. Numerical results are presented to demonstrate the throughput improvement of the proposed schemes and to discover the impact of the imperfect CSI. From the complexity comparison and the numerical results, the GMI ITP offers a good tradeoff between complexity and throughput.

Traditional mobile data offloading transfers cellular users to WiFi networks to relieve the cellular system from the pressure of the ever-increasing data traffic load. However, the spectrum utilization of the WiFi network is bound to suffer from potential packet collisions due to its contention-based access protocol, especially when the number of competing WiFi users grows large. To tackle this problem, we propose transferring some WiFi users to be served by the LTE system, in contrast to the traditional mobile data offloading which effectively offloads LTE traffic to the WiFi network. Meanwhile, leveraging the emerging LTE in unlicensed spectrum (LTE-U) technology, some unlicensed spectrum resources may be allocated to the LTE system in compensation for handling more WiFi users. In this way, a win-win situation would be generated since LTE can generally achieve better performance than WiFi due to its capability of centralized co-ordination. To facilitate it, three important challenging issues are addressed in the paper: which WiFi users should be transferred; how many WiFi users need to be transferred; and how much unlicensed resources should be relinquished to the LTE-U network. We investigate three different user transfer schemes according to the availability of channel state information (CSI): the random transfer, the distance-based transfer, and the CSI-based transfer. In each scheme, the minimum required amount of unlicensed resources under a given transferred user number is analyzed. Furthermore, we utilize the Nash bargaining solution (NBS) to develop joint user transfer and unlicensed resource allocation strategy to fulfill the win-win situation for both networks, whose performance is demonstrated by numerical simulation.

Traffic offloading and resource sharing are two common methods for delivering cellular data traffic over unlicensed bands. In this paper, we first develop a hybrid method to take full advantages of both traffic offloading and resource sharing methods, where cellular base stations (BSs) offload traffic to WiFi networks and simultaneously occupy certain number of time slots on unlicensed bands. Then, we analytically compare the cellular throughput of the three methods with the guarantee of WiFi per-user throughput in the single-BS scenario. We find that traffic offloading can achieve better performance than resource sharing when existing WiFi user number is below a threshold and the hybrid method achieves the same performance as the resource sharing method when existing WiFi user number is large enough. In the multi-BS scenario where the coverage of small cells and WiFi access points are mutually overlapped, we consider to maximize the minimum average per-user throughput of each small cell and derive a closed-form expression for the throughput upper bound in each method. Meanwhile, practical traffic offloading and resource sharing algorithms are also developed for the three methods, respectively. Numerical results validate our theoretical analysis and demonstrate the effectiveness of the proposed algorithms as well.

Small cell deployment in heterogeneous networks, whereby small cell base stations (SBS) are deployed alongside traditional macro-cell base stations, is a proven solution for enhancing spatial frequency reuse across licensed spectrum in long-term evolution (LTE) networks. In order to mitigate the shortage of licensed spectrum resources, licensed-assisted access (LAA) has been introduced to allow LTE SBSs to share the unlicensed channel with WiFi nodes. As such, a complex yet interesting optimization problem results from the joint utilization of licensed and unlicensed spectrum resources by the SBSs to meet the quality-of-service (QoS) requirements of small cell users (SUEs). In this paper, we highlight the fundamental tradeoff induced by the SBSs between the amount of co-channel interference (CI) resulting from the reuse of licensed spectrum resources and the collision probability (CP) imposed on the co-existing WiFi nodes due to the sharing of unlicensed spectrum resources in such a coexisting LTE LAA-WiFi heterogeneous network deployment. We find that this fundamental tradeoff can be analyzed by developing a power allocation rule with double water-filling lines and the complete set of Pareto optimal solution can be achieved by the weighted Tchebycheff method. Our simulation results show that the proposed joint resource allocation algorithm can achieve a flexible and suitable tradeoff between the licensed spectrum CI and the WiFi CP according to the QoS requirements of SUEs in LTE LAA networks.

Driven by the demand for more radio spectrum resources, mobile operators are looking to exploit the unlicensed spectrum as a complement to the licensed spectrum. LTE-unlicensed (LTE-U), also referred to as licensed-assisted access by the third generation partnership project, is an extension of the LTE standard operating on the unlicensed spectrum. To realize LTE-U, its coexistence with Wi-Fi systems is the main challenge and must be addressed. In this paper, a listen-before-talk access mechanism featuring an adaptive distributed control function protocol is adopted for the small base stations (SBSs), whereby the backoff window size is adaptively adjusted according to the available licensed spectrum bandwidth and the Wi-Fi traffic load to satisfy the quality-of-service requirements of small cell users and minimize the collision probability of Wi-Fi users. Meanwhile, both licensed and unlicensed spectrum bands are jointly allocated to optimize spectrum efficiency. An admission control mechanism is further developed for the SBS to limit collision with Wi-Fi traffic. Extensive simulation results show that the proposed schemes achieve fair and harmonious coexistence between LTE-U small cells and the surrounding Wi-Fi service sets and substantially outperform baseline non-adaptive channel access mechanisms in the unlicensed spectrum.

In this paper, two novel mechanisms are developed for the coexistence of cellular and WiFi systems in unlicensed spectrum. In the opportunistic method, the small cell base station opportunistically selects traffic offloading or resource sharing on each WiFi access point (AP). In the hybrid method, the base station simultaneously offloads users and shares the unlicensed spectrum of each AP. The performances of the proposed methods are analyzed and compared. We find that traffic offloading can achieve better performance than resource sharing when the number of existing WiFi users is below a threshold and the hybrid method achieves the same performance as the resource sharing method when existing WiFi user number is large enough. Numerical results are presented to demonstrate the effectiveness of the proposed methods.

In this paper, an adaptive channel access mechanism is proposed to optimize the performance of licensed-assisted access (LAA) long-term evolution (LTE) small cell networks through joint allocation of licensed and unlicensed spectrum resources all the while ensuring a fair coexistence with Wi-Fi service sets on the unlicensed spectrum. A listen-before- talk (LBT) access mechanism featuring an adaptive distributed control function (DCF) protocol is adopted for the small cell base stations (SBSs), whereby the minimum backoff window size is adaptively adjusted according to the available licensed spectrum bandwidth and Wi-Fi traffic load to satisfy the quality-of-service (QoS) requirements of small cell users (SUs) and minimize the collision probability of Wi-Fi users. Meanwhile, both licensed and unlicensed spectrum bands are jointly allocated to optimize spectrum efficiency. An admission control mechanism is further developed for the SBSs to limit collision with Wi-Fi traffic. Extensive numerical results are presented to demonstrate the effectiveness of the proposed schemes.

Cooperation among network nodes at one side and terminal nodes on the other side are the two main enablers of radio access virtualization to establish scalable and dynamically adjustable data pipes to the users in the 5G mobile networks. User cooperation requires careful design to address cooperation incentive, battery life, user discovery, security and privacy. Dummy user, a network-aware terminal, can facilitate the implementation of user cooperation and leverage its benefits. Dummy users can offer a low cost alternative for the enhancement of the network performance to address persistent or temporary demand such as a hotspot created by an outdoor festival. Proper deployment of dummy users provides fairness and ubiquity of the network while enabling many advanced transmission and reception schemes that require more accurate channel state knowledge at the network.

Licensed-assisted access (LAA) has been developed to improve LTE system capacity by using unlicensed bands. However, the energy efficiency (EE) of the LTE system may be degraded by LAA since unlicensed bands are generally less energy-efficient than licensed bands. In this paper, we investigate the EE optimization of LAA systems. We first develop a criterion to determine whether unlicensed bands can be leveraged to improve the EE of LAA systems. We prove that unlicensed bands can be used to improve the EE only when the allocated licensed resource blocks (RBs) are not enough. We then investigate how to jointly allocate licensed and unlicensed RBs to achieve EE fairness among small cell base stations (SBSs), based on the Nash bargaining solution. Numerical results are presented to confirm our analysis and to demonstrate the effectiveness of the proposed algorithm.

A virtualized radio access network (VRAN) is envisaged in next generation wireless networks. Therein, users experience a seamless ubiquitous service without cell-specific signaling through transparent grouping of densely deployed transmit points (TPs) and helping UEs. Aiming at reducing the Carbon footprint as well as the operational expenditure while maintaining users' QoS, we propose an energy/cost-aware dynamic wideband muting and traffic offloading scheme for the VRAN. The proposed scheme favors muting hypotheses with greater energy/cost savings from TPs with relatively light traffic loads. Such loads are opportunistically offloaded to adjacent TPs to improve their energy efficiency. This is achieved by employing a low-complexity joint wideband muting and multi-point scheduling algorithm optimizing a novel energy-aware utility. The utility accounts for the power consumption models of different TPs, the current cost per unit energy and the TP's predicted 'Soft Loading Ratio'. Operator controls the energy savings-performance tradeoff in individual network regions regardless of the topology. Simulation results show significant energy efficiency and system capacity gains.

Device-to-device (D2D) connectivity is likely to represent a major enabling technology for future fifth generation (5G) radio access networks. In this paper, we introduce a new model for device cooperation in 5G radio access networks termed frequency-selective soft forwarding (FSSF). FSSF is based on soft-combining by a target user equipment (TUE) of selectively forwarded soft information data by a set of cooperating user equipments (CUEs) acting as mobile relays towards the TUE. FSSF exploits the inherent frequency selectivity and broadcast nature of the downlink radio access channel for the sake of enabling efficient device cooperation and seamless integration of D2D connectivity into cellular radio access networks. Several variants of FSSF are investigated, including centralized and distributed approaches, thus offering various tradeoffs of performance versus signaling overhead cost. Exhaustive simulation results using a state-of-the-art long-term evolution (LTE)-compliant link-level simulator show that FSSF well outperforms baseline device cooperation schemes relying on conventional decode-and-forward (DF) relaying and approaches the performance of optimal joint reception with significantly lower cost in terms of D2D resource utilization and signaling overhead.

Virtual radio access (VRA) technology wherein groups of cooperative transmit points (TPs) form virtual TPs (VTPs) to serve user equipments (UEs) continue to be a thriving subject of research in future generations of wireless networks. In this paper, we propose a technique that uses UE-centric metrics to provide multiple partitions of a wireless network into VTP sets. Our technique guarantees that all UEs enjoy a required gain in at least one VTP; effectively eliminating the edge UE experience in the network. To further enhance the performance of the proposed VRA technique in practical scenarios wherein there is a large load imbalance in the network, we also introduce a new concept of soft UE-TP association in which each UE is partially associated with multiple TPs. The use of our soft association concept when forming VTP sets facilitates load-balancing among various TPs. Finally, a technique is also offered to select the best VTP set at each scheduling resource unit. Numerical simulations are used to demonstrate the performance of our virtualization techniques.

In this paper, a multi-antenna two-way relaying protocol is proposed whereby two source nodes wishing to exchange information via a relay node additionally send private messages intended solely for the relay. In particular, we investigate the performance of this bidirectional relaying protocol over fading channels when the relay and source nodes are equipped with multiple antennas thus enabling them to leverage diversity and/or multiplexing gains. Specifically, provided enough antennas are available at the relay, the latter may opt for a demodulate-and-forward approach whereby it demodulates all incoming streams before broadcasting solely the messages to be exchanged between the source nodes or it may opt for a generalized analog network coding approach whereby it only demodulates the private messages destined for the relay's own sake while treating the messages to be exchanged between the source nodes as colored noise, subtracting the demodulated information from the overall received signal and then broadcasting the remaining part of the received signal. We compare how the two approaches fare when coupled with different multiple-input multiple-output (MIMO) detection techniques thus striking suitable tradeoffs between performance and implementation complexity for the generalized multi-antenna two-way relaying channel under consideration.

In this paper, we study the impact of uncertain channel state information (CSI) on the performance of demodulate-and-forward relaying protocols with higher order modulation formats such as pulse-amplitude modulation (PAM) and rectangular quadrature-amplitude modulation (QAM). Assuming a single source and a single destination node assisted by $N$ relay nodes, we study the average bit error probability (BEP) performance of $M$-ary PAM and rectangular QAM constellations with Gray code mapping and imperfect CSI at the relay nodes as well as the destination. The main contributions of this paper are the derivation of closed-form expressions for $a)$ the cumulative distribution functions of the demodulator test statistics, $b)$ the transition probability of error at a given relay, and $c)$ the average BEP for independent and not necessarily identically distributed Rayleigh fading channels with imperfect receiver CSI.

In this paper, we derive closed-form expressions for the average symbol error probability (SEP) of arbitrary rectangular I × J-ary quadrature amplitude modulation (QAM) in cooperative amplify-and-forward (A&F) relaying systems, when no direct line-of-sight exists between the source and the destination nodes and when the links between the K successive nodes forming the multihop cooperation chain (including the source and the destination nodes) follow independent but not-necessarily identical Nakagami-m fading distributions with arbitrary real indexes {mk}k=1Knot less than 1/2 and arbitrary average power levels {γ̅k}k=1K. The average SEP of rectangular QAM for this set-up is provided in closed-form as a linear combination of the first Lauricella's multivariate hypergeometric function, FA(K+1), K being the number of multihop links, which can be efficiently evaluated using standard numerical softwares. Simulation results sustaining our analysis are provided, and the impacts of various parameters on the overall multihop system performance are investigated.

Cross-layer design is a generic designation for a set of efficient adaptive transmission schemes, across multiple layers of the protocol stack, that are aimed at enhancing the spectral efficiency and increasing the transmission reliability of wireless communication systems. In this paper, one such cross-layer design scheme that combines physical layer adaptive modulation and coding (AMC) with link layer truncated automatic repeat request (T-ARQ) is proposed for multiple-input multiple-output (MIMO) systems employing orthogonal space--time block coding (OSTBC). The performance of the proposed cross-layer design is evaluated in terms of achievable average spectral efficiency (ASE), average packet loss rate (PLR) and outage probability, for which analytical expressions are derived, considering transmission over two types of MIMO fading channels, namely, spatially correlated Nakagami-m fading channels and keyhole Nakagami-m fading channels. Furthermore, the effects of the maximum number of ARQ retransmissions, numbers of transmit and receive antennas, Nakagami fading parameter and spatial correlation parameters, are studied and discussed based on numerical results and comparisons. Copyright © 2009 John Wiley & Sons, Ltd.

We propose an intercell downlink orthogonal frequency division multiple access (OFDMA) scheduling technique in a sectorized cellular network. Adjacent sectors from neighboring cells form a cluster and each OFDMA resource block is allocated to the rate-maximizing sector. Compared to a cellular network that uses conventional fractional frequency reuse (FFR) technique, our proposed system requires only slightly more backhaul traffic while providing an appreciable performance gain. Intercell scheduling, which grants a resource exclusively to the rate-maximizing cell within a cluster, is a simple and powerful base station cooperation technique that balances non-cooperation and full cooperation. We find out that a tri-sectored network is particularly well-suited to applying inter-sector scheduling as each cluster is relatively isolated from other clusters. We provide an option to adjust the load on backhaul traffic by adjusting the granularity of the OFDMA resource under contention. We also provide an option to optimally swap resources. Analysis on performance gain for a few configurations are given. Simulations are provided to verify and illustrate the claimed performance gain.

In this contribution, we derive exact closed-form expressions for the average symbol error probability (SEP) of arbitrary rectangular quadrature amplitude modulation (QAM) for single- and multichannel diversity reception over independent but not-necessarily identically distributed Nakagami-m fading channels. The diversity branches may hence exhibit identical or distinctive power levels and their associated Nakagami indexes need not be the same. Our work extends previous results pertaining to nondiversity reception of M-ary rectangular QAM over Rayleigh fading channels and multichannel reception of M-ary square QAM over Nakagami-m fading channels. For a given number L of diversity branches and a corresponding set of arbitrary real-valued Nakagami indexes not less than 1/2, our SEP results are expressed in terms of Gauss's hypergeometric function2F1and Lauricella's multivariate hypergeometric function FD(L)of L variables, both of which can be efficiently evaluated using standard numerical softwares.

The impact of imperfect channel state information (CSI) on the performance of transmit-beamforming (TB) over multiple-input multiple-output (MIMO) Rayleigh fading channels when using constant-power rate-adaptive pilot symbol assisted modulation (PSAM) is investigated. Specifically, imperfect CSI is accounted for with respect to both estimation and prediction errors, thereby allowing to quantify the performance degradation of the adaptive PSAM-based TB system due to both channel estimation and prediction errors. Such errors entail a mismatch between the optimal transmit/receive beamforming weights and the transmission rate implied by the true CSI on the one hand, and the actual values of these quantities as determined based on the estimated and predicted CSI, on the other hand. The compound effect of both estimation and prediction errors on the overall system performance is assessed in terms of the achievable average spectral efficiency, average bit error probability and outage probability, for which approximate closed-form expressions are derived for arbitrary numbers of transmit and receive antennas. Furthermore, the latter metrics are used to optimize the PSAM parameters, namely the power allocation between data and pilot symbols as well as the pilot spacing in order to maximize the achievable average spectral efficiency while adhering to a fixed target bit error probability.

This paper proposes a decentralized adaptive soft frequency reuse scheme for the uplink of 4G long-term evolution (LTE) systems. While universal frequency reuse (UFR) is being targeted for next generation multi-cellular wireless networks, ongoing efforts supporting the LTE standard have proved that actual implementations of UFR in LTE lead to unacceptable interference levels experienced by user equipments near the cell edge area in a multi-cellular configuration. The herein proposed adaptive soft frequency reuse scheme is a step forward towards effective inter-cell interference coordination (ICIC) in next-generation wireless networks. Our solution to the uplink ICIC problem stands out for its two essential features that consist of physical resource block (PRB) reuse avoidance/minimization and cell-edge bandwidth breathing which can be implemented at the cost of a negligible information exchange over the X2 interface (backbone). The PRB reuse avoidance feature significantly decreases inter-cell interference levels while improving the achievable average throughput per user, especially for those identified as cell-edge ones. The cell-edge bandwidth breathing strategy allows to track and adapt to semi-static changes in traffic loading and user distributions within each cell which drastically reduces the blocking probability of incoming calls under cell-edge bandwidth constrained traffic.

In this study, the impact of mobility is investigated in low-speed environments such as femtocells and picocells for wireless networks. Given that there is interference on the uplink of a FDD system, this study solely focuses on how interference evolves with respect to mobility of terminals which move in a random fashion. Wiener-Levy process is used as a stochastic tool for characterizing the impact of mobility on the future behavior of interference. The results show that there is a trade-off between short and long interference observation (measurement) interval. On the one hand, choosing a short interval leads to a waste of processing power, since the interference level to be observed is not expected to deviate drastically from the previous observations. Choosing a long interval, on the other hand, increases the variance of the density of future interference level. In addition, results show that if there is more than one interference source in motion, the interference level observed has a tendency to increase in the future in low mobility environments. It is also shown that mean value of the interference level density to be observed in the future increases, whereas its standard deviation decreases with respect to the number of interference sources in motion.

This paper investigates the capacity of multiple- input multiple-output (MIMO) wireless communication systems when instantaneous channel state information (CSI) is available at both the transmitter and the receiver in a line-of-sight Rician fading environment. Specifically, an infinite series representation for the ergodic capacity of MIMO channels subject to uncorrected Rician fading (URiF) is derived, assuming both transmitter and receiver CSI. The ergodic capacity and its associated outage probability are expressed as a function of a cutoff value capturing the optimal power allocation scheme. Moreover, an equation for evaluating the cutoff value using standard numerical search techniques is derived, along with closed-form expressions for the capacity of the URiF MIMO channel when the so-called eigen-mode channel inversion technique and its truncated variant are implemented. We then provide numerical results showing the effects of Ricianness on the capacity of the eigen-mode optimal power and rate adaptation, and the sub-optimal channel inversion techniques and compare the achievable spectral efficiencies with and without channel knowledge at the transmitter thereby highlighting the capacity gains enabled by channel side information in a Rician fading environment.

This paper investigates the impact of spatial fading correlation and keyhole (pinhole) condition on the capacity of multiple-input multiple-output (MIMO) channels when instantaneous channel state information (CSI) is available at the transmitter and receiver sides. A separable correlation model is considered, whereby spatial fading correlation is accounted for at either or at both sides of the collocated MIMO wireless channel. Two extreme scenarios of a double scattering environment are analyzed: (i) an extremely rich scattering environment corresponding to a conventional semi-correlated Rayleigh fading channel and (ii) a double-correlated rank-deficient keyhole channel with a single degree of freedom. In the case of semi-correlated Rayleigh fading, the capacity expressions are derived for two types of correlation structures among the transmitting or the receiving antennas, namely, a constant correlation model and an arbitrary correlation model, the latter being induced by a full-rank Hermitian covariance matrix with non-repeating distinct eigenvalues. On the other hand, the capacity expressions pertaining to the double-correlated keyhole channel are derived given arbitrary Hermitian covariance matrices at the transmitter and the receiver. For all channel types and correlation structures, closed-form expressions for the capacity of the eigen-mode optimal power and rate adaptation policy as well as for the sub-optimal eigen-mode channel inversion and its truncated variant are derived. Monte Carlo simulations are also carried out thereby upholding our theoretical analysis.

This paper investigates the impact of fading correlation and channel degeneracy alias keyhole condition on the capacity of multiple-input multiple-output (MIMO) spatial multiplexing systems when instantaneous channel state information is available at the transmitter and receiver sides. Two special scenarios of a double scattering channel model are analyzed: (i) an extremely rich scattering environment corresponding to a conventional semi-correlated Rayleigh fading channel whereby correlation is accounted for either among the transmitting or the receiving antennas and (ii) a rank-deficient keyhole channel with a single degree of freedom and zero correlation at both sides of the wireless link. For both fading scenarios, closed-form capacity expressions are derived in terms of a cut-off signal- to-noise ratio which must be solved for numerically. In the case of semi-correlated Rayleigh fading, the capacity expressions are obtained for two kinds of correlation structures, namely, a constant correlation model and an arbitrary correlation model, the latter being induced by a full-rank covariance matrix with non-repeating distinct eigenvalues. Monte Carlo simulations are also carried out thereby upholding our theoretical analysis.

In this work, we derive exact closed-form expressions for the average symbol error probability (SEP) of arbitrary rectangular quadrature amplitude modulation (QAM) when used along with orthogonal space-time block coding (OSTBC) over independent but not necessarily identically distributed multiple-input multiple-output (MIMO) Nakagami-m fading channels. The derived SEP expressions account for diversity branches which may exhibit identical or distinctive power levels while their associated Nakagami indexes can take arbitrary real values not less than 1/2. Our work extends previous results pertaining to the performance analysis of OSTBC using M-ary rectangular QAM over Rayleigh fading channels and M-ary square QAM over Nakagami-m fading channels. For a MIMO diversity system with nTtransmit and nRreceive antennas and a corresponding set of arbitrary real-valued Nakagami indexes, our rectangular QAM SEP results are expressed in terms of Lauricella's multivariate hypergeometric functions FD(L)and FD(L + 1)where L = nTnRis the total number of diversity branches.

In this paper, we characterize the eigenvalue distribution of Hermitian matrices generated from a set of independent zero-mean proper complex Gaussian random (PCGR) vectors with an arbitrary common covariance matrix. Such random matrices follow the so-called Wishart-type distribution, a generic designation for both Wishart and pseudo-Wishart distributions. More specifically, we propose new simple expressions for the probability density function (PDF) and derive the cumulative distribution function (CDF) of any subset of unordered eigenvalues of Wishart-type random matrices with arbitrary finite dimensions. Many interesting results can be deduced from the foregoing distributions. In particular, one can straightforwardly deduce the statistics of the largest eigenvalue of Wishart-type random matrices, thereby paving the way for the second contribution of this paper, namely, analyzing the average error probability of dual multiple-input multiple-output (MIMO) systems using maximum-ratio transmission (MRT), subject to frequency-nonselective semicorrelated Rayleigh fading. Furthermore, Monte Carlo simulations are carried out and shown to be in perfect match with the corresponding analytical results, thereby illustrating their validity.

This paper characterizes the eigenvalue distributions of full-rank Hermitian matrices generated from a set of independent (non)zero-mean proper complex Gaussian random vectors with a scaled-identity covariance matrix. More specifically, the joint and marginal cumulative distribution function (CDF) of any subset of unordered eigenvalues of the so-called complex (non)central Wishart matrices, as well as new simple and tractable expressions for their joint probability density function (PDF), are derived in terms of a finite sum of determinants. As corollaries to these new results, explicit expressions for the statistics of the smallest and largest eigenvalues, of (non)central Wishart matrices, can be easily obtained. Moreover, capitalizing on the foregoing distributions, it becomes possible to evaluate exactly the mean, variance, and other higher order statistics such as the skewness and kurtosis of the random channel capacity, in the case of uncorrelated multiple-input multiple-output (MIMO) Ricean and Rayleigh fading channels. Doing so bridges the gap between Telatar's initial approach for evaluating the average MIMO channel capacity (Telatar, 1999), and the subsequently widely adopted moment generating function (MGF) approach, thereby setting the basis for a PDF-based framework for characterizing the capacity statistics of MIMO Ricean and Rayleigh fading channels.

This paper investigates the capacity of multiple-input multiple-output (MIMO) wireless systems when instantaneous channel state information (CSI) is available at both the transmitter and the receiver in a line-of-sight Rician fading environment. Specifically, an infinite series representation for the ergodic capacity of uncorrelated Rician fading MIMO channels is derived, assuming both transmitter and receiver CSI and a specular component of arbitrary rank. The ergodic capacity and its associated outage probability are expressed in terms of a cutoff level capturing the optimal eigen-mode power and rate adaptation. Moreover, an equation from which the cutoff value can be solved for numerically is derived for arbitrary numbers of transmit and receive antennas.

In this paper, we characterize the eigenvalue distribution of Hermitian matrices generated from a set of independent zero-mean proper complex Gaussian random vectors with an arbitrary common covariance matrix. Such random matrices follow the so-called Wishart-type distribution, a generic designation for both Wishart and pseudo-Wishart distributions. More specifically, we propose new simple expressions for the joint probability density function and cumulative distribution function of any subset of unordered eigenvalues of Wishart-type random matrices with arbitrary finite dimensions. We further show how one can extract many interesting results from the foregoing distributions such as the statistics of the extreme eigenvalues. In particular, we focus on the statistics of the largest eigenvalue of Wishart-type random matrices, thereby paving the way for the second contribution of this paper, namely, analyzing the average bit/symbol error probability of dual multiple-input multiple-output systems employing maximum-ratio transmission, subject to frequency-nonselective semicorrelated Rayleigh fading.

In this work, we provide a new framework for the analysis of the multiple-input multiple-output (MIMO) Ricean and Rayleigh fading channel capacity statistics under the assumption of perfect channel knowledge at the receiver, no channel state information at the transmitter and isotropic Gaussian distributed inputs. More specifically, we show that by deriving the marginal densities of the unordered eigenvalues of (non) central Wishart matrices, it is possible to generalize Telatar's approach for evaluating the average channel capacity, to derive the capacity variance as well as its higher order statistics, such as its skewness and kurtosis, for a class of MIMO fading environments, including the uncorrelated Rician and Rayleigh fading and the semicorrelated Rayleigh fading, thereby alleviating the need to resort to the moment generating function approach so far used in the open literature. Numerical results are also provided and sustained by Monte Carlo simulations in order to show the perfect match between the theoretical and simulation results.

The impact of imperfect channel state information (CSI) on the performance of transmit-beamforming (TB) over multiple-input multiple-output (MIMO) Rayleigh fading channels when using constant-power rate-adaptive pilot-symbol-assisted modulation (PSAM), is investigated. Specifically, imperfect CSI is accounted for with respect to both estimation and prediction errors. Such errors entail a mismatch between the optimal transmit and receive beamforming weight vectors and the constellation size for adaptive modulation as implied by the true CSI and the actual values of these parameters as determined according to the predicted CSI, thereby degrading the performance of the adaptive PSAM-based TB system. The compound effect of both estimation and prediction errors on the overall system performance is assessed in terms of the achievable average spectral efficiency, average bit error probability and outage probability, for which approximate closed-form expressions are derived for arbitrary numbers of transmit and receive antennas

Orthogonal space-time block coding (STBC) is an open-loop transmit diversity scheme that decouples the multiple-input multiple-output (MIMO) channel, thereby reducing the space-time decoding into a scalar detection process. This characteristic of STBC makes it a powerful tool, achieving full diversity over MIMO fading channels, and requiring little computational cost for both the encoding and decoding processes. In this paper, we exploit the single-input single-output equivalency of STBC in order to analyze its performance over nonselective Nakagami fading channels in the presence of spatial fading correlation. More specifically, we derive exact closed-form expressions for the outage probability and ergodic capacity of STBC, when the latter is employed over spatially correlated MIMO Nakagami fading channels. Moreover, we derive the exact symbol error probability of coherent M-PSK and M-QAM, when these modulation schemes are used along with STBC over such fading channels. The derived formulae are then used to assess the robustness of STBC to spatial correlation by considering general MIMO correlation models and analyzing their effects on the outage probability, ergodic capacity, and symbol error probability achieved by STBC.

In this paper, we exploit the single-input single-output equivalency of orthogonal space-time block coding (STBC) in order to analyze its performance over nonselective Nakagami-m fading channels, in the presence of spatial correlation. More specifically, we derive the exact average symbol error probability (SEP) of coherent M-PSK and M-QAM, when such modulation schemes are used along with STBC over correlated Nakagami-m fading channels. Besides, for integer values of the Nakagami parameter m, closed-form expressions for the derived SEP formulae are provided. Moreover, in the latter case, we also derive exact closed-form expressions for the ergodic Shannon capacity of STBC, when used in the presence of spatially correlated Nakagami-m fading channels. Numerical results are provided to assess the robustness of STBC to spatial correlation, by analyzing the effects of specific correlation parameters on the achievable symbol error probability

In this paper, we capitalize on some recently derived results yielding the probability density function (PDF) of the largest eigenvalue of complex central Wishart matrices with independent and identically distributed entries, to derive a closed-form expression for the capacity of adaptive transmission with the so-called multiple-input multiple-output (MIMO) maximal ratio combining systems, also known as transmit-beamforming (TB) systems, under Rayleigh fading. The achievable spectral efficiency by this type of MIMO systems is derived for two power and rate allocation policies, namely, the optimal power and rate adaptation policy (opra) and the channel inversion with fixed rate policy (cifr). The spectral efficiency of these adaptive transmission policies when used along with TB is evaluated and compared for different MIMO antenna configurations.

In this paper, we derive general closed-form expressions for the Shannon capacity achieved by orthogonal space-time block coding (STBC) over Rayleigh fading channels under adaptive transmission and channel estimation errors. Adaptive transmission can be performed on a frame-by-frame basis provided that a channel state information (CSI), consisting of the SNR level as estimated by the receiver, is fed back to the transmitter, thereby allowing for different compromises between the achievable capacity and the corresponding implementation complexity. The closed-form capacity formulae, derived for different power and rate allocation policies, are expressed in terms of the number of transmit and receive antennas, the code-rate of the STBC mapping, the average SNR per receive antenna, and a single parameter capturing Gaussian channel estimation errors. Numerical results showing the effects of the estimation errors on the capacity of STBC subject to the adaptive transmission policies under consideration are provided.

Transmit-beamforming (TB) over multiple-input multiple-output (MIMO) fading channels steers the transmit power in the receiver's direction, so as to maximize the output signal-to-noise ratio (SNR) after maximal ratio combining (MRC) at the receiver. This letter proposes a simple algorithm that allows evaluating an exact and tractable expression for the probability density function of the SNR at the output of the TB receiver, subject to Rayleigh fading. The latter enables the derivation of closed-form expressions for the outage and ergodic capacity of MIMO MRC systems under Rayleigh fading, thereby avoiding the need for time-consuming numerical integrations or Monte Carlo simulations.

In this paper, we investigate the capacity of orthogonal space-time block coding (STBC) in Rayleigh fading, subject to different power and rate adaptation policies. These policies can be performed on a frame-by-frame basis provided that partial channel state information (CSI), consisting of the signal-to-noise ratio (SNR) level as estimated by the receiver, is fed back to the transmitter. This allows for adapting the transmit power and rate to the variations of the fading channel using different policies that provide for different compromises between the achievable capacity and the corresponding implementation complexity. In particular, we derive exact closed-form expressions for the Shannon capacity of three power and rate adaptation policies, namely, the optimal power and rate adaptation, the total channel inversion with fixed rate policy, and its variant, the so-called truncated channel inversion with fixed rate policy.

The aim of this paper is to provide a framework for cross-layer management of packet-data transmissions in MIMO systems employing orthogonal space-time block coding (STBC) over Nakagami fading channels. The framework integrates physical layer adaptive modulation and link layer truncated automatic repeat request (T-ARQ), in an attempt to maximize the system's spectral efficiency under prescribed quality of service requirements such as delay and error rate constraints. The performance of the proposed scheme is assessed via three metrics for which we derive closed-form expressions. These metrics consist of the average packet error rate, the average spectral efficiency and the outage probability. We illustrate our analysis through numerical results showing how the combined cross-layer design significantly outperforms both physical layer adaptive modulation and link layer T-ARQ when solely one of these adaptive techniques is used in conjunction with STBC.

In this contribution, we first derive the Shannon capacity of MIMO orthogonal space-time block coding (STBC) in Rayleigh fading, expressing it in closed-form as function of the number of transmit and receive antennas, and the average received signal-to-noise ratio (SNR). We then assess the performance of M-ary quadrature amplitude modulation (M-QAM) used in conjunction with STBC. The performance of this rate adaptive policy is evaluated in terms of its induced average bit error rate and average spectral efficiency, the latter being compared to the derived Shannon capacity which represents the upper bound on the achievable spectral efficiency for any practical approach to adaptive modulation (AM) using STBC.

We consider packet scheduling and rate assignment on the uplink of a packet data wireless CDMA network in the presence of imperfect interference cancellation (IC) and limited user transmission rates, and subject to in-cell and out-of-cell resource limitations. The objective is to propose and implement a system level position-based flow control algorithm that accounts for a limited IC capability provided by power control for multi-user detection. The proposed algorithm assigns packets to be transmitted to separate queues, one for each spatial zone within which packets generate roughly the same in-cell interference and impose equal interference on a neighboring base station. Given the cell partitioning into zones, the algorithm dynamically adapts to the resource constraints and efficiently uses IC to provide for fairness in serving the various queues without giving up the objective of maximizing data throughput. Throughput and fairness are two conflicting objectives to be optimized. We show that the joint use of IC and location-based scheduling is able to achieve complete fairness with negligible loss in throughput even under stringent resource limitations.

Abstract We consider packet scheduling and rate assignment on the uplink of a packet data wireless CDMA network in the presence of imperfect interference cancellation (IC) and limited user transmission rates, and subject to in‐cell and out‐of‐cell resource limitations. The objective is to propose and implement a system level position‐based flow control algorithm that accounts for a limited IC capability provided by power control for multi‐user detection. The proposed algorithm assigns packets to be transmitted to separate queues, one for each spatial zone within which packets generate roughly the same in‐cell interference and impose equal interference on a neighboring base station. Given the cell partitioning into zones, the algorithm dynamically adapts to the resource constraints and efficiently uses IC to provide for fairness in serving the various queues without giving up the objective of maximizing data throughput. Throughput and fairness are the two conflicting objectives to be optimized. We show that the joint use of IC and location‐based scheduling is able to achieve complete fairness with negligible loss in throughput even under stringent resource limitations. The IC technique implemented is based on the interference subspace rejection (ISR) technique. We investigate both successive and group cancellation modes of ISR. Through the zone‐based grouping of users, the flow control algorithm provides a high flexibility in taking advantage of IC and is general enough to adapt to situations with constraints on the transmission rates. Results provided show how group‐based scheduling with group‐cancellation can provide for high fairness even under stringent out‐of‐cell resource limitations. Copyright © 2003 John Wiley & Sons, Ltd.